Welcome everyone to the session from Sam. He's with us to talk about creating an unexpected moment for good with agile. So without much further delay, over to you Sam. Thank you and good afternoon everyone. Namaste. Namaste from me. I'm Sam. I'm coming to you from Sydney, Australia. It's a pleasure to be sharing this story with you today. So welcome. The story today is a fascinating one, which I'm really excited to be sharing.  My day job is teaching and helping people to learn about agile. And I think it's a great privilege to help people learn and grow every day. Before I became a full-time agile trainer with the scrum alliance, I was working at ComBank in Australia and ComBank are one of the largest agile companies in the whole of Australia and Australia's largest biggest bank. So I've seen lots of things in terms of how agile works at ComBank, but also I have been involved over many years. And I'm going to share some of those stories with you today in terms of what I've learned. Now I want to kick off today with a video. And the video is going to tell the story of this movement, an unexpected movement for good with agile. You're going to hear from some of these companies that I've been working with. They're all not for profits. They are doing things to help the community and they're using agile.  We're going to go for about three minutes with the first video. So video goes for three minutes and then we will pause and then I will get into the detail of my chat. I'm Sam from Red Agile. We are Australia's leading agile and scrum training organisation. At Red Agile, we like to help people who help others. Every training course has places free of charge for our partners from the not for profit community. Let's take a look at the impact this has had on their businesses and our communities. Welcome to our guests. My name is Andrew Miller. I was harvest Australia. Adam from cerebral palsy alliance. Carmen for BBMU support. And Anna Melton from Indigenous Consulting Group. Hi, I'm Natalie from MPS Medicine Wise. My name is Olivia and I'm from Beyond Blue. How does your not for profit help everyday Australians? We are not for profit mental health organisation that provides support and services to the community in Australia with a focus on anxiety, depression and suicide prevention. We give out scholarships for young people in agriculture, trade and water culture to go overseas for work experience. We're an indigenous owned business and specialised in cultural awareness training. We also deliver mental health first aid training out in very remote areas. Ground breaking, global centre of expertise, cerebral palsy research, advocacy, intervention and assistive technology innovation. Development of healthcare education products. We're a food rescue charity. What's the impact been of Agile? We've used Agile now with Sam, coaching for a few years. I think the key benefits for us, it keeps a check on our productivity. It's given us a tool to review, do that continually, really embed continual improvement in the way that we function. Our journey with Agile and Scrum has been truly transformational for our little team and for our organisation. We became a self-organising team. We had greater transparency and trust. We knew what each other were doing and not just get on with each other, but actually be able to do large chunks of each other's work. Learning more about Agile has helped us better embrace community centricity. We are engaging and testing with our community regularly and able to respond to their feedback more quickly. The impact of learning more about Agile has been profound. We needed to improve our ability to not only adapt to change, but thrive through change. Instrumental in this was the engagement of the Sam and Stuart Red Agile, which provided our newly created team with the confidence and courage to challenge the old ways of working. We'd like to extend a very big thank you to Sam and the team at Red Agile. Through COVID, it's allowed us to be very nimble and swap from a face-to-face training platform to an online version. Working in Agile matter has streamlined and facilitated the development of healthcare education products. For example, whilst clinical leads are verifying clinical content, medical writers are developing the next stream of work. Thanks to Agile, NPS MedicineWise is able to develop robust healthcare educational products in a shorter time frame. All right, we're going to pause the video there. I'll come back and go into a bit more depth when we get to the end of the session. So all of these organizations, we've been helping in different ways. And if you look at the different things that they do, cerebral palsy, helping people with disabilities, Os Harvest are a food rescue company. All of these companies are doing different things. Beyond Blue are working with people with mental health and suicide. All these companies are using Agile to help them run their not-for-profits better and to help them do more great things in the community. I'm going to share this story with you and talk about why we did this. Why did all of this come about? Why did we create this movement? And I called it an unexpected movement. I did not set about and plan to do this. What's happened in the last six years has been surprising and phenomenal. I'll talk about why it all started. I'll then talk about what we did. What did we do? And I'll talk about how could you do something like this? How could you get started and create something that may be an unexpected movement for good? So let's start with why. Why did this whole thing start? Now I'd like please to get some input from all of you in the chat, in the chat channel. Make sure you're sending a message to everybody. What do you think is the critical success factors in us delivering projects at work? Everyone put something in the chat. Use the zoom chat, press the chat button. What do you think is the most critical success factor for project delivery? Prasanth, thank you. Prasanth says the team. Give me some more please. This is the interactive bit for the team in India and wherever you are in the world. What else? So team, thank you Prasanth. What else please? Shridhar talks about inclusion of the stakeholders. I like it. Give me some more. Empathy, thank you Tej. Tej is talking about empathy. Give me some more. What do you think are the critical success factors for delivering projects well? Let's get one more view. All right, I'm going to move on. So thank you for sharing. Let me give you Sam's view. So thank you Vijay. Focus on value. Now I've been working and delivering projects for many, many years and the success factor for me is simple. Look after the humans. Look after the humans. Let me tell you what do I mean by that? Look after the humans. There are three things that I want to give you in terms of looking after the humans. Number one, care about their well-being. Care about the well-being of the people on the project team. But also care about their development in terms of what they might do next. If you help people with what they do next they're going to help you and do more right now. So help them with their future. Number two, know the people. Know them. Know them. Build relationships with them. Get to know them beyond the workplace. Build genuine relationships with them and then support them. Make sure you've got their back. That's the second part. The third part of the people is not just you maybe as the scrum master or the leader whatever your role is. Help everybody get to know everybody. A high-performing team, everyone knows everyone and everyone's got everyone's back. That to me is the secret for creating a high-performing team. Look after the people and the rest will just happen. The rest will just happen. So that's my first premise. The first premise for this talk is that we need to look after the people delivering our projects. That was kind of at the heart of where this whole movement started looking after our own people who were delivering the work. So as part of this and creating teamwork, I started to think about how can I create this sense of teamwork? What can I do, and this was by the way when I was a project manager, what can I do to open spaces for people to build relationships outside of work? I'm going to share with you some of the things that I did to what I call open spaces for people to build relationships and rapport. One of the first things I did many, many years ago was we got external companies in who had all of these games that you could play outdoors and we had some fun working and learning games with ropes. So we just did some play. So just playing and I know that in India, having been to India many times, I've been to India three, four times to work with teams there.  So this was an outdoor game playing with ropes, one of the first things I did. I also did an amazing race in Sydney and we did a selfie challenge. This is the project team. Look at their faces. These are people at work getting paid. This is what I mean by helping people have fun, creating spaces for them to have fun. It was a fantastic day and also doing things like this, kayaking and having fun maybe with just having a picnic in the park and having a barbecue together. So opening spaces where people can just chat and they can have some fun. The other thing I did was in terms of understanding each other as humans is I started to look at personalities and how do we understand each other as humans. Now some of you may have done some of these tools at work. They help unpack. What am I like as a person? On the top left you've got disc which is a quite common one in the corporate world. At the bottom there's a tool called human synergistics. On the top right is TMS team management systems and on the bottom right is a free one. So if you want a free one write this down. It's called 16 personalities. If you want to learn more about your people get them to do the 16 personalities survey.  We understand how we are similar but also we understand how we are different. So this is an example of some of the team building days that I used to do to try and create a sense of team and then an opportunity came up to do volunteering and I decided to send a team on a volunteering day to see what happened and what I wasn't expecting is that when we helped our project teams do something in the community something amazing happened. The impact for people was huge. This is one of the events that we did. We took a whole team of people to Oz Harvest where we were cooking food. You can see on the table in front the way we were working. Everyone was cooking. We were cooking rescued food.  The food that we cooked went out into the community and was given to the people who needed food. It's called cooking for a cause. It's a fantastic team building activity and the people absolutely loved it. This is a recent photograph of my team here at Red Agile in Sydney doing cooking for a cause just at the end of the pandemic and here's the food that we cooked. Phenomenal. The food that we cook is fresh, beautiful food and it goes straight out to people in need. Another activity that we did was the New South Wales Special Olympics. We were helping people with disabilities learn different sports. They were doing things like throwing. They were doing basketball. We were teaching them with running races. Just simple stuff. It wasn't the real Olympics. This was just a fun Olympics where people with all sorts of disabilities could come together and we would help them learn. We were connecting our project team to people in the community who are less advantage than us. The final one was called Cana Farm and this was a place where people came to rehabilitate. People had been in prison. People who were long-term drug abusers. They're not the people on the screen. The people on the screen in my project team. The project team went to work on the farm with these people and they had conversations. Imagine talking to people who have got long-term drug addiction problems who are trying to rehabilitate themselves. It was confronting but it was amazing in terms of the conversations that we had. These three ladies are all recovering from drug abuse of some sort and one of them has been in prison. We helped them in terms of how we can work with them and learn from each other. A fantastic day, a huge impact on the people in our team. But then there was an impediment. I was doing all of these activities and I was being supported by my manager but then my manager left and the manager that supported me doing all of this team building and community work the new person who came in was less supportive. The new person who came in didn't think this was a good use of time and it impacted me. It impacted me and I had to dial it down for a while. I did the only good thing that you can do which was move into a different job in the company and I started again. If you've got a manager that doesn't support you to do this stuff I think it's so important. If we can't look after the humans you've got to do something about it. You've got to fight for this stuff. It's so important. These volunteering days the volunteering days that we did were the things that people enjoyed the most because they were helping others and as well as having some fun as a team they were giving back. That's why we started this whole connection with Not For Profits started with team building. That's why it started and it was a formula that motivated our people to come to work and help them make a difference. It was a winning formula. That's the why. That's the why. I'm just going to pause and just ask you all to share in the chat. What have you been doing with team building? Just share something in the chat please. What sort of things have you done in terms of team building and have you done something in the community? Maybe you've done some things in the local community with your project teams. Please put a message in the chat. What have you done in terms of team building events? How do you connect? Maybe it's going for a drink. Maybe it's having a meal together. Share something in the chat. What have you done with your teams please? This is the interactive bit. Please share something in the chat. What have you done? What have you done? A virtual lunch in the pandemic. Thank you, Prasant, for sharing. Icebreaker sessions is great. Yeah, icebreaker sessions to get to know people. Virtual coffee, Vijay. Thank you. A lot of the things in the pandemic made this stuff harder. Going for lunch together. Hopefully now we're back in the office a bit more. We can do more of these things. Connect as humans. I remember when I came to India, so many times I'd go for dinner with the teams. We'd do some fun stuff after work. So many things. We went to the cricket sometimes to watch the the IPL. So many good things. Thank you for sharing. Let's talk about what happened now. So how did things move? How did we start this agile movement? How did this all start? I was at an agile conference just like you are today and the agile conference was in Melbourne in 2016. It was Agile Australia. And there was a keynote presentation from Margarit Purvis. And she had come over from New York. She works at the New York Food Bank. She's the CEO. And she told a fascinating story of when two people from a company called Toyota came into her company and made a massive difference. In just eight weeks, they brought in some process improvements and really made a difference to how her food bank was working. And this gave me a spark. This gave me a spark. I thought wow if these two people from Toyota can just go and help the food bank what can I do? What can I do like this to help others? It was within six months I was at back at Oz Harvest and I was doing cooking for a cause, the charity event, and I got my lightbulb. I spoke at Agile India for the first time back in 2018 and thank you for having me back. So four years ago I was speaking in India and I told this story. I told the story of what happened and how the movement got started with Oz Harvest. I'm now going to kind of tell you what's happened in the last four years since I shared this initial story. So it started with one not-for-profit. Here is our very first not-for-profit attendees coming to a training class. So the movement works like this. I teach training courses. They're two-day training courses for people in corporates and every time I run a training course two people from a not-for-profit can come for free. I've been teaching today. So I've just finished teaching. It's 7.30 p.m. here in Sydney. I was teaching today. There were two people from a not-for-profit today on a training course. In this picture there are two lovely ladies who work for Oz Harvest. This was the first time we had participants come to the class and they came free of charge to learn about scrum and agile and then lots of interesting things happened. But the first thing that happened is after they'd come on the first training course I went into their office to see what had happened. So we'd trained them in scrum and agile. I was hoping they were starting to do some good things. Now I went back to their office and each person had created a visual management board above their desk to do, doing, done. The next person had a visual board above their desk to do, doing, done. They'd missed the point. Instead of it being a team visual management board each person had created their own visual management board of their own to-do list. They missed the point so I realized I had to give more. So rather than just training I gave some more time just like the team had done at Toyota and I gave some coaching. I was coaching them to work in scrum and I was helping them learn and grow beyond the training course. More people started to come from Aus Harvest to our training. I was lucky enough to meet Marguerite Pervis two years after the first time that she spoke in Australia. She came back again and it was fantastic to meet with her and share with her how she had given me this spark and this light bulb. Back at Aus Harvest what have we been doing in the last four years? So many things. I run team building events for them. We won retros with the people who drive the vans around Australia. We've done strategy days. I've done fundraising in terms of getting the bank that I was working for come back to donate a lot of money towards one of their educational programs. So it led to a movement of coaching mentoring team building. I would just go and help them every week in some way and they would decide how I could best help them. I didn't expect it to evolve like this in terms of helping Aus Harvest and it then evolved to more not-for-profits. Our first not-for-profit was Aus Harvest. As I was speaking at different Agile conferences in Australia I met not-for-profit people who were in the room. So not-for-profits had started to get involved in the Agile movement. I met some people from the cerebral palsy alliance who work with people with disabilities. I met some people from NPS Medicine Wise who are doing medical research using Agile and I invited them to join our classes. I was working for a big bank. I was training people in Agile and Scrum and the not-for-profits were coming for free. This is when the movement really started to get some traction. It became a way of working. Every training course not-for-profits came. Every training course we gave it away for free and we were helping people. And I was also connecting coaches. Learning from the lesson that coaching is important. I was connecting Agile coaches to each organization. So we're having Agile coaches giving their time for free to help the organizations beyond the training course. Two years ago I left ComBank. I left the bank I was working for who'd supported me through this and I joined a company called Red Agile who I now work for here in Australia. And I'm now a full-time trainer. So what's awesome now a full-time trainer? I can do even more of this. And my partner, Stu, who you can see on the screen, has supported this and between us we are helping more and more not-for-profits and even though I change companies we're still doing this great work. We have nearly a thousand Google reviews for what we do with a leading Agile training company in Australia and maybe in the Southern Hemisphere. We actually get a lot of people come from India, from Bangalore, from Chennai to come on our training and we're very proud of what we do. We got too successful. We got so successful with our training that the pressures, the courses were full and how can we keep giving away the free places on the course if it's full?  And there was a moment when it was suggested to me that we stop offering free places for not-for-profits. And I said this, if we stop doing this, I'm out. This meant so much to me in terms of what we were doing for the community. I was prepared to leave. So we kept going. We squeezed them in. We squeezed them in by hook or by crook. We were working virtually. We squeezed them in and we kept going. I'm going to share the second part of the video. We're going to listen to a little bit more detail now on specifically what have they done with Agile. Here comes the next three minutes. Hopefully the audio is good. Here we go. Second three minutes of the video. Let's go deeper into some of the specific stories and examples. And give visibility across the organization around what is happening, the ability to remove roadblocks much quicker, just an overall efficiency in what we do. So thank you Sam for teaching us your techniques. This emphasis, together with Customer Centre Design, has led us to develop an industry-first portal that allows our clients to manage their services with us, with clients being involved in the discovery, prototyping and pilot phases. This process has taken us months where previously it might have taken years. We've learned to fail fast, how to prioritize and reprioritize, and make sure that value fights for its life. So when we started our Agile journey in 2019 with a new CEO, we had previously been trained by Sam and Red Agile. We saw the impact almost immediately. Continuously deliver value to continue to be a high-performing team and have the satisfaction of delivering meaningful valuable work. So that was fantastic. And the greatest impact of this Agile transformation for us has been that everybody shows up with enthusiasm and everybody truly loves their work and we work beautifully together as a team. We do it with enthusiasm and that's really what we want to think about Agile and Sam for. Working in this manner has also acted as a risk management tool. Once the stream is completed and reviewed, errors made are addressed immediately. In the past, MPS medicine-wise worked in a waterfall manner, meaning that the entirety of the content would be built and reviewed which then caused a lot of rework if errors were made. We've also developed a lot of new products so we've used this methodology to roll this out and it's been a huge success. So thank you again to everyone at Red Agile. Our team's a cross-functioning so we always have the right capabilities in the room to make the best decisions and the collaborative atmosphere is a great environment to work in. We embrace stakeholders to become more involved. Now they have more context and better forms to give feedback and this has allowed the team to move faster without lengthy approval processes. They trust our capabilities more and now trust us to release changes to the community faster and more regularly. Team autonomy is creating a psychologically safe environment for members to speak up more, to have healthy conflict and to also chance to change and improve our workflows and processes. We will continue to be Agile and learn new things in the organization but after four months we are already at the amazing part where myself and team are empowered and enthusiastic about our jobs, what we deliver and how we work together every day. So it just warms my heart to see the impact of what we're doing. The story is about value fighting for its life and that focus on delivering value. The story is about teamwork and how people are connected as humans at work and doing fantastic things as high performing teams and the feedback loops people have created. So phenomenal just to hear so many different stories about the different not-for-profits that we've been training is actually making an impact and that's why we do it of course. We do it for the impact and how we can help them help them help others. All of these companies are helping people in different problem spaces in Australia. The people who are homeless, we've got Mission Australia who look after the homeless, we've got FoodWaste, we've got lots of companies around mental health and mental health support as well as dealing with people and helping people with disabilities. So I'm very proud of the organizations we've helped and what the impact has been. So let's change track now and go to how you could do something like this. How could you create a movement for good or how could you just do something that helps motivate and inspire your team to know each other better as humans and to do some some great things together. So in terms of what I would love you to think about is what motivates your people. I worked out what motivated teams in Australia which was doing team building around volunteering. That's what motivated the people here but what motivates your team? What is it that gets them excited and how can you give them more of it? So I want you to start with that. Let's not just copy however Sam's done this but what can you do? So what motivates your team? When it comes to purpose and working on something bigger or something of a higher purpose, Zappos who are an online shoe retailer, there's really nice kind of how happy we are at work. If you kind of deliver great work you're happy. If you deliver working flow and you're really engaged with the work you're happier. But if you can be part of something bigger than that you're doubly happy. So really looking at this engagement. If we can get involved with something of higher purpose it really helps us in terms of engagement. Zappos have got some great family core values which I enjoy and brings them this purpose which is to be a family. That's how Zappos present themselves as an organization.  The purpose for Patagonia is the environment and everyone who works they gather around that purpose and give something back. But it's not just about purpose. The work of Ryan and Deckey help us understand what motivates people at work and there are four things that motivate people at work. Make a note of these please write them down if you're taking some notes. The first thing that motivates us at work is called autonomy. And it's giving people the freedom to work on what matters for them. You're giving the freedom to decide how they how they do their work. When they work give people autonomy. Stop micro managing them give them autonomy. That's the first thing that motivates people. The second thing that motivates people is mastery. Help me get better at what I do every day. Help me improve. Help me do more of the stuff I love and give me feedback. Mastery is the second element. The third element is purpose. Doing something for a higher purpose which is kind of linked to where I've been talking about all afternoon. And finally relationships. The people you work with of course are going to motivate us if we work with great people. So let's take a quick look at these and I'm going to see this is another interactive piece please. In the chat think about autonomy. What have you done to create autonomy? In the chat channel please. The Zoom chat. Interactive part of the talk everyone. In the Zoom chat. What have you done or how have you seen others create more autonomy to people? And as a reminder autonomy means freedom to decide how they do their work. Freedom on when they work. Freedom on who they work with. What have you seen? And I'll give you some of my examples. Examples in the chat. What have you seen in terms of autonomy please? How have you created more autonomy? I shall wait another few seconds. Okay we've got one for from Percent. Thank you. Team members feeling that they've been trusted. Yeah nice. Trust their decisions. Trust them and allow them to fail. Love it Percent. Rashmi empowering them to take decisions. Yeah support those decisions. What's the worst that can happen? Allow them to make those decisions and support them. Fantastic suggestions. Tajasvi having a hip sprint. What does hip mean? Giving them the freedom to bring. So an innovation sprint. Love it. Here's a few more ideas. Great suggestions. Here's a few more ideas. 10% time. Give them 10% time and this is similar to your hip sprint. 10% time. Could be 10% to innovate, to learn whatever they want. Yeah 10% to do something different. Give up control. Give up control. Let them have that control over what they do. Involve them in setting their goals and let them set their own goals rather than forcing goals on them and allow them to work when they want and where they want. The hours of the day and the location and COVID has helped with that for sure. Number two is mastery. In the chat channel please. What have you seen around mastery? Now let me remind you what mastery means. Mastery means helping people get better at something. Maybe they enjoy a certain skill or they've got certain skills. How can they get mastery at their craft? How do we help them get better? That's allowing them to learn or giving them feedback. What have you seen please? Allow them to experiment is nice. Thank you Rashmi. What else have you seen? How have you given them mastery? Helping them grow their skills and to learn. One or two more suggestions please. What have you seen to increase mastery? Continuous learning is nice. Giving them space to learn. Yeah permission to learn almost. Give them permission to learn. It's interesting with Singapore. I've done a lot of work with Singapore this year. So many people come on a training course on the weekend because they're not given permission to learn by their bosses. They're having to learn at the weekend. So give people space to learn. Thank you Sherida. Last one or let me give some examples so we've covered the first one. The space and time for learning ongoing training opportunities. Cross-skilling is a good one. So cross-skilling in other words teach them each other's jobs. A Goldilocks task. Remember Goldilocks from the nursery rhymes. The Goldilocks task. It's not too difficult but it's not too easy. It's challenging enough and then genuine two-way feedback. Genuine two-way feedback. And Prasanth, I love your example. Support from the company to sponsor their learning interest. At DBS in Singapore they created a scholarship where anyone in the company could ask to go on a training course. The company would pay for it. Guess what? Here's the catch. All you've got to do is teach it back to others at work. They would pay for your training. You just got to come and teach others. Which I think is a great way to look at it. We'll send you on a course. I think there's a budget of about one or two thousand dollars. And in return you teach this back to others at work. Phenomenal. Last one, purpose. We've been talking about purpose. Doing something for a bigger reason. What have you got please in the chat? What have you done in the community with your teams? How have you helped people understand the bigger purpose? Either the bigger purses of what they're doing at work but how have you connected them with a bigger purpose beyond the office please? Beyond the office. What have you seen? Purpose. How do we create purpose and meaning for people at work? Suggestions. What have you seen? Could be within the company in terms of your product or connecting them to the purpose of what you're doing as an organization or it could be something beyond the workplace. What have we got? Any examples please? Workshops and sessions. Thank you Tejasfi. Thank you. What else? How have you created a sense of purpose? Connecting them with the why is beautiful Rashmi. Connect with the why. Why are we doing this yeah? Why are we doing this? What's CSR? Help me with that one Rashmi in the chat. But the purpose of what we're doing often we overlook that. I remember coming to India on my first ever trip and I was interviewing people in Bangalore who were working for different clients across the world. I said what are you working on? They said they told me they said oh we're working this code. I said why are you doing it? We don't know we're just doing code. They didn't understand the why. Connect people with the why. Thank you Rashmi. Corporate social responsibility giving back to the society and many organizations do this and I was fortunate enough working for ComBank that we did lots of this. So we've covered the giving the context on why we came up with that well done. Making them time to get closer to the real customer. Help them get close to the real end customer. Connecting the team to the bigger picture of the company and then volunteering opportunities to give back. There's copies of the slides with all of these top tips that you can get after the class. I've made all the slides available. So ask your team what motivates them and then open spaces for them to have more autonomy helping them grow mastery and connect them to something meaningful. This is going to help make a big difference in your team. Some of the specific things that I'll give you in terms of ideas.    You use your skills to help them deliver their work. So you go into a company for a few hours or for a few days and you help them with some work. It's called skilled volunteering. That's what a lot of what I've been doing has been around. Team building volunteering is where you take a team of people to and not for profit and you do something together. Maybe you're going to do some weeding in the garden of the local church or you're painting a wall or whatever it is you're doing but you take a team just to do team building so you don't get involved in their core business as a skilled volunteer would but you just do something of value to help them not for profit. The other suggestion with scrum and agile is that if you're working with a local church or a local community or a local group how can you help them run projects with agile? The skills you have you will be amazed. People in the community need your skills in terms of helping them work better. How can you help them with that? There's a few ideas for you. I'm going to finish the talk with the video. How do you create a movement? I wasn't expecting to create a movement. Check out this video you're going to love it. How to correct a movement? Watch the video carefully. Watch the video carefully. If you've learned a lot about leadership and making a movement then let's watch a movement happen. Start to finish in under three minutes and dissect some lessons.  This is key. You must be easy to follow. Now here comes the first follower with a crucial role. He publicly shows everyone else how to follow. Notice how the leader embraces him as an equal so it's not about the leader anymore it's about them, plural. Notice how he's calling to his friends to join in. He takes guts to be a first follower.  Being a first follower is an underappreciated form of leadership. The first follower transforms a lone nut into a leader. If the leader is the flint the first follower is the spark that really makes the fire. Now here's the second follower. This is a turning point. It's proof the first has done well. Now it's not a lone nut and it's not two nuts. Three is a crowd and a crowd is news. A movement must be public. Make sure outsiders see more than just the leader. Everyone needs to see the followers because new followers emulate followers not the leader. Now here come two more people than three more immediately. Now we've got momentum. This is the tipping point and now we have a movement. As more people jump in it's no longer risky. If they were on the fence before there's no reason not to join in now. They won't stand out. They won't be ridiculed and they will be part of the in-crowd if they hurry. And over the next minute you'll see the rest who prefer to stay part of the crowd because eventually they be ridiculed for not joining. And ladies and gentlemen that is how a movement is made. So let's recap what we've learned. If you are a version of the shirtless dancing guy all alone remember the importance of nurturing your first few followers as equals. Making everything clearly about the movement not you. Be public. Be easy to follow. But the biggest lesson here did you catch it? Leadership is over glorified. Yes it started with the shirtless guy and he'll get all the credit but you saw what really happened. It was the first follower that transformed a lone nut into a leader. There's no movement without the first follower. See we're told that we all need to be leaders but that would be really ineffective. The best way to make a movement if you really care is to courageously follow and show others how to follow. When you find a lone nut doing something great have the guts to be the first person to stand up and join in. So great video on how to create a movement in terms of getting people behind the idea. I was the lone nut. I was the lone nut. The first followers were the other agile coaches who helped me. Let's just finish with the impact that we have. Let's finish with the impact then we'll go to some questions. The impact was this. We have trained more than 15 not-for-profit organizations. We have trained more than 1,000 people in Australia in not-for-profit organizations. They have had 16,000 or more hours of training and it's valued at 1.2 million but to me it's not about the the value of this financially. It's about the impact that it's had to all of these amazing organizations. Let's go to Q&A. Thank you so much. Thank you so much for having me. Sam, inspiration with the understatement. I should say seeing all this but we do have a question from DigiSwee. As for agile, we say people who are process but still in reality we are responsible to check if agile is being followed in the design manner. So isn't this contradictory to what has been stated in Scrum Guide? I mean the Scrum Guide talks about people in process, individuals and interactions over processes and talks. But if I look at the Scrum Master and what your job is as a Scrum Master your job is to create a high-performing team. Let's not lose sight of that. Because I focused on the people doesn't mean I don't care about the outcomes. If you look after the people they will deliver amazing outcomes and you will get a high-performing team. It is about results. It's not just about let's be nice to each other. Great question. Do we have more questions? I know we're close to time. Any more questions? We don't have one but there is some amount of appreciation from Prashant. It was a great session. It helped me to understand why people care is important. Thank you so much and thank you to all of you who've joined the session. Enjoy the rest of Agile India everyone. Thank you for having me again. This is my fourth time coming to Agile India. It's been a pleasure to help you learn today. Enjoy the rest of the day.


Our final speaker this morning is Jonathan Newman. Jonathan is a young man. We're very pleased to have become associated with the Institute. He is a PhD student across the street at Auburn University, and perhaps some of his students are in the room as well. He is also a summer fellow with us last year in 2014, and he's really proven to be a great friend of Mises Institute, and he's going to speak today at greater length on inflation and business cycles, which have been alluded to in some of the earlier talks. But he's going to really hopefully expand our understanding of what inflation is, and when he's done, prepare your questions, we'll have a brief Q&A among the various speakers. With that, Jonathan. Thank you, Jeff. I'm a little jealous that both Jeff and Mark were, they had the nice topics of where does money come from, how does the market produce money, and what the world could look like if we had our way as economists. And so if Dan and I start foaming at the mouth, it's because we have the bad topics. We get to talk about war, inflation, and business cycles. And so since I'm sort of prone to ramble, I'm going to try to stick to the script here, but here we go. I'm going to talk about inflation and business cycles. The word inflation means different things to different people. One popular conception of inflation focuses on prices, all prices actually. For these people, including some economists, inflation means a rise in the general price level, that is the goods and services we buy become more expensive. The other conception of inflation focuses on the money supply. Economists with this focus think of inflation as an increase in the amount of money in the economy. We'll see that viewing inflation as a rise in prices can be misleading and ambiguous, especially compared to viewing inflation as an increase in the money supply. First of all, prices can rise for many reasons. If the demand for something increases relative to its supply, or if the supply of something decreases relative to the demand for it, the price will increase. And the fundamental reason for this is called diminishing marginal utility. Increasing our stock of some good means that it will go toward the satisfaction of a lower ranked end. If the next marginal unit goes toward a lower ranked end, then the most we are willing to pay for the next unit will be less than the previous unit. You might be willing to pay $600 for one Apple Watch, which came out of the market today, but the most you would be willing to pay for another might be $100. Maybe as a gift for somebody, or so that you could wear two on both of your wrists. Think of how cool that would look. Even though this sounds pretty limiting in terms of the reasons prices can rise, these two concepts, supply and demand, can and do channel all sorts of changes in the market. Preferences can change, goods can go in and out of fashion, accidents can happen that reduce our supply of a certain good. We can think of new and more efficient ways of producing goods. Services that at one time could only be done with human labor can be replaced or complimented with new tools and machines and so on. The list of things that affect supply and demand is infinite, depending on how specific you get, but the important thing to remember is that all of these sorts of changes are integrated into and channeled through our preferences and ideas and therefore supply and demand. Secondly, there is really no good way to measure a general rise in the price level. You may be familiar with indexes like the consumer price index, which are calculated and compiled based on survey data and technical mathematical methods, but by their very nature, they cannot appropriately measure the price level. They cannot do so because these sorts of indexes are one number. They try to boil the trillions of pieces of data on the prices of all goods and services in the economy down to just one piece of data. Market prices, which are a complicated phenomenon on their own, fluctuate not only year to year, but month to month, day by day, and even second to second. Also, there is no central repository of price information. Even in one country, prices emerge in a very scattered, decentralized way, from the halls of Washington, DC, to the dark back alleys of downtown Chicago, from the lots of car dealers with neon paint to hand to hand to pocket tips for bell hops and restaurant servers, from fleeting ones and zeros soaring at light speed across the internet to long-term contracts for land use or film production. One number couldn't even begin to describe the magnitude and dynamic nature of something like the price level. It would be like driving out west for a camping trip and going to the remotest location at night to view the stars and a meteor shower, and then a month later, when you return to civilization and cell service, you text your parents what the view is like and say, it was cool. Price index information is delayed, incomplete, and by its very nature incapable of describing the astronomical picture of market prices. And we haven't even mentioned the well-sided issues with surveys, government data, and the more specific issues with the particular measurements. A third issue with viewing inflation only has arrived in the price level is that it stops short of explaining the full consequences of monetary inflation. Many people correctly understand the relationship between the price level and the money supply. More money means higher prices. And they also understand that this relationship is bad for the average Joe. Now, Dr. Solerna, whose first name is Joseph, is not averaged by any measure. But we can say that if he is one of the later receivers of new money, he has to pay higher prices before his own salary increases due to inflation, however you define it. In this way, inflation is not harmless. It represents a wealth transfer to the first users of the new money from the later users of the new money as it ripples through the economy. Even though most people know and understand this consequence of increasing the money supply, it stops short of explaining the full consequences of monetary inflation, which will be developed in the second part of my talk. But to summarize, viewing inflation as a rise in the price level has at least three main problems. It is ambiguous because almost anything can change prices. It is impractical because it can't be appropriately measured and it is incomplete because it doesn't tell the whole story of increases in the money supply. Inflation is more appropriately viewed as an increase in the money supply and this conception of inflation does not suffer the same problems as the other. Monetary inflation has a simple, well-defined cause unlike price inflation. Monetary inflation is measurable because money is its own unit of account and can be counted up unlike price inflation, which is not directly measurable. Monetary inflation is also the starting point for the business cycle story instead of the stopping point for many, like price inflation. Before we can discuss the ups and downs of the business cycle, we have to gain an understanding of two connected concepts, the interest rate and production. The interest rate is a price, like any other price, but for present money. It seems weird that buying money or it seems weird that you can buy money, but if you just reverse your perspective of any regular transaction, buying money becomes an obvious and ubiquitous part of our day-to-day lives. When you buy an Apple Watch or two, if you want one on both wrists, you exchange money for the device. From Apple's perspective though, they are not only selling the watch, but buying your money. The price of your $600 is one Apple Watch. The interest rate is a price for present money in terms of future money. When you take out a loan, you are buying present money in exchange for the promise of a future payment. The relative difference between these two sums is the interest rate. And just like any other good, the lower the price, the more people will want to buy. At lower interest rates, more people are willing to borrow. In modern times, we've outsourced a lot of the lending to banks, which act as financial intermediaries. Banks use our savings to lend to prospective borrowers, and so the supply of loanable present money depends on how much people save. Said another way, it depends on how much people consume since saving is the opposite of consumption. The indirectness of borrowing and lending through banks does not complicate things too much. In fact, it makes it easier for us to conceive of the supply of loans as being made up of savings. Entrepreneurs are some of the primary borrowers of present money. Entrepreneurs buy factors of production like land, labor, and capital to produce goods and services. They will only engage in production, though, if they expect to profit. That is, if their revenues exceed their costs. If they borrow money to pay for the factors of production, then the profit would also have to exceed the interest they promise to pay for the borrowed funds. For this reason, the interest rate is a vital piece of information for entrepreneurs. If interest rates are high, then only highly profitable lines of production will be undertaken. If interest rates are low, then more lines of production become profitable. In an unhampered market, interest rates are determined by supply and demand. If people become more willing to part with their present money or save, then the supply of loanable funds will increase relative to demand, and the interest rate will fall. At the lower interest rate, more lines of production will become profitable because now entrepreneurs can borrow more cheaply to purchase factors of production. Since this scenario started with people becoming more willing to save, it's also clear that the entrepreneurs will be able to purchase the real resources required for production. Consumers have shown that they're willing to consume less, so now more resources can be used by producers for production. Let's walk through a specific example of how this works. Suppose Tim Cook has an idea for how to produce one million Apple watches and expects revenues from his sales to exceed his cost by about 10%. He doesn't have the money to pay for the machines and the laborers and the factories required to produce the watches, so he needs to borrow. The current interest rate is 15%, unfortunately for Tim Cook, so we just hold on to his idea for the time being. However, a couple months later due to increased willingness for people to save and invest, the interest rate falls a whopping 10% down to just 5%. Tim Cook reevaluates his plan and his expectations of profitability and decides to go for it. He borrows the money necessary to pay for laborers, machines and factories and starts producing Apple watches. He sells his product and gets revenue that exceeds his cost by 12%, which was a little more than he was expecting. He pays back his creditors the amount he promised 5%, which left him with 7% all to himself for taking the risk and producing something that consumers like. The lower interest rate in this example encouraged the entrepreneur to produce and also signal to the entrepreneur that resources have been freed up in the economy for use in production. Now let's see what happens when entrepreneurs get a false signal from credit markets via monetary inflation. When a central bank decides to increase the money supply, the new money enters the economy through the same markets that people borrow and lend. The new money increases the supply of present money available for lending, which as we all know will decrease the price or the interest rate in this case. To be clear, this time the lower interest rate does not reflect people's willingness to save or invest, but only reflects the central bankers intervention. This artificially low interest rate sends all of the same signals to entrepreneurs and lenders that a normal interest rate does, but it is not based on people's real preferences. When the central bank increases the money supply and interest rates fall, it induces more borrowing and less saving. Entrepreneurs are more than happy to take out the loans at the lower interest rate, but everybody else is less willing to save at the lower interest rate. The newly printed money makes up the difference. Less saving means more consumption, and since the interest rate is so low, they may even borrow to finance even more consumption. Entrepreneurs take their funds and purchase factors of production, and at the new lower interest rate, the lines of production they undertake are the ones that weren't as profitable before. Everybody is happy as they consume, invest, earn higher wages, start new projects, and enjoy the ride to the top. The high cannot last forever, though. Even though spending is climbing on all fronts, no new resources have been created, just new green slips of paper. The economy has not allocated real resources away from consumption and towards production, it has just stretched the existing resources thin. The signals entrepreneurs rely on were falsified and based on the whims of a few powerful people, not the collective voluntary interactions of individuals everywhere. The boom peaks and falls into a bust when some combination of these events unfolds. One, when the increasingly scarce factors of production become too expensive. Two, when the monetary spigot gets turned off and so consumption and investment run dry. And three, when people start to realize the damage that has been done. The bust is characterized by under and unemployment falling prices and a readjustment of capital through the economy. The bust is painful but necessary and healthy. Capital and laborers have been misallocated, funds malinvested and lines of production that appear to be profitable are revealed to be unprofitable in hindsight. The correction happens during the bust, in fact, the bust is the correction. Resources need to go where they are most highly valued and the only system capable of such a daunting and huge task is the unhampered market economy. In the past and up to today, the necessary correction hasn't been allowed to run its course before central banks reinflate and restart the cycle. So it's unfortunate that we have to call the boom bust cycle instead of the boom bust event. If it were a one time thing, we might forgive the ones responsible and say, okay, that was an interesting experiment. We didn't really think it was going to work but now everybody knows. Sort of like the George Clooney and Arnold Schwarzenegger Batman movie. Just as the term business cycle suggests, the artificial booms and the painful busts continued because some people, especially the government and those connected stand to benefit at the expense of others and because of a general lack of understanding of even the fundamental mechanisms at work. It's so dreary. So let me try to end on a positive note. We can avoid the mess. People are getting into and developing currencies that are not tied to our fractional reserve and central banking system. Newer technologies are being adopted for loans to be processed at rates less affected by central bank manipulation. Many people are realizing the disastrous record of central banking and expansionary monetary policy. The same people are learning the way to real economic growth via real savings and economically sustainable uses of our resources. Maybe one day we'll look back at the wrecking ball swings of our current economy the same way we look at the Batman and Robin starring George Clooney and Arnold Schwarzenegger laughing but cringing and shaking our heads. Thank you.


How to Shrink a Sweatshirt If you bought a sweatshirt and later realized it's too big, don't worry. You can easily shrink your fabrics or your sweatshirt fits better. Try submerging your sweatshirt in hot and or boiling water, and use a hot heat setting to launder your garment. If your shirt is not shrunk enough after using the washer and dryer, run an iron over top of a wet sweatshirt. With either method, you may be able to shrink your sweatshirt to your liking. Using the washer and dryer. Check the tag to review washing instructions and material type. View the tag on your shirt to see if the garment has any specific washing instructions. Some fabrics easily shrink with heat, while some fabric will not shrink at all. If the tag tells you to wash your garment in cool water, you can wash it in warm water to shrink it. For example, cotton easily shrinks, as does cotton and polyester blends. Synthetic fabric like rayon and nylon do not shrink. For example, cotton easily shrinks, as does cotton and polyester blends.Synthetic fabric like rayon and nylon do not shrink. Wash your sweatshirt in hot water as a first attempt to shrink it. To do this, put your sweatshirt in a clean sink, and run hot water over the garment for 5-10 minutes. Let the sweatshirt cool down to room temperature, and then check the sizing. If you are satisfied with the amount your sweatshirt shrinks, you can launder it as normal.  To check the size, hold the shirt up to your torso and examine it in the mirror. Submerge your cotton sweatshirt in boiling water to shrink the fabric. If your sweatshirt did not shrink enough after using hot water, boil a large pot of water on high heat. When your water comes to a boil, submerge your garments, put a lid on the pot, and turn off the heat. The boiling water helps shrink your shirt even more. If you want to shrink your shirt even more, use boiling water as a first attempt to shrink the fabric. If you are satisfied with the amount your sweatshirt shrinks, you can launder it as normal. If you want to shrink your sweatshirt even more, use boiling water, your washing machine, and or your dryer, to check the size, hold the shirt up to your torso and turn off the heat. If you want to shrink your shirt one size, leave it in the water for 10 to 15 minutes. If you hope to shrink your shirt two sizes, let it cool to room temperature. Do not do this if washing a polyester sweatshirt. The high temperatures can make the fabric rough or stiff. Polyester should not be heated above 178 degrees Fahrenheit 81 degrees Celsius. Alternatively, put your sweatshirt in your sink and pour boiling water over top the garment. Then, let it cool to room temperature. If you want to shrink your shirt one size, leave it in the water for 10 to 15 minutes. If you hope to shrink your shirt two sizes, let it cool to room temperature. Do not do this if washing a polyester sweatshirt. The high temperatures can make the fabric rough or stiff. Polyester should not be heated above 178 degrees Fahrenheit 81 degrees Celsius. Alternatively, put your sweatshirt in your sink and pour boiling water over top the garment. Then, let it cool to room temperature. Select the hot water setting on your machine after applying hot water. After you've soaked your sweatshirt in hot and or boiling water, put it in your washing machine. You can wash your sweatshirt with other garments you want to shrink, such as T-shirts.  After you wash your sweatshirt, check the sizing before you put it in the dryer.ss equals, reference, aria label equals, link to reference 4, greater than to maximize your shrinkage, use the longest washing size. If you just want to shrink it one size, you can use a normal wash cycle.  Once the sweatshirt is dry, you can try it on to check the fit. Put your sweatshirt in the dryer on the hottest heat setting. If your sweatshirt is still not your desired size, use a very warm heat setting on the longest drying time. This can shrink your sweatshirt an additional size. If your sweatshirt is shrunk to your liking, follow the drying directions on your garment tag. Most list a medium heat setting and normal drying time. Check the fit of your sweatshirt after it cools to room temperature. After the dryer cycle is complete, take out your sweatshirt and lay it on a flat surface. Once your sweatshirt is at room temperature, put it in to check your overall fit. If your sweatshirt did not shrink adequately, try using an iron to shrink it another size. If your sweatshirt did not shrink adequately, try using an iron to shrink it another size.


My name is Darrell Bullens. I am the president and CEO of Forensic Technologies based in San Diego, California. We provide forensic services for a lot of governmental agencies. We currently have 26 contracts providing polygraph, computer forensics, and digital forensics. I've been involved in the credibility assessment world since the year 2000. I've been involved in many of the polygraph organizations. When I first heard about Eye Detect, I was the president of the California Association of Polygraph Examiners. I became concerned that this new technology might be like some of the other credibility assessment tools that have come along in the past and not really be up to par. I wanted to find out for myself so I went and met with Dr. Kircher and his team at the University of Utah and listened to what they had to say and also did a practical test with the Eye Detect instrument and was blown away to be quite honest and quite shocked and surprised. It was not what I expected at all. I went there expecting to find out that this was simply yet another tool that came along that didn't work and it was quite the opposite experience and I have been pleased to be on board with Converis team ever since.


Reservoirs have been built in almost all of the hydrographic basins of Brazil. Main impact is the change from Lodic to Lentic water, which influences aquatic fauna, including fishes. Most affected species are the rheophilic and long-distance migratory that require distinct habitats to fulfill their life cycles. This article was authored by A.A. Augustino, F.M. Pelicis, and L.C. Gomez.


So, we were discussing convergence of characteristic functions right. So, one theorem one result we said was. So, if so this we proved yesterday if x n converges to x n distribution then c x n of t converges to c x of t for all t right. This is a theorem we proved yesterday. So, convergence in distribution necessarily implies the convergence of characteristic functions. This we proved using score card and dominated convergence theorem right. We did this proof. Now, we were talking about the opposite. So, the converse. So, if you were if you is it true that if the sequence of characteristic function goes to has a certain limit is it true that you have convergence in distribution right. So, this is the result we were talking about. So, it turns out. So, I will state this properly. So, let x n be a sequence of random variables with characteristic function c x n of t and let x be a random variable with characteristic function c x of t. If c x n of t converges to c x of t for all t then x n converges to x in distribution. So, what this theorem says I think I did not state it very precisely in towards the end of the last class this is the correct statement. So, if you have a sequence of characteristic functions which converges to the characteristic function of another random variable then you have convergence in distribution. So, the catch is that you may have the sequence of random variable sequence of characteristic functions converging to some function of t which is not a valid characteristic function. It may happen that way. So, what do I mean not a valid characteristic function. So, three properties. So, a characteristic function has to have three defining properties right. The one is that it should absolute value is not equal to 1. Then you must have you must have absolute uniform continuity and you must have non-negative kernel right. Every characteristic function is a non-negative kernel. See if these three properties even if one of them is not satisfied by the limit function it will not be a valid characteristic function and there is no question of convergence distribution. However, if the limit is a valid characteristic function namely if you can verify that c x o the limit satisfies these three fundamental properties then you have convergence in distribution. Try constructing an example of a sequence of characteristic functions which converges to something that is not a characteristic function. It is fairly easy. So, that is that. So, now actually there is a more refined theorem called continuity theorem which says that you do not even have to check all three properties of the limiting function right. Here what we are saying is that if a sequence of characteristic function goes to some function you have to verify the three basic properties of a characteristic function to verify whether or not it is a legitimate characteristic function. It turns out that you do not have to do that. You do not have to work so hard. You do not have to verify all three conditions. In fact, it turns out it is enough to verify continuity of the limit function at t equal to 0. So, if your limit function is continuous at t equal to 0 you are guaranteed that you have convergence in distribution. So, that is because. So, I will. So, it is somewhat involve theorem. It is a fairly sophisticated theorem. It involves again some tools from harmonic analysis, complex analysis and all. I will tell you fundamental reason or it is may be I will state it and then explain. So, continuity theorem for convergence of characteristic function right. So, this says. So, let X n be a sequence of random variables with characteristic function C X n of t. This is the sequence of characteristic functions and suppose limit n tending to infinity C X n of t exist for all t. Then either one of the following is true actually then exactly one of the following is true. So, let us call this limit some C of t. So, this limit exist for all t. I am calling this function C of t. Of course, the C of t I am not saying that it is a valid characteristic function. I am going to say more about it. If C of t is discontinuous at t equal to 0. So, then one of the following is true. So, then I said C of t is discontinuous t equal to 0 and in this case X n does not converging distribution. But, the other possibility is C of t is continuous at t equal to 0 and in this case C of t is a valid characteristic function of some random variable X and X n necessarily converges in distribution to X. So, this theorem says that this limit is some C of t. So, there are only two possibilities. So, A is C of t you check for continuity at t equal to 0. If it so happens that C of t is discontinuous at t equal to 0 the limit is discontinuous at t equal to 0. The C of t cannot possibly be a characteristic function because characteristic functions are continuous. In fact, they are uniformly continuous. So, C of t cannot be a characteristic function and in this case you can conclude that X n does not converging distribution to anything, which means F X n does not converge CDF does not converge. The other possibility is if you have continuity at t equal to 0 that is all you need. Then it automatically becomes a characteristic function and of some random variable and you have then convergence distribution that is because when you have if the limit is a characteristic function then you have convergence in distribution. So, why do you think this is true. So, intuitively without going into the mathematics of the proofs why do you think this is true. So, I am saying that if C of t has to be valid characteristic function I need to satisfy the three basic properties. But I am saying now that it is enough to check for continuity at t equal to 0 not even for other values of t. It is enough to check for continuity not even uniform continuity for or non negative kernels and so on. See the C of t it might happen that C of t is continuous at t equal to 0, but does not have the other properties of the characteristic function. But this theorem is saying that is not possible if you have continuity equal to at t equal to 0 you are guaranteed that it is a valid characteristic function. Do you have any guesses on why this is happening. That is the convergence of some valid characteristic function. That is essentially the reason see because the C of t is not some arbitrary function of t it is obtained by. So, it is obtained as the limit of a sequence of characteristic functions. So, these guys already have a lot of structure to them they have all the properties of a characteristic function. So, whatever limit it has I mean it is not some limit of an arbitrary sequence of functions it is already has a lot of structure to it. So, it is so turns out that if you just verify continuity at t equal to 0 all the other structures will fall into place. Equally uniform continuity and non-negative corner all that will work out automatically. Because the C of t is not any old function of t it is obtained as a limit of a sequence of characteristic functions which already have a lot of structure. So, this bit is very useful. So, I take the limit of some sequence of characteristic functions and I only verify continuity at t equal to 0 then immediately assert convergence in distribution. So, this theorem will be very instrumental in proving central limit theorem and even weak law of large numbers any questions on this. So, I forgot there is one result that is outstanding still. So, I should have done this last class the previous class there is one result that I forgot to do which I will just mention now. This says this is about convergence in earth mean this is something I should have done in the previous class. Theorem x n converges to x in the earth mean implies x n converges to x in the s th mean if r is bigger than s bigger than or equal to 1. So, this result basically says that if you have convergence let us say convergence in mean square r equal to 2 then you necessarily have convergence in the mean. So, if you have convergence for a bigger value of r convergence in smaller value of s in the mean. So, this is something I forgot to mention seems believable. So, the proof of this actually the proof of this follows in a straight forward way from an inequality called Lyapunov's inequality. So, it follows from Lyapunov's inequality and that brings me to a digression about a certain geometric inequalities which I have not done so far. So, I will briefly for 5 minutes I will digress into 3 well known inequalities I will just mention those inequalities I will not have class time to prove them, but I will I will probably refer you to I mean I will probably upload some material on the proofs. So, let me put these inequalities down there is 3 of them one is called Holder's inequality one is called Minkovsky's inequality and then Lyapunov inequality let me pull this up. So, this is a digression. So, this is not about convergence. So, I want to mention Holder's inequality Holder over with an umlot Holder's inequality this says if p and q is greater than 1 and 1 over p plus 1 over q equal to 1 then expectation of absolute x y less than or equal to expectation of. So, expectation of x to the p whole to the 1 by p times expectation of absolute y to the q whole raise to 1 over q. So, this is Holder's inequality. So, this generalizes Cauchy Schwartz inequality right. So, Cauchy Schwartz Cauchy Schwartz is for p equal to q equal to 2 right. So, this generalizes that.  So, I will point you to some reference on this proof. So, that is Holder's inequality then there is something called Minkovsky's inequality. See all these inequalities are highly geometric in nature I will as I will explain shortly right. In fact, this is a generalization of Cauchy Schwartz right. So, it is geometric means Minkovsky rather says if p is greater than or equal to 1 then expected x plus y to the p raise to 1 over p is less than or equal to expected value of x to the p to the 1 over p plus expected value of y to the q y to the p whole to 1 over p. Finally, Lyapunov inequality says that if r is greater than s is greater than or equal to 1 then expectation of x to the s whole to the 1 over s is less than or equal to expectation of absolute value of x to the r whole to the 1 over r does that make sense or is that the way. So, I mean that should imply this result. So, I think this is correct right yeah I think this is correct. So, a brief note. So, this Minkovsky inequality if you look at it it tells you. So, again see for. So, this basically tells you that if you take the p th moment or p th moment and raise to the 1 over p that satisfies triangle inequality right that is essentially what is saying correct. So, this Minkovsky inequality essentially asserts that this object expectation of x to the p whole to the 1 over p right. So, this is this acts like a norm it can actually show be shown using Minkovsky inequality that this object acts like a norm in the space of L p random variables now random variables for which the p th moment is finite 0 mean random variables for which the p th moment is finite. So, we know that see we mentioned earlier that the standard deviation behaves like a norm right and we mention that expectation of x y behaves like an inner product right in the space of L 2 random variables. This actually is more generally true that the L p the space of random variables with finite p th moment this behaves like a norm and it satisfies. So, Minkovsky says it satisfies the triangle inequality and this guy this hold us inequality which is also true in Euclidean space right you hold us inequality you may you can easily prove hold us inequality in Euclidean space for vectors in R n. It shows that this is like a generalization of Cauchy Schwartz in some sense and it gives you a relationship between these 2 dual norms this p th norm and q th norm or dual norms if this is satisfied and. So, it is exactly analogous inequality works in Euclidean space. So, again so this is like this is now you are saying that in the space of L p random variables or random variables which have both p th and q th moment finite the dual norm satisfy this right. So, these things are exactly analogous to Euclidean space. So, that was just a digression. So, you may encounter these inequalities they are useful to know and this in particular gives a proves that this is a norm in L p the space L p. So, that completes. So, that completes what I had to say actually here this completes what I had to say about generally about convergence of random variables. So, what remains then is just the limit theorems 2 or 3 major limit theorems and then we will be done. So, in particular we will do weak law of large numbers strong law of large numbers and the central limit theorem these 3 are very fundamental results. So, we will do laws of large numbers and central limit theorem. So, here we will do weak law and strong law. So, again so this both laws of large numbers see laws of large numbers I have said in plural because it is not one theorem. So, it is like a family of theorems. In fact, similarly I should say central limit theorems because central limit it is not one theorem it is refers to a family of theorems. We will only do some very specific version of it for the of these theorems for the IID case. But these 2 families of theorems really are at the core of probability theory they are very very important theorems and in fact, one there is no exaggeration to say that the laws of large numbers really the backbone of probability theory. So, if you have to choose a theorem or a family of theorems that make probability worth it it is the law of law of large numbers. That is because the laws of large numbers essentially they give you an interpretation of the expected value expectation of x as an average as an average value. So, far nothing we have said about expectation of x which is we just defined as integral x d p it is just a number right at the back of your mind you make I have this notion that it is some average value or something. But we have not said anything about it I kept saying that so far it is just a number for you it is the law of large numbers which gives the expected value of a random variable the operational meaning or a practical meaning in as an average. So, if the law of large numbers were not to nobody would study probability theory right because this whole frequentist interpretation of probability that oh if you toss a coin a million times fraction p will be heads or whatever right. So, that is essentially because of the laws of large numbers. So, it is the law of large numbers are in fact therefore, the backbone of probability theory without it nobody would study a theory like that and the theory would be entirely useless right. And central limit theorems in some sense they establish the importance of the Gaussian. So, the central limit theorem basically says all this family of central limit theorems they say that in the space of finite variance random variables the Gaussian is the is like an attractor. So, what it says is that if you add a large number of finite variance random variables no matter what their distribution the sum will look roughly like a Gaussian in distribution. So, in some sense the C L T establishes the Gaussian as in some sense the king of this of the as the most preeminent distribution in the finite variance world. So, that is the high level picture of things I have not I mean that I just poke it out right. So, I will now put down the results more properly any questions at very high level. So, any questions all right. So, let me let us first deal with the weak law of large numbers let x 1 x 2 dot dot dot b independent identically distributed random variables with expected value expectation of x which is finite. So, we are saying that the expected value exists the I D random variables for which the expected value exists and it is finite then. So, let S n is equal to then S n over n converges to expectation of x in probability. So, this. So, you have I D random variables with finite expected value expectation of x and you are looking at the sample average. So, you are looking at sum over i equals 1 through n x i over n. So, you are you have this I D realizations of this random variable and you are taking the sample average right you are adding the first n and dividing by n you are just taking the statistical average of sample average of the random variables x i's right. And the law of the weak law of large numbers says that this sample average converges in probability to expectation of x in probability. And it is in this sense that the law of large numbers says the sample average converges to the statistical average that is why this expectation of x has the interpretation as the statistical average value of the random variable. So, this weak law of large numbers is fairly old. In fact, the first published proof of it goes back to Jacob Bernoulli and it was published posthumously after he died in the year 1713. So, it is almost exactly 300 years old. So, it is a old result it is not a modern result it is not. So, most of what we have done is modern probability theory rate all this measures and so on. So, this is this pre rates all this by quite a bit. So, in. So, if you want a more explicit statement. So, it says that limit intending to infinity probability that S n over n minus expected x greater than epsilon equal to 0 for all epsilon greater than 0 right. So, as n becomes large the probability of the sample average being different from the expected value goes to 0 then becomes large. So, this means that with high enough with fairly with probability very close to 1 if you just look at S n over n it takes value close to expectation of x and this you can choose any epsilon you want 10 power minus 6 and you will find a large enough n for which this probability goes to 0. For large enough n this probability will be very close to 0 and n tends to infinity will be 0. So, this is the weak law of large numbers now maybe I should just take the strong law also because before proving both the strong law on the other hand is a modern result. The strong law of large numbers says under exactly those see under these conditions this convergence is almost sure there is only difference between weak law and strong law. The only difference is here instead of I P you will write A S under no further assumptions. So, strong law subsumes the weak law because almost your convergence in place convergence in probability. So, one might ask why do we even bother about weak law. So, it is for historical reasons I mean people figure that out 300 years ago whereas, it took all these measure theoretic machinery. So, and Borel proved a special case of it in 1909 or something then Colmogorov proved the general strong law. So, this is strong law of large numbers as we know it today is only about 100 years old whereas, this is about 300 years old. So, for 200 years people did not know that a stronger result is possible and that is because they did understand this measure theoretic tools properly. That came up only in the early 1900s strong law of large numbers. If x i are same story x i greater than or equal to 1 or i i d random variables with finite mean. So, expectation of x exist and it is finite then S n over n converges to expectation of x almost surely or with probability 1 i e. So, it is just a minute x n over n converges to x. So, this is so you are saying that this is a sequence of random variables which converges to. So, you should look at this not as a constant it is a random variable which always takes the value expectation of x. This is obviously, you have a sequence of random variables converging to another random variable. But that random variable is a constant here that is the correct way to interpret it. But this convergence is almost sure. So, in order to write. So, if you want to write it a little bit better i e the probability of omega for which S n of omega over n converges to expectation of x is equal to 1. So, this is a very different statement from this we in fact know that this is a stronger statement. So, if you look at this this is a statement about the sample parts the sample the samples omega. And this is not a statement about I mean this is the statement saying that S n over n is close to expectation of x for large n that is all this is saying. But this is saying that the sequence S n of n as a function of omega converges to expectation of x for almost all values of omega. So, the probability 1 essentially. So, remember so I will help you interpret this statement a little bit it is very important to understand this statement. So, you remember that all this x i is a living in some probability space omega f p. So, all these guys are living in some omega f p. And the moment nature picks a little omega all this random variables x i of omega realize as real numbers. And then obviously S n of omega over n also realizes as a sequence of real numbers. Now, the sequence of real numbers S n of omega over n may or may not converge first of all it is just some sequence of real numbers for every omega. So, change omega sequence will take some other value. So, what this theorem is saying the stronger of large numbers saying is you can imagine let us say if you like you will have 3 buckets. So, you pick an omega and you check if this sequence converges to expectation of x. So, if the sequence does not converge at all put that omega in the first bucket. If it converges but converges to some value other than expectation of x it could go to any other value put it in the second bucket. If it converges to expectation of x put it in the third bucket you see what I mean you are just partitioning the sample space right effectively. So, in some sense what you are saying is. So, let that those omegas the sequence does not converge let us say. And for those omegas the sequence converges but not the expectation of x. And for these omegas the sequence converges the sequence converges to expectation of x. What the strong law of large numbers is saying is that these 2 have probability 0 and all the probability is here. So, the moment omega realizes with probability 1 you will get a sequence whose average value converges to expectation of x. And the probability of either the sequence not converging at all the average not converging at all or converging to some value other than expectation of x is 0. So, that is the statement of the that is what this means that is very different from this you see. And we in fact know an equivalent characterization of almost here convergence which is also worth stating here. What is it we did a theorem about equivalence of almost here convergence to the excursions never happening beyond a certain m right. That is what so that also it is equivalent to saying this right equivalently you have to help me out here I think. Probability of union right n greater than or equal to m omega for which S n over n minus expectation of x greater than epsilon that right or the another way of writing it is limit m tending to infinity probability that soup n greater than or equal to m S n over n minus. So, or right I mean this union is same as this you can write a soup here the same thing this is all true for all epsilon greater than 0 right. So, this statement is equivalent to this statement right because we proved it right just the equivalence of almost here convergence to this. So, again to emphasize this says I mean they both exactly the same right we write a super right union is the same S n of omega. So, this says that as if you if you fix an m. So, if you fix a large m probability of an epsilon excursion. So, if you look at the difference between the sample average and expectation of x the difference exceeding epsilon is like an epsilon excursion at n. So, the probability of having even 1 epsilon excursion after m m and beyond goes to 0 right. Whereas, this convergence probability says the probability of an epsilon excursion at n goes to 0 right. This is saying probability of an excursion m and beyond goes to 0. So, this is stronger right we have seen this already. So, are there any questions on these 2 this did you understand the difference between these 2. So, if you strong law if you strong law implies the weak law right. So, in some sense weak law is completely subsumed. So, if you prove the strong law you prove the weak law, but on the other hand proving the weak laws much easier which is why it was done 300 years ago. And this is much harder this is why it was done 100 years ago because this is a measure theoretic statement right. You are looking at a measure of all omegas where this convergence happens. So, I think I will stop here yeah I think I will stop here good place to stop. So, next class we will have to prove these results and then I will have 1 class for central limit here. So, I think that is just about right.


What do you say? What do you say? What do you say? Making requests in English. What do you say when you want someone else to do something for you? Well, it depends on the situation. There are lots of ways to make requests in English. Let's see how well you can handle these scenarios. Here are some situations for practicing English phrases for conversation. Requesting Situation 1 You are carrying some boxes and need someone to open the door for you. What do you say? A. Could you help me to open the door? B. Would you mind to open the door? C. Could you open the door, please? D. Why don't you open the door? What do you say? Think about it. Situation 1. Analysis For each of these situations, we will highlight the best answer and give a natural response to it. We will also say what is wrong with the other answers. The best answer is C. Could you open the door, please? Sure, I'd be glad to. What's wrong with the other answers? A. Could you help me to open the door? That's too wordy. Also, the word help doesn't work here. Help usually means you're doing something with someone. Here you want someone to do something for you. B. Would you mind to open the door? The grammar is incorrect. Would you mind opening the door? D. Why don't you open the door? It sounds kind of rude, like what's wrong with you. Situation 2 You are working on a project and need to use the scissors, which are across the table near your co-worker. What do you say? A. Please hand me the scissors. B. I want the scissors now. C. I might need the scissors. D. You should give me the scissors. Analysis The best answer is A. Please hand me the scissors. OK, here they are. What's wrong with the others? I want the scissors now. This is impolite. It sounds very demanding. I might need the scissors. Huh? You need to be more assertive. Tell what you want. More directly. D. You should give me the scissors. This sounds rude. Don't tell me what to do. Ready for the next one? Situation 3 You need a ride to the grocery store. Your friend is heading that way. What do you say? A. Could you taking me to the grocery store? B. Would you ride me to the grocery store? C.  D. Could you possibly take me to the grocery store? Analysis The best answer is D. Could you possibly take me to the grocery store? Sure. I'd be happy to. What's wrong with the others? Could you taking me to the grocery store? The grammar is incorrect. Should be could you take me? B. Would you ride me to the grocery store? This is wrong usage of the word ride. It doesn't work here. You'd have to say could you give me a ride to the grocery store? C.  The expression is incorrect here. It should be give me a lift. Question 4. You're almost freezing in your office. Someone is near the thermostat. What do you say? A. Could you close the air conditioner? B. Can you turn down the air conditioner? C. Will you stop at the air conditioner? D. Will you reduce the air conditioner? The best answer is B. Can you turn down the air conditioner? Of course. It's too cold in here. What's wrong with the others? Can you close the air conditioner? This is the wrong word. It's a machine. You don't close machines. You turn them on or turn them off. Turn them up or turn them down. C. Will you stop at the air conditioner? This has an extra word and it's extra wordy and it sounds kind of rude. Stop it. D. Will you reduce the air conditioner? Word choice. The word reduce is strange here. It sounds a little bit too formal and for machines we don't reduce them. We usually turn them on or off or up or down. Situation 5. You need to ask a favor of a close friend. What do you say? A. Could you favor for me? B. Could you do me a favor? C. Could I do you a favor? D. Could I ask of you a favor? A. Analysis. The best answer is B. Could you do me a favor? Sure. What is it? What's wrong with the others? Could you favor for me? This is very strange. It's missing a verb. Favor is not a verb in this case. Could I do you a favor? You want to help them or you want them to help you? Could I ask of you a favor? There's a problem with word order. Could I ask a favor of you? There's also a problem with formality here. Could I ask a favor of you is too formal for a situation with your close friend? Situation 6. Someone tried to throw a wad of paper into the trash can and missed. What do you say? A. Please, would you pick that up? B. Will you properly throw that away? C. Would you mind for me? Would you mind putting that in the trash? D. Put it in the waste paper basket, okay? The best answer is C. Would you mind putting that in the trash? Oops, I might have missed. Or I must have missed. What's wrong with the others? Please, would you pick that up? And do what with it? You need to be more specific. B. Will you properly throw that away? That sounds snobbish, like you're better than me when you use those kind of words in this situation. D. Put it in the waste paper basket, okay? Sounds a little rude. It's kind of like you're accusing me of doing something when it was probably just an accident. I didn't do it on purpose. Situation 7. Someone is blocking your view of the screen in the conference room. What do you say? A. Would you be so kind as to move over a little? B. Would you mind moving your body? C. You're blocking my view. Please move. D. I hate to tell you, but you need to move. Analysis. The best answer is A. Would you be so kind as to move over a little? No problem. Can you see better now? What's wrong with the other answers? Would you mind moving your body? Sounds strange. What do you want me to do? Dance? C. You're blocking my view. Please move. That's direct, but very rude. D. I hate to tell you, but you need to move. Too strong for this situation. Situation 8. You need the receptionist to give Mr. Paxson an important document. What do you say? Will you give to Mr. Paxson this paper? B. Give this document to Mr. Paxson now. C. I'm sorry. Mr. Paxson needs this today. D. Will you see that Mr. Paxson gets this? The best answer is D. Will you see that Mr. Paxson gets this? Sure. I'll give it to him right away. What's wrong with the others? A. Will you give to Mr. Paxson this paper? Something wrong with the grammar. We have an indirect object here. Will you give this paper to Mr. Paxson? Or will you give Mr. Paxson this paper? B. Give this document to Mr. Paxson now. It sounds very demanding. Be more polite. Even to receptionist and secretaries. You need to be polite to everyone. I'm sorry. Mr. Paxson needs this today. Don't apologize. You can be direct and ask them to do something. Request that they do something. It's their job to help you. Requesting. A review. There are several ways to make requests in English. Usually, longer is more formal and polite. Look at these examples. Open the door. Please open the door. The word please makes it more polite. Can you open the door? Will you open the door? What's the difference between can and will? Well, the formality is almost the same. Can means like, is it possible for you to do this? Will means like, are you willing to do this? The next ones would and could are more polite than can and will. Would you open the door? Could you possibly open the door? When you insert the word possibly, you're making it longer and a longer statement is usually more polite. Would you mind opening the door? Notice the grammar here. After would you mind, you have to have the ing form of the verb. Would you be so kind as to open the door? This is the longest one and it's the most polite. Always remember to consider the situation. For example, if there is a fire in the building, you probably would not say the last one. Would you be so kind as to open the door? You'd probably say, open the door! Because of the situation, you don't have to be as polite. If there's a fire or something like that. Your turn. Practice using English phrases in these situations. Talk to a partner, a friend, or your teacher. What do you say? You need a lift to the airport. What do you say? You want some help with your assignment. What do you say? You need someone to fix a problem with your computer. What do you say?  What do you say? You need some help carrying a huge pot of plant. What do you say? Think of your own situations. Role play with a partner. You can use the situations here or think of your own. Talk. It's your turn. Go ahead. Talk. Practice requesting, asking for help, and giving responses. Feel free to pause the video and take as much time as you need. Hope you enjoyed that. If you liked this video, please give it a thumbs up below. And remember to subscribe to our channel. This video was brought to you by the following English learning websites. Have an idea for our next video? Please share your ideas with us at the link below.