Everybody forced here. Rip in twenty-twenty-three Pomeran University football breakers to light. Six box number four. Pick your letter style. First name, first letter. Alvin with J. Bruce has L and P. Danny with D. David has F and Q. Don has C. Jeffrey S with B. Jeffrey H has M, S, T and E. Larry with W. Matthew has A and H. Nate with R. N and X. Pascal with G and O. Richard has K. Good luck everybody. Let's get to it. We do have pick your team listed for I think Wednesday nights on here. We've been doing PYTs over on Fanatics Live and they are a blast. They are a blast. You can grab like Southern Cal, Oregon, you know, LSU. There's an all other spot that just has a ton of different like you know schools that only have like one or one or two guys in it. Vyrofractors of Victor Rosa. Jaden Bray, Drew Pine, Matthew Golden and Austin Jones. Nice orange shock here going to Jay as Jackson Dart. Dart in your neck. Twenty-five. You dart in Sean's neck in a minute here. Purple to three ninety-nine is Caleb Johnson for K. Three ninety-nine Roman Hemby as well and a yellow Keon Kelly. There you go K to seventy-five. Mike D. How you doing buddy? Mike D in a place to be. First auto is Carson Beck for C and a Kyle McCord. There we go K. Nice Kyle McCord. Kyle? Kyle McCord. And a Jackson Arnold. Do it now. Who is your daddy? What does he do? Sarah Connor one's always pretty good. Sarah Connor. Hey Travis Hunter Refractor. Bo Collins, Dylan Gabriel, Dylan Dalin Hayden and Keon Kelly. Orange shock, color match to twenty-five Nate Wiggins. Purple out of three ninety-nine Jacob Cowang. Two ninety-nine, Bo Nix on the Aqua. Aqua again, Shaz Preston out of two ninety-nine. With a refractor first woman autograph of Jaden Dolara to four ninety-nine plus a base auto of Javon Bullard and a Jordan Travis. Early Risers. Come on Rangers. Going back out for a seventh. Let's go Monty. Let's go Monty. Our refractors of Marshawn Lloyd. Taylor Green. Justice Haynes. Casey Thompson. Will Johnson. A shock of Michael Panicks Jr. Aqua, Oscar Delp to two ninety-nine. Purple Mini Diamond. Tavia and Robinson to three ninety-nine. Big Kahuna. Cade Clubnick on the SP. Cade Clubnick. Refractor auto again to four ninety-nine. Jaden Dolora for J. Early Risers. Shudder Sanders Auto. There he is. Sixty-six of ninety-nine. Boom, boom, boom, boom, boom. I need a nice watch. I don't have any nice watches. Congrats to S. Awesome hit there. That's going in a mag of course and a Drake May Early Risers. Nobody warm up in the pen, eh? Man, they're just letting Montgomery go out there. Although it is the bottom of the lineup so you may as well let them get you through the seventh. Dude, yes, exactly, Shady. Yes, yes, yes. Let's go Giants. Refractors, Kyle McCord. Solomon to Shields. Although I have a feel on second half, Michael. A little differently.  They could easily turn around. Montreal. Yeah, that could be a first drive. I get to flip. Montreal, Johnson, Dalen Everett and Parashtones. It'll likely go that way but, you know, Donovan Jackson, Orange Shock to 25. There we go. Aqua Will Johnson out of 2.99. Exactly, Paul. None of us ever root for the Giants so hard. It's kind of crazy. Purple Mini Diamond, LT Overton. Although, to be fair, I'm always rooting for the worst team to win, like the underdogs. I'm always doing that to be fair, so. There's two door teams this time, so, you know. Purple Mini Diamond, Overton. LT Overton. Joe Alt to 3.99 as well. First base auto, Dalen Hayden. And refractor, first auto, Michael Pratt. Michael Pratt, number to 4.99, and a Marvin Harrison. Junior Early Risers. I mean, hey, you Dolphins and you Dolphins fan need it. You need the bills to take an L. All right, refractors of Alton McCaskill, Dante Moore, Bonix, Devin Leary, JVon Cohen, and a shock of Malachi Starks. How about True Orange Marvin Harrison Junior? First bowman, 1 of 25. The Orange OSU receivers have been hitting tonight. Had like two Orange Shock Agbukas at one and one of the breaks.  That is going into a mag 1 of 25 as well for M. Green refractor out of 99, Jarquez Hunter. I like that name, Jarquez. Jarquez or Jarquez. So to 1.99, Nate Wiggins. Green first auto, Evan Stewart out of 99. Stewart. And Richard Reese on the 1955 bowman autograph, number to 99. Very nice hit for R. And Caleb Williams, Early Risers. So glad that the Raiders beat the Pats. Who also is a terrible team that won today. Now, they already had a couple wins though, but it is good that they that they got some more. Cam Camper, Ty Simpson, Tyler Neubin, Blake Corum and Malika Neighbors. Oh, no, no way, Eddie. The Raiders are definitely a better team. It doesn't matter how incompetent your coach is. If you have guys like Devonte Adams and like Josh Jacobs and you have actual talent, you'll be better than the other worst team. We don't have talent. There's no talent. Our defensive talent got hurt. Orange Shock, Tray Sean Ward to 25. Oh yeah, the Ravens lost. Orange, Ramblin Man, Blake Corum for B. Wow, is Dwayne Almond playing guitar in this room? That's exactly what it sounded like. Wait, Dwayne Almond passed away? I don't know. I forget which one. Blake Corum on the Orange 25 to 150, Jaden Bray to 299, Troy Franklin. Hey, it's Franklin. Green KJ Jefferson Otto. There we go. It's a 99. Oh, Ravens did win. Yeah, I have no idea. And Refractor Otto Brock Bowers to 499. Yeah, they play the Titans. Does that even count? Early risers, bow, nicks. All right, let's go ahead and recap. This stuff is fun, man. Value in this product. Let's go, Monty. Monty. Titans might be. Yeah, I needed the Titans to get a win today. I don't hate the Ravens, but I needed the Titans to get some dubs. But direct competition for number one pick was the Raiders as well. They got a win. We did Panther start winning. They got to pull something off. Patsy, that number one, baby. Let's get that number one pick. All right, we got numbered cards of Troy Franklin, Jaden Bray, Nate Wiggins, Jarquez Hunter, Will Johnson, Oscar Delp, Shaz Preston, bow, nicks, Jacob Cowing, Caleb Johnson, L.T. Overton, Joe Alt, Tavion Robinson, Roman Hemby, Keon Keely, to 25, Jackson Dart, Nate Wiggins, Donovan Jackson, Traysean Ward, Blake Corum, a lot of orange. Great color. Autos, to 499, Brock Bowers, to 99, KJ Jefferson, to 99, Richard Reese, to 99, Evan Stewart, to 499, Michael Pratt, base, Dallin Hayden, to 499, Jaden Dolorat, twice, base, Jevon Bullard, and Carson Beck, and a base, Kyle McCord. Solid names in there too. Ed True Orange, first bowman, Marvin Harrison, Jr., for M. What a card. And then, early risers, Auto, to 99, Shudder Sanders. That's awesome. Thanks again, everybody, moving on now to some gold standard.


Hi friends, welcome back to my channel and a very special welcome if you're new here. My name is Jen. I'm a certified weight loss and nutrition coach and it is a Friday, so it is weigh-in day. Let's talk about my week, my weigh-in and the Weight Watchers Workshop topic.  Make sure you're subscribed. Your bell notification is turned on because we do a weigh-in every Friday and I actually upload five videos every single week. Check out the description box down below where you will find nutrition coaching highly, highly, highly recommend, personalized macros and calories. This is how I've lost and maintained a 140 pound weight loss as well as one-on-one coaching for accountability, support, or to ask questions. Links to discounts to my favorite things are also down in that description box as well as my Facebook group. Come join us there. We'd love to have you. So let's go ahead and jump into this week's weigh-in, how my week was and the Weight Watchers Workshop topic. Before we get started, I wanted to let you know that my beautiful, wonderful friend, Michelle, my Australian bestie has officially moved to the United States. She won the green card lottery several months ago and has just in the last few weeks relocated from Sydney, Australia to Atlanta, Georgia. And back in November, she was here visiting and left a suitcase in our home so that she wouldn't have less to bring over from Australia when she moved to the US. So she is actually coming in just a couple of days on Sunday for almost a week to hang out with me and of course to pick up her suitcase. So with that being said, there will not be a weigh-in video next Friday because she will be here and we will be living our best life. We are spending some time in Phoenix. Definitely make sure you're in my Facebook group. You follow me on Instagram. I'll post lots of pictures and updates there for you guys, but just a reminder that there will not be a weigh-in next Friday, but all of the rest of my regular content will be up next week. So now let's talk about my week. You guys, I had such a good week. I had a really, really busy week. I've been doing a lot of pre-filming, pre-editing, just gearing up for Michelle to be here. I wanted to make sure that I cleared my schedule, of course, to spend as much time with her as possible. So this week, not only did I work a lot, but I also went to boot camp. I did miss Monday because it is officially monsoon season here. In fact, it's rained almost every day this last week, which we need the rain. I'm not complaining, but we were rained out on Monday. So I actually went to the gym, did the elliptical, lifted weights, still got in a really good workout and then I was able to go to boot camp the rest of the week, go to the gym. I also played pickleball. I have just been very active and that really has helped me decompress with all the working that I've been doing to get caught up and ready for Michelle's arrival and to make sure that I still can put out all of my regular content for you guys. Really, truly working out and exercising helps me decompress, not to mention just makes me feel better overall. I've been really working on cleaning up my diet. I talked about that in what I eaten a day a couple of weeks ago. I'm really focusing more on whole real food, which to be honest with you has not only made me feel better, my gut health is better, my workouts are better, I just feel better overall. I'm less sluggish. I don't have as many sugary cravings. I don't have as many junk food cravings throughout the day. I'm not getting that afternoon crash. I mean, really, truly just choosing better foods about 80% of my diet has really helped me in so many ways. So I've been really focusing on that this week and making sure that I have good, whole, healthy foods on hand. I'm just feeling really good body, mind and soul which makes me super happy. I definitely want to share this week's Wayne with you but before we, before I do, let's talk about this week's Weight Watchers workshop topic and that is can't fall back asleep, try this 20 minute rule. I talk about sleep a lot.  I've said time and time again that I can fall asleep but I can't stay asleep. I wake up, my mind starts moving and then I feel like I need to get up and do things at one in the morning. So this workshop topic is really helpful if you have a hard time getting back to sleep or falling asleep when you first hit the sack. Try this, get out of bed. Go into another room or space that's dimly lit, quiet and comfortable. Set it up ahead of time so it's ready when needed. Number two, do something calming. Whatever you choose, keep the lights low and the electronics off. Listen to a sleep story podcast. Do a jigsaw puzzle. List three things you're grateful for. Focus on your breathing. Read a slow paced book or flip through a catalog. Then start to notice when you get sleepy. Are your eyelids heavy? Can you not concentrate anymore? It's time to go back to bed and repeat. If you haven't dozed off after another 20 minutes start over with step one. This might seem a little odd to get out of bed when you're trying to fall asleep but really truly these tactics work. I have done this several times. I've actually went out on the couch, laid there for a few minutes, in the dark, just eyes closed, just trying to decompress and relax and then once I actually go back to bed I can easily fall asleep. You can utilize these tips before you go to bed or if you wake up in the middle of the night and can't fall back asleep. Changing the scenery and really just focusing on something other than the fact that you can't fall asleep is really beneficial to actually help you get to sleep. Oh and side note, don't sit there and watch the clock for the 20 minute mark to pass. You may get up a few times especially in the beginning you may need only 10 minutes or you may need 25 minutes. So don't focus on the clock. Focus more on how you feel and if your body is finally ready to go to sleep. Seven to nine hours of sleep is recommended every night. This lowers your risk of a lot of health related diseases. It also lowers your risk of weight gain due to choosing unhealthy foods the next day because remember when we are tired our body wants energy and our body knows that energy comes quickly from sugary foods and processed carbohydrates. So that's what our body's going to crave if we are lacking sleep. Get on a sleep schedule and again, sheet for seven to nine hours every single night. I also do want to share as always three fast facts from Weight Watchers with you. Number one, the majority of adults report a sleep problem every night or almost every night. Number two, healthy sleep makes it easier to eat well, move regularly and have a more helpful mindset. And number three, planning ahead for what you'll do when you have trouble sleeping can help you fall back to sleep more quickly and easily. Fail to plan, plan to fail. This even matters with sleep. So I think these tips are great. Like I said, I've utilized a lot of these strategies in my own life. For me, I don't have a hard time falling asleep. It's the staying asleep that's an issue for me. And I know firsthand that these tips and tricks work. So if you're in the same boat as me, definitely take advantage of this week's Weight Watchers workshop topic. So now let's talk about my weigh-in. Like I said, I've really been whole food focused. I've been moving my body. I talked a few weeks ago about how my weight changes throughout my hormones changing, ovulation, starting my cycle. Right now I'm in the midst of ovulation. Now, typically for me, ovulation time means a spike on the scale. Not always, sometimes more prior to ovulation or at the end of ovulation, right before I become bilinist before I start my cycle. And right now I'm kind of in the middle of ovulation. This month I didn't notice that big weight spike. Now I do always have weight fluctuations. I weigh myself every day and my weight does this. That is very, very normal. It doesn't mean I'm gaining weight. It's simply a weight fluctuation. Last week I actually maintained my weight to the ounce and this week my weight is actually up 0.6. To me that is a maintenance. That's a weight fluctuation. I'm okay with that. Because I weigh myself every day, I see those fluctuations. And actually there were a few days this week that I was at my leanest, I've been in a long time and then my weight just kind of pops back up those few ounces. It could be multiple things. It could be water retention. For me it typically is hormonal or because I'm sore from working out. I've been way more active lately and that's going to lead to some weight fluctuation. So 0.6 to me, I'm considering that a maintenance. I'm happy with that. I am currently trying to maintain my weight as I continue to heal from my cosmetic surgery. See what my body does over the next few months. And with Michelle being here, I basically consider that kind of like a mini vacation and I don't track my food on vacation. So I won't be tracking while my friend Michelle is here. I'll be mindful, I'll be focusing on protein but I'm gonna enjoy my time with her and I'm going to enjoy all the fun foods that we're going to try out. For her, there's a lot of different foods in the US than Australia. So we're gonna wanna try those out when she's here visiting. So I'm looking forward to seeing what the next two weeks bring as far as weigh-in goes. Because as a reminder, there will not be a weigh-in next Friday. So the following Friday will actually be a two week weigh-in. Post little mini vacation and gearing up for another little trip that I have planned mid-September. So I'm happy with my .6 gain. I'm happy with what I consider to be a maintenance and now I wanna hear from you guys. How was your week? How was your weigh-in? What do you think about this taking this 20 minutes to really get into a healthy sleep pattern? Let me know everything down below. And of course, if you enjoyed today's video, give it a big thumbs up, subscribe, turn your bell on so you never miss a future video. Don't forget to check out the description box for nutrition coaching, links and discounts to my favorite healthy things. Come join my Facebook group, follow me on Instagram. I'll be posting lots of pictures when my friend Michelle is here. And I will see you guys in tomorrow's massive stocked up grocery haul.


Some wangs. It's still pink. Perfect. Just the way I like my chicken with a bit of salmonella. And that's how you do it guys.


This neighborhood sure has changed. I know. A few years ago, not many people lived here. But the population is growing so fast these days. Remember how we used to rent videotapes at that little video store? Yeah. Now it's a multiplex cinema. And I hear they're tearing down our high school. They're going to build a shopping mall. Soon there will be just malls and parking lots. That's because everyone has a car. Fifty years ago, people walked everywhere. Nowadays, they drive. That's progress, I guess. Well, what about that old bookstore? Do you know if it's still there? No, it's not. Now it's a hair salon. Really? What about the Thai restaurant next to it? I love that place. Oh, that's still there. Let's go there this weekend. I'll drive. I can pick you up. Great.


But if you're a long buy straighter, these stocks are going straight up and that is your opportunity to go long. We mentioned that, you know, zombie times are approaching, these stocks may bounce in, you know, now these meme stocks are back in play for, you know, a couple of days, a couple of weeks, a couple of months. Who knows what's going to happen, right? In all honesty, I have no idea what these stocks are going to do. You know, I'm walking away with, you know, break even day today still depends on what these stocks do. But the main thing that I need to focus on in this market cycle is avoiding the hot stock. So all these meme stocks are going crazy again.


Thank you very much. Good morning, ladies and gentlemen, distinguished guests. It's wonderful to be here this morning. Could I begin to be acknowledging we're gathered on the lands of the noneable people and to pay my respects to elders past and present. This morning I'm very pleased to be able to launch the ACT's Community Sector Development Program. The program has five integrated modules, sustainability and strategic risk, governance and financial management, collaboration and strategic alliances, working with government and tendering and procurement. And as we've heard, this period of tremendous change, this development program is not the only ACT government initiative that's going to impact on the community sector in the territory. Many have already participated in the design work for the Human Services Blueprint. The government has also commenced a series of major reforms to community sector procurement, to contracting and to reporting. Today's seminar on sector sustainability and strategic risk is the first of a series of events on this topic over the next 18 months. So from the ACT government's point of view, a sustainable sector is one that has the genuine capacity to play a part in delivering positive social impacts. Sustainability is organisationally neutral, though. In simple terms, our community needs just enough capable organisations, not too many, not too few. And they won't be the same organisations over this extended journey. At the level of individual community sector organisations, sustainability means that over the next 10, 20 years and beyond, a specific organisation has to have the ongoing capacity to play its part in delivering a positive social impact. Sustainable organisations within the sector will have a skills-based board, good governance, an appropriate business model, financial strength, a strong and skilled management team and skilled and well-led workers. And the government is more interested in these high-level characteristics and in delivering outcomes than we are on the black ladder of reporting. This has got to be a step forward in the relationship between government and the community sector, one that's based on trust and on collaboration, and I look forward to it continuing. We know that there are considerable challenges ahead in the sector for the government and for our community as a whole. The Australian Federation, particularly in the context of our federal financial relations, is rapidly approaching breaking point. Some of you may have heard Ken Henry, the former Secretary of the Commonwealth Treasury, recently talking about the unsustainability of the tax bases of states and territories. Dr Henry spoke of the great difficulties that governments face in funding new, large social programs from budget cuts alone. And as Treasurer of the ACT, I can tell you I'm in a pretty good position to know that his comments apply just as much here in Canberra as they do to any other part of the country. And that's why the ACT government has embarked upon tax reform, a hard but necessary task to ensure our city's long-term economic sustainability. And there will come a time in the not too distant future when the territory simply runs out of land and other assets to sell to finance our city's needs. And if we've not reformed our tax system by this time, then the city will be in serious financial trouble. And what this means specifically for the community sector is that in the short and medium term, sustainability is not going to be achieved off the back of rising contributions from the territory government. In the long run, a more sustainable revenue base will allow for important and strategic investments in the territory's community services. But during the transition period, it will be very challenging. We all know that demand for services will rise thanks to the inevitability of demographics and the ups and downs of the economic cycle. The big risk is that we will collectively fail to achieve the social impact that we're striving for to build a strong and fair community and a strong and fair economy. There's also a big risk that individual organisations will succumb to the many pressures that they face. We don't want this to happen. Whilst a rational perspective might be so long as there is some in the sector able to pick up the slack, it doesn't really matter if the makeup of the sector changes over time. We don't necessarily want to bring that hard headed rational approach to sector reform. None of us want to see organisations failing. None of us want to see people's jobs threatened. None of us want to see clients forced to find alternative support. But to make sure that this happens as infrequently as possible in the coming period, there are some fundamental strategic risks to sustainability that every single organisation is going to have to address, including those in the community sector. Many of these risks do sit with the sector to address, but not all of them. The government will seek to find ways in which we can reduce or mitigate this impact. There are also some policy risks. From the ACT government's perspective, we're fairly well aligned, we think, with the community sector's policy priorities. We've worked closely over many years to develop a strong shared framework. Most recently, the collaboration on the Human Services Blueprint has demonstrated the strengths of this relationship. Another example, the NDIS, a significant policy reform strongly supported by the community, especially people with disabilities and their families. The policy shift, though, from block funding to a market-based model is very, very significant and could well be the first area of social reform to undergo such a shift. The tough part of this significant reform, the implementation phase, is starting to happen now. There are certainly risks associated with the rollout of the NDIS, but there are risks to engage with and risks to manage, not risks to avoid. But as you would all know, no major social reform is easy. No major social reform is risk-free. At a national policy level, we're still to get a better sense of how the new Australian government settles and how much difference there's going to end up being between how and what they wish to deliver for our community and how we wish to deliver community services in Canberra. Equally, the anticipated abolition of the ACNC is creating uncertainty. We had planned to shift our regulation of charities in the territory to the ACNC to reduce duplication and to make improvements to reporting. Sadly, I fear that opportunity is now lost. There are also financial risks at this point in time, largely posed by the Commonwealth Government. Here in Canberra, we face two risks, the broad risk to our economy and to our community from potential job cuts and a significant withdrawal of the Commonwealth Government from our economy. The specific risk also of budget funding for specific programs or national partnerships ceasing or significantly diminishing. This is a challenge that is unique to Canberra. Yes, all state and territory governments face the second risk, but only we face both. This risk may also be magnified right now because of the uncertainty. While we always have a firm eye to the Commonwealth budget, this year, ladies and gentlemen, I think the anticipation and the trepidation is high than it has been for many years. But the financial risks are more fundamental than just the Commonwealth budget, as Ken Henry and many others have noted. Government budgets across the world are under pressure. Australia actually has stood out in recent years. And in the ACT, we've stood out within Australia as having fundamentally strong economies. But the challenges remain. Traditionally, governments have supported community sector entities in doing the good things they do in the community. Sometimes just because they were doing good things in the community. But in these times of competing priorities for scarce resources, government owes it to taxpayers to fund for outcomes. And this is a national and an international trend. What we're doing here in the territory is to shift our service funding agreements from a focus on delivering outputs to one that focuses on delivering outcomes. And then, ladies and gentlemen, we come to one of my favourite categories of risk regulation. Now, let me tell you, the ability of parliaments and bureaucracies to generate useless time wasting regulation can be staggering. I probably don't need to convince anyone in the room of that. I think we are in competition at times, not always, but in times with some of the worst bureaucratic outcomes in the nation. Not necessarily in the world, but certainly in the nation. We've had our share of challenges and problems, and we need to work through those. But this government is seriously interested in reducing those burdens, not least for our own internal purposes, but also for yours. I recognise this as one of the more significant risks to your operations, and I'm actively looking at ways to reduce this. I see the government's role as being a catalyst and a resource aggregator. Something that can bring together different forms of assistance to community sector organisations. Virtually all of the modules of the sector development program operate on this principle, where we've aggregated the co-contribution that many of you make and turned it into what we expect to make a valuable contribution for your strategic benefit. And I hope today's session is just the beginning of this. So to summarise, the strategic risks to your sustainability are very real. I'm certain that in five years' time, this sector will look very different. Many of the risks we've talked about, particularly those arising from economic pressures from demographic, societal, technological and similar changes, cannot be avoided and have to be engaged with head-on. You will only be able to manage these risks if your organisation has a clear mission. Is financially strong, operationally nimble, efficient, has capable workers and is well-led. By implementing the Human Services Blueprint, by focusing on outcomes, by removing unnecessary regulation and administrative clutter and by providing targeted support through the sector development program, we're determined to play our role to help this sector continue to grow in strength and in capability. We look forward to partnering with you in the future. Before I close this morning, I'd like to take the opportunity to acknowledge the valuable assistance of the community sector reform advisory group. Many of you are in the room today. Thank you for giving your personal experience and your insights into what would be the most valuable reforms for the sector. Input also has come from consultants, sector leaders and people outside the sector. So it's no surprise that as a result, we now have a flexible and an innovative development program. But I'm confident it can be of great value to the sector to help now and into the future. Thank you very much. Thank you, Minister Barr. And the minister has kindly agreed to take questions for about 10 minutes if there are people from the floor who would like to take this opportunity to ask some questions and we have some roving mics as well. Have a question back here. Minister Simon Rosenberg from Northside Community Service. I guess the major theme today is community sector reform. If I can ask a somewhat cheeky question that is what about government sector reform? I think most of us in the room would be very much in favour of an increasing partnership arrangement and while we'll never be equals because you have the funding or the policy agency, we will hopefully contribute increasingly to policy development with you. There are issues of capability that I think are being recognised in government that need to be handled as well as in the sector. So can you tell us a bit about your thinking there? So well, Simon, the press club is the place for cheeky questions, isn't it? Excellent star. Look, yes, I acknowledge the need for further reform in the way the ACT government conducts the entirety of its operation. So a lot of what I've said in my speech this morning applies equally to how the government goes about delivering services either directly to the community or directly through stakeholders. We have a digital first policy now for the territory government. We will be needing to transition the bulk of our operations into that online space. In theory, with an upfront investment delivers considerable savings for the government in the way that we engage with stakeholders and that can be a straightforward or a simple example is that for every face-to-face transaction with the ACT government it costs us about $10. Every online transaction is about $0.10. The difference between those two is money that could be put to more useful purpose. You can't go, obviously, from removal of all the kind of instantly removal face service provision and not all areas of government lend themselves to that reform. But some areas do and in some areas we lag well behind either other governments or other organisations that deliver similar sorts of services. In terms of the organisational structure of the government since the Hawke review and the one government model there have been some improvements in cultural operations, if you like, within the government and some reduction in the siloing approach. And unfortunately the ministerial system and the budget system tend to reinforce. So the next iteration of ACT government reform that the Chief Minister will announce in due course, not being my place this morning to make that announcement, will see further development of that one government approach looking to ensure that in terms of the outward focus of ACT government that people don't have to shop around many different forums, don't have to have the conversations with health, justice, education and community services to break through on solutions to the wicked problems that we know we face. I've been driving that change through the budget process. It's nothing like the flow of money to generate cultural change within an organisation and part of that has been to provide a pool of funding for new initiatives within the territory budget that require cross agency collaboration, that require agencies to work together to deliver better outcomes. And you can see that in the corrective services area working more closely with community services and with education. In terms of for example how we approach the support systems for those who exit from our corrective services system. That's one example there are many more that we're seeking to pursue. Nothing happens quickly in government but it should happen more quickly in the ACT than elsewhere given the smaller size of our bureaucracy. And I think with the right incentives in place by way of a clear directive from the cabinet that we want that sort of agency collaboration and we want some of those silos removed that will help. There's still a fundamental challenge though in that there will still be ministers who have in a particular portfolio streams and there will still be directorates. As an old Churchill quote about democracy being the worst form of government except for all the rest. Westminster and the arrangements we have here are not ideal but there hasn't been a better model but we're working on improving the one that we have in the territory. So we have time for a couple more questions one at the back here. Hi Andrew Christina Ryan advocacy for inclusion. You mentioned being more virtual and doing a whole bunch more stuff online. I guess I'm aware that the ACT has got a very high rate of internet usage but for people with disabilities and particularly for people who are highly isolated it's less than 50%. So I'm really concerned about the access of our consumers our members to that world if we if we shift it without the government coming forward. A good example of that the treasury consultation documents for the budget process last year were only available in PDF. Completely useless to a huge number of people. So we need to be mindful in the context of that of how to make sure that everyone comes forward and particularly with the NDIS when people will become more engaged potentially more employed in the community sector we would hope is going to be acting as a major employer for a lot of people. So I guess I'd like to be aware that you've got some recognition of that that you're actually remembering it on an ongoing basis and in fact have plans in place for how government will ensure that accessibility is across the board and not an afterthought that we constantly have to remind you about which is kind of where we're sitting now. Sure yeah look though we've not done digital particularly well. No we haven't and it has to get better but it is inevitable. So there's certainly no point trying to hold back that tide everything that can possibly digitize will and in just some areas of the economy it's happening at a rate that is you know beyond what you would think is fathomable but it is happening but it is going to it is going to impact upon every area of our lives that it possibly can where anyone can possibly make a dollar out of it. That is a given the challenge for for government is that we are even in the ACT a slow beast when it comes to turning turning to this area but I recognize that the change is inevitable. The challenge of implementation is the is the big one and yes we will probably need constant reminding of those points because yes it is easy to get lost in the you know in the if you like the statistics of 92% home internet connection in the ACT the national broadband network the highest take-up in the nation is here in the ACT in the areas where it's provided. So we have a significant element of the community who are way ahead of government you know they're five years ahead of us and there's a significant part of the community that's five years behind and how you bring that part of the community forward. One thing that is good in this area I guess is that the economics of it are driving costs down and down and down that the technology is improving what you used to be able to get for a certain certain unit cost is now massively enhanced and as as this technology just you know rolls over the world it will get cheaper and cheaper and cheaper that's the good news in terms of its universal availability. The challenge for the government it's going to be what we do in the intervening period you know which could be another five years or so before this technology is just so ubiquitous that we're not having this conversation about about who's left behind. Some of the things very practical things we can do are to provide free Wi-Fi throughout the city that will will give people access to the internet for free and the capability to access the services that that can be delivered in that in that context. That won't be the complete answer but it's part of it in the short term but over time as the pace of change of technology continues I suspect our challenges are going to be keeping up with people rather than needing to to ensure that there aren't people left behind but we're there's a few years to go before we get to that point. And there was one more question in the in the middle here and then one down the back and then we'll wrap up. Thank you Stephen Fox National Disability Services. My question also relates to the NDIS minister. You talked about it in a sense perhaps being a forerunner in terms of moving towards a more market driven environment and I think that offers two challenges which I'd seek your views about. Firstly how the sector itself retains its community character its engagement out in the broader arrangements for supporting people in need and who are vulnerable and secondly I think that market driven side of things faces challenges for government and I'd be interested to know if the government has any further views about its role either as a service provider or indeed looking forward to the full rollout of the NDIS what the ACT's continued mission will be in the space concerned with disability. Okay well I'll go to the second question first to say that's the subject of some consideration within government in the very near future possibly even tomorrow so I won't I won't be preempting any cabinet decisions on that at this point. Suffice to say though that it is it is a significant issue that that we are considering and over what time frame and in terms of a transition if if indeed we are to make a significant transition from the way we've currently been doing business to the to the first question well look I think there will there will inevitably be as a result of this change people coming in to deliver services with a profit motive I think that's an inevitable outcome of the NDIS model and as to whether or time will tell us to whether the NDIS model is successful everyone loved it in theory the practical implications are going to be the challenge different government implementing it to that that proposed it different state governments with different approaches so it's a save and you know in the inside of six months it's a very different beast to what it was when Prime Minister Gillard passed the legislation and provided the funding in her last in her last budget so I suspect that it will continue to be an evolution there from the community sector's perspective doing the job well well will certainly assist and I have no doubt that across the sector locally and and nationally that that will occur but I think it's going to be universal way I don't think I could put my hand on my heart now and say that every community sector organisation is going to get this right and be outstandingly successful in in this new world I don't think that's true I think the majority will but I think there will also be some new entrants who might deliver some innovation and deliver services in a different way that we might not have thought about yet and technology again will play a significant role in that but it does remain to be seen we need to closely monitor it if this service to every model doesn't work then I wouldn't foresee it being rolled out in other areas of the community sector in the long run it might need some refinement along the way there'll be interesting questions particularly in smaller jurisdictions in regional areas whether there will be a sufficient base for the market to be able to provide services efficiently and effectively there could be market failure look that could happen in larger jurisdictions as well the design of this will be important and consumer expectations are going to be a challenge too I think there's no doubt and rightly so expectations are very high so there is there is also a risk that that we won't broadly as a as a sector meet those expectations that risk is very real too I think we had one more question down down the back here and then the minister will need to leave us to take some some press questions Good morning Tim Bavinton from sexual health and family planning ACT thank you for your overview minister a question in the spirit of the ones that have come around your thinking we hear a lot about a changed world for community service organizations over the next five to 10 year lot period of time could you give us some of your thinking on who should be picking winners and losers in that kind of environment and what sort of criteria should inform that that's a look it's a very good question it's it applies in so many areas of public policy I think I can best sum it up by saying the consumer is now king or queen depending on your outlook either way either way consumers are going to drive are going to drive a lot a lot of change in many areas I think there are probably some sectors some elements of the community sector where the consumer or the client is not particularly empowered and where really it's we take what's available or there's nothing else available and that will probably slow change in in some in some parts of the sector it's probably not going to be well there is I should say there is a power imbalance in some areas some people's voices are stronger than others some people have better advocates who can champion their cause for reform of service delivery or more resources going into a particular area and that applies within the sector and across the broader realm of public policy take a long run view of these things unless we reform our revenue bases then everyone no matter where you sit in society which sector in a which set of interests your lobbying or representing if there are a few more scarce resources overall then I don't think anyone is going to is going to end up being in a better position in five or ten years time I am deadly serious when I say the federation in terms of its financial relations is approaching breaking point you know we we simply cannot fund the sort you know a labor if you like a labor social agenda of a liberal tax base you can't abolish carbon taxes mining taxes cut company tax cut personal tax and think that you can continue to run the sorts of social programs that this country does just cannot be done you can't fund it off budget cuts in other areas not unless you are going to savage health and education which consume you know more than half of state and territory budgets and are growing at a rapid rate and you know the observation I made about demographics is very clear as society ages we are consuming more and more of our available resources into the health field now it's everyone's number one priority everyone wants more money spent on health every opinion poll everywhere in the nation in every jurisdiction what's our community's number one priority is health followed by education so it's perhaps no surprise then that those two areas consume the bulk of our resources but it can't continue as it is forever something has to give I think it's it's a bit of an indictment on the Australian political system that the smallest jurisdiction in the country is the only one engaging in any meaningful tax reform to try and do something to ensure that we have the resources to deliver the services we know our community will need but most of you would have been in Canberra in 2012 and would have seen the campaign that was run how are your rates have they all tripled in the in the last 12 months but you know seriously there's no magic pudding if we want to deliver the services that I think people in this room agree the community needs it's got to be paid for and it can't be paid for just out of cuts in other areas of government expenditure I hope that answers the question so minister thank you for what's been a very candid assessment of a number of the risks and challenges faced by the sector both immediate and longer term and the structural things that are driving that locally as well as broader I think global trends that are challenging our binary notions of public and private but also I think in what I heard daring us to imagine a community sector that can be both focused on accountability for results engaging with those risks but perhaps going less where the money is and more driven by outcomes and able to set their strategies to do what they do best to deliver on that will you join me in thanking the minister


Hi there everyone calls me Professor Jay. I am from the Department of Biostatistics and Bioinformatics at the Milken Institute School of Public Health at the George Washington University. Now this is a short video tutorial on exploratory data analysis which means summary statistics and data visualization using the chat GPT large language model. Now this video tutorial is specifically for our postgraduate students in the school especially those that are planning to or have taken my postgraduate class in introduction to biostatistics but this tutorial is open to all of our students at the school and at GWU. And as always I extend an invitation to anyone interested in the Korean public health. If you want to study at one of the leading schools of public health in the US or indeed in the world why don't you consider GWU here in our nation's capital Washington DC. I can hardly think of a better place to start your career. Now I will leave information about our school in the description. The plan in this tutorial is to use the GPT4 model with the code interpreter from chat GPT. Now this requires chat GPT plus which is the paid subscription. In a later video I will take another look at a large language model that is available for free. Now for this video though I will start by uploading a spreadsheet to chat GPT and then show you a variety of prompts that you can use to perform EDA using a large language model. We will take a look at summary statistics, comparative summary statistics and data visualization. Now stick around till the end because I have included a sneak peek into how you can set things up so that you can perform statistical tests in chat GPT. To get us started we'll look at the data set. Now this data set is available on Kaggle and in other repos on the internet. I've simplified it a bit by removing some of the columns just to keep it easy because what we're trying to do is just some exploratory data analysis. I'm going to call it just EDA. As mentioned this is a simplistic data set. If you want to learn more about the diagnosis of coronary artery disease which you'll see is our last column here whether someone has heart disease or not. If you want to learn more please have a look at this link down below and you can read up a little bit more about the proper diagnosis of coronary artery disease. So we're just going to use this data as it is quite simplistic view of it but we just want to do some simple EDA and have a look at how to do it using an LLM. So a couple of things about this data set. First of all I've noted there for you that this is in tidy data, tidy data format which means we have very well defined what a row and what a column is. So along all the rows each separate row, a row of these would be a single observation. That's so a single participant in the study and then for each of these variables we'll have a random value for a very specifically defined variable. So each row is a separate observation. Each column then is a separate and individual variable. So we see the names at the top. The column headers age and then binary six cholesterol resting ECG, max heart rate, exercise and gyna and heart disease and then for each of these columns a very specific variable, specific data type, defined sample space. So if we look at exercise and gyna there's only n and y. That's the only values that are possible if we look down the age column. It's only integer values so we won't find anything like a string or words or sentences in that column. There's only integers allowed. For the next one binary six there's only m and f for male and female. There are no numbers in there. So it's a very well-defined sample space, a very well-defined variable and a very well-defined level of measure. So the age column for instance that would be continuous numerical whereas for the binary six well that'll be a nominal categorical variable. So these things are very well-defined defining for us this idea of tidy data. The next thing that we'll notice is if we look at these column headers, cholesterol resting ECG, that there are no illegal characters. Now the most common illegal character would be a space. Now that might look nicer if we had resting spaced ECG. That might look nicer and certainly if we want to create plots we certainly want that space in between but if you've got any kind of experience with Python R or any other programming language you'll know. If you want to do this kind of data analysis it's much better if there are no illegal characters inside of these column headers. So that's just something to be aware of but as I mentioned if we do want to create plots we'll have to fix the fact that that looks about ugly just max HR and you want that to say maximum heart rate. So let's have a look at these seven variables that we do have here. In our first column it's an age variable with the name age and as I mentioned there's only natural numbers in there but it does define for us as far as level of measurements concerned that that is a continuous numerical variable binary six. So simplistic view of gender there and as much as it's a binary variable there are only two unique values in our sample space there's either f for female or m for male. So just a very simple data set. In other words cholesterol that's serum total cholesterol that's measured in milligrams per deciliter and you can see the values there once again they natural numbers but that does define for us a continuous numerical variable. Next one is resting ECG that's a multilevel or nominal categorical variable. They are three levels so three unique values there are in other words three classes or three levels these unique values in the sample space of this variable and they are normal for those participants that just have a normal ECG electrocardiogram ST for ST segment changes now if you know anything about an ECG that might indicate that there is some ischemia on the heart there's not enough oxygen supply to the heart muscle itself and then LVH for left ventricular hypertrophy and that is enlargement of the left ventricle so that can be at least looked at as far as an ECG is concerned giving that idea from the ECG that there is LVH. So those three classes or three levels there for resting ECG then max HR maximum heart rate that's the maximum heart rate achieved by each individual when they were stress tested and stress test is a exercise induced stress so usually walking or cycling in in in a lab allowing for the measurement of the maximum heart rate and that can indicate various problems. Next one is exercise induced angina now you're going to either ask the patient you know whether develop angina when they are physically active or once again in the lab on a treadmill or on a bicycle see if they do develop a pain across the chest that's exercise induced angina when they are physically active and the sample space there is yes and no Y4S and for no so that makes it a binary categorical variable as well and then finally we have heart disease and that's encoded with a zero if there no heart disease and one if there is a heart if there is heart disease present and that makes it binary categorical that is not any medical variable that's just encoding so we've got to be we've got to be careful there again it's not the simple we won't just use those six variables to decide whether someone does have heart disease so please have a look at the link that I've put down here below if you want to learn more about the proper diagnosis of heart disease but this is our data set so we're going to use an LLM and we're going to do some EDA exploratory data analysis so here we go we've chosen chat gpt for this demonstration and that is at chat.openai.com of course if you want to sign up there's a whole sign up process they are going to ask for your telephone number etc and as you can see here this is chat gpt plus so the plus makes this gpt4 model available to us with all the plugins and code interpreter but that does cost the money it costs $20 a month and if time allows I will make a video where we'll look at some of the free options like clod.io but here we have gpt4 so this is in chat gpt plus costing $20 a month so if I hover over gpt4 you'll see it says there that it is available exclusively for plus users and then gpt4 currently has a cap of 50 messages every three hours even though we are paying for it and then there's the default setting the code interpreter setting which is the one we're going to use and you can see it already has a check mark so just click on code interpreter and then there are an abundance of plugins that you can use as well but for this demonstration of eda we're going to choose the code interpreter and that is then already selected so right at the bottom we can also see this is the august third version of the gpt4 model and we can see our little box where we're going to interact with the large language model you'll see the little plus symbol there for if you hover over that it says upload file and that is where we're going to upload our data set so in this instance for chat gpt4 model with code interpreter you have to have the csv file the spreadsheet file on your local system so that you can upload that one thing I didn't mention when we had a look at the at the data set itself that was saved as a csv file so from any spreadsheet software you can save in the proprietary format of that software or you can choose to save as a csv file that stands for comma separated values and what that does is just strips away all the extraneous niceties that we like to add to our spreadsheet files by you know taking the dates and putting them in a certain format adding dollar symbols to anything that is financial data etc just strips away all of that so we're working with the pure values themselves and I always suggest that you export your spreadsheet files as comma separated values so that is the file format that we're going to use here and upload so I'm going to click on upload which will bring up a navigation system on my explorer on my system here and I'm just going to select that file click on it and upload it here so there you go it's hotlm.csv a link to this file will be in the description so you can use it yourself and then we can just type our message there so this file is already uploaded once you click on that upload depending on the size of it you'll see a little blue spinning disk and you know that indicates that the file is being uploaded as it stands the file is already uploaded now we can just hit this little play button here or sending our message so that the llm can interpret this file and it'll do a pretty good job it really looks at the data type for each of our columns have very nice if your data is in long format tidy data tidy data format makes it very easy for for the code interpreter to analyze your data and your data should be in that format anyway for proper analysis but I like to do something else I like to put a short little message there telling GPT-4 about my data set so there we go I'm going to copy and paste a set of prompts that I have pre-written and we'll go through each of those I'm just only doing that just to save time so you don't have to watch me type but we'll go through these as I mentioned you can just hit the same message without typing any of this once your CSV file your data file is uploaded and as I said chat GPT will do a pretty good job of interpreting what your variables mean but I do like to write a proper prompt and give it as much information as I can now I would give even more information than this but this is just for demonstration purposes so let's go ahead so I've said yeah the CSV file contains seven columns and then I I talk a little bit about each of these the age describes the age of participants in years binary sex describes the gender of each participant with two classes m4 male and f4 female cholesterol is the serum cholesterol in milligrams per deciliter resting ecg is a multi-level variable with classes normal for normal ecg st for st segment elevation or changes and lvh for left ventricular hypertrophy max hr is a continuous variable measured in beats per minute describing the maximum heart rate reached during exercise exercise angina is a binary variable with two classes n for known y4 yes and describes whether angina was induced by exercise and heart disease is a binary response variable with a zero for no heart disease and a one for the presence of heart disease so I would typically do a little bit more than this but as I said you don't need to do anything at all when you just upload this file so there we go I'm just gonna hit send message and there you can see the response it says great let's start by loading the data from the CSV file to inspect its first few rows this will help us get a sense of the data structure and it'll do that you know without us having given any prompts and it'll do a pretty good job but now that I've given it a little bit more it should know a little bit more now the other thing that you'll see is finished working show work and if I drop down you'll see the actual code in the results so it's going to show you the actual code that was used so here we see it's always going to be python by default here and uh so you can actually copy and paste this code and put it in your IDE that's an integrated development environment I like to use visual studio code or you can use it JupyterLab there's various software that you can use to type in your python code but it's going to give you the actual python code that it used and the output of that python code so it's an excellent way to learn python is just to use a large language model so this is not going to work for our you know other some of your other favorite languages for your data science and I suppose it just underscores the popularity of python when it comes to data science now it's going to tell us a little bit more about these as I said if I had put in no prompts it would have it would have given this same same set of results here that we can see for these seven variables but giving it that little prompt maybe later on it'll help the large language model make more sense of the analysis so that's it our data set is now uploaded it's very simple I clicked on the plus behind the scenes I just navigated on my internal hard drive on my computer to where the CSV file was and I just added a little bit of a prompt and just sent the message and the data is now uploaded so let's go for our next prompt so here we go I have typed in provide summary statistics for the continuous numerical variables include the number of observations the number of missing data the mean median standard deviation variance minimum maximum range quartiles and interquartile range generate a table of the results so that's my prompt I could probably just have said provide summary statistics and that's it or at least summary statistics of the continuous numerical variables I would not have to put in all of those specific statistics that I'm after for the sample but it helps if you guide it this way and be specific about the summary statistics that you want let's see what the LLM does you can see here the table is being generated line by line we get a little message there at the bottom it says it appears that there are no missing values for the continuous numerical variables in the data set so that's brilliant and there we see there's our metric count mean standard deviation min the first quartile the median or then the second quartile third quartile maximum variance range IQR missing so put it in a nice little order there for us as well and we can see age cholesterol and maximum heart rate so we'll see there's 918 observations for each we can see the mean age was 53 and a half years with a standard deviation of 9.43 or variance as we see at the bottom which is the square of the standard deviation 88.97 so very nice table and we can very quickly get some idea this is EDA we need to understand our data in the first step of doing that is just to print out or determine these summary statistics and how easy was that I typed in a line of a couple of English sentences I should say a little paragraph of English sentences and there's my result once again I can click on show work and you can see there what was done this is the python code for producing this result here at the bottom and you can see that you can just click copy code and as I mentioned before if you go to your IDE you can just paste that code run it and it'll run because here we see the output of that code which was then used by chat gpt just to create this beautiful table that we can see here so very nice there's your summary statistics you have a very good idea of our continuous numerical variables so here's my next prompt I have typed in created table of the frequency and relative frequency of the classes for the categorical variables so here we don't want you know it's impossible this is a categorical variables so we can't have mean and quartiles and variance etc we want the frequency and the relative frequency and as mentioned there I want this in a table as well and there you go instead of a table we've actually got a little bit of a list of you here and there are variables it's binary 6 it's found m and then for male f for female we see the frequencies there 725 male and 193 female and with a relative frequency or proportion then that's 78.98 male and 21.02 female so we'll see that for resting ECG as well normal lvh for left ventricular hypertrophy st for st segment elevation and probably st segment changes would have been more appropriate but look it is drawing that initial information that I gave about the data set it's taking some of that information to be able to write this response for us exercise and gina no and yes and then heart disease one presence of heart disease zero no heart disease so again using some of that information that's why I like to give it information about my data set when I do the first upload so now we've got a pretty good sense of our numerical variables and our categorical variables so with the cda we start to develop a good understanding of of our data set now we can get a little bit fancier than this so what I've done is I've included all the values for these columns for these variables but what if I just want to do my summary statistics but I want to filter for some of the specific classes for instance for one of my variables my categorical variables so let's have a look at this what I've typed here I have typed create a table of the summary statistics of the numerical variables used before but filter only for those with a normal resting ECG so once again just a normal English sentence I didn't use any of the normal or st lvh the the abbreviations that were used as as the names for those unique values or classes in that variable no this is a normal English sentence I want a table of the summary statistics of the numerical variables used before so it's going to give me all those statistics but I want to filter only for those with a normal resting ECG so let's just go back up here and if we look at our results here resting ECG normal just have a look at that frequency there were 552 instances or observations then that had a normal resting ECG so let's see what happens with this prompt and look at that it says similar to the entire data set there are no missing values for the continuous mega variable in this filtered subset if we look at the count we'll see 552 so really that was correct there were only 552 observations that had a normal ECG and now I'm going to get the summary statistics of my numerical variables age cholesterol and maximum heart rate but only for those 552 participants I'm excluding all the others so you can start to see how specific you can get by filtering some of your data and then redoing your summary statistics so you can get a real good sense of what is going on with your data and I really can't emphasize this strongly enough if you want to start to understand this information the knowledge the story that's hidden in your data summary statistics is just a the proper way to start looking at your data so up till now we've only looked at a single variable at a time so we've included all of the values so the whole data set for our summary statistics both for our continuous numerical and for our categorical variables and we've seen how to select or filter out only a subset of our participants and so that's great if we just look at a single variable at a time called univariate summary statistics but we can also do comparative summary statistics where we're going to compare two or more groups to each other and we do remember that one way that we develop these groups is just to group them by the classes for one of our nominal categorical variables so what I've typed here is use the same summary statistics for the continuous numerical variables as before but only for the age column so I'm asking for all those statistics but only for the age column and group the results by the classes of the response variable now remember I told it right at the beginning that heart disease is the response or the target variable or the dependent variable so use no heart disease for zero and heart disease now let's just change that that should be a one and heart disease for one as row values for the two classes of the heart disease variable so let's have a look at what the large language model does with that so remember what I'm trying to do I'm trying to create summary statistics of my age column but I'm doing comparative summary statistics I'm going to divide all the values into two groups and those two groups are the two classes that it finds in the heart disease variable so here we go here's the summary statistics and as I said I wanted two rows the zero for no heart disease one for heart disease and that's exactly what it's done so instead of putting a zero and a one there it's actually put the words no heart disease and heart disease so there were 410 with no heart disease 508 with heart disease and as far as the age column is concerned we see the mean and now we can see that those with heart disease were slightly older they had a mean age of 55.9 versus there were no heart disease of 50.5 and that's what we mean by this is comparative summary statistics so if we know that we have a bunch of research questions where we're going to make comparison between two groups and the two groups are the two classes of our target or our outcome or response variable our dependent variable it's very good if we do this to start off with if we do this comparative summary statistics now we need not only do that for our continuous numerical variables but we can also do this for our categorical variables so I have typed create a contingency table using the resting ECG and heart disease columns include row and column totals in the table also generate a table of expected values under the null hypothesis that the variables let's put a little s there are not associated with each other so this is comparative summary statistics as far as frequencies are concerned and that's what a contingency table is going to give us now along the rows we'll have one of the variables the classes of the one variable and across the columns we'll have the classes of the second so this is also a form of comparative summary statistics so here we go remember there's always the python code to show you how the results would be calculated if you would use python code but here we see our results so along the rows it's put the resting ECG classes lvh left ventricular hypertrophy normal or st and across the two columns no heart disease and heart disease so if we look at those without heart disease 267 of them had normal ECGs 61 had st segment changes and 82 had left ventricular hypertrophy and we see the different frequencies when it comes there to to those with heart disease and then we can also see the row totals and the column totals so with no heart disease once again they were 410 and with heart disease there was 508 and then under the null hypothesis remember these two variables resting ECG and heart disease are independent of each other and if you remember a bit of your probability theory there's a very easy way that all of these expected cell counts can be calculated and the easy way to remember that is if we look at this first cell where we get 83.97 that is in this lvh row and in this no heart disease column so we're just going to multiply these two that 188 which would be the row total times the 410 which would be the column total for this specific cell this first cell and then divide by the sum total 918 that gives us 83.97 but it's best to to think about this in terms of independence of these two in other words our joint probability must be equal to the product of the two separate probabilities as far as the two things that we would put into the joint probability so lvh and no heart disease and so here's our expected frequencies we see that all of them are five or more and from that we know that's at least one of the assumptions that we meet for the use of a chi-squared test for independence or Pearson's chi-squared test so there's our summary statistics and then also a very nice table of expected values now while summary statistics are great specifically comparative summary statistics it's even better when we visualize our data so what have i asked for here create a histogram of the age column use the title and then i've used the quotation marks there distribution of participant age also use the horizontal axis label age in yours and the vertical axis title count use a light orange as the bar color create bins with a minimum of 20 and a maximum of 80 with a step size of 10 so what i'm trying to showcase here is i can be very specific about the styling of my plot i can tell it what kind of titles axis labels or axis titles i want and also as i said the color and the actual bin size and what i love about this response is that was actually a mistake in the code here and you can see in red there there's all the error there's a using a string of single character colors as a color sequence is not supported so it actually you know executes this python code finds an error and then tries to correct itself and then you can see the actual code where the correction was made so that we can get the proper plot and there's our plot i've got the title that i asked for i've got the axis labels or axis titles that i asked for and then the color that was orange and we can see the bin sizes it was from 20 to 80 and in step sizes of 10 so i can be very specific about this and that's going to change the code for me look for instance there it says bins equals range 20, 81, 10 and that very specifically defines these bins so don't leave it just to the default i can be very specific it's going to generate that python code for me but remember this is using a large language model so if you're not interested in the code we can just forget about the code all we want to do here is just look at the eda the exploratory data analysis and we can see that age is kind of normally distributed and we can take a lot away from that as far as the majority of cases in this decade 50 to 60 and very few people on this younger age group says a little bit of a left tail i suppose included there as well so that's great for histogram let's plot some more create a scatter plot of age and max HR add the title scatter plot of age and maximum heart rate use the horizontal axis title age in years and the virtual axis title serum cholesterol and milligrams per deciliter group the markers by the classes in the heart disease column add a legend so i'm not only want to scatter plot but i want to scatter two different scatter plots you know on top of each other so i want that separation that group by the the classes in the heart disease so the two classes those without and those with heart disease and i want to see them separately add a legend named heart disease with the class names no heart disease for zero and heart disease for one and also insert grid lines so very specific about this plot that i want now you needn't be this specific you are still going to get a plot and this is all eda so i'm just trying to learn about that knowledge that story that's hidden in all the numbers of my spreadsheet but i've asked it to be very specific and that's what it's done so look at that you know there's sort of a little bit of a negative correlation there as people get older their maximum heart rate goes down a little bit and we can see there the little blue markers for no heart disease and the little red markers for those with heart disease so a lot of information once again that i can get from the scatter plot now in future tutorials i'll show you that you can then indeed now do some or calculate at least the correlation between these two and calculate the correlation for each of the two groups those without and with heart disease but this tutorial is all about just the eda so we've created a nice histogram and you can go through all of your continuous numerical variables and create this histogram you can also then you know create two histograms so that you do summary data visualization or comparative data visualization i should say for those with and without heart disease for instance so try out different prompts and really ask this llm to create plots that you want so that should give you a proper idea of the power of using an llm to do your eda your exploratory data analysis it is so easy to do you can be very specific you need not be as specific as i was here but you can learn you know all that initial information start to get that story out of your data by comparative summary statistics and data visualization really powerful here now as a little sneak peek not part of eda but if you want to explore a little bit further have a look at what i've typed here so create separate lists for the age values for each of the two classes in the heart disease column determine if the data meets the assumptions for the use of an equal variance t-test to determine if there is a difference in the mean age values for each list so think about your classes as far as by statistics we're concerned one of the first statistical tests that we learn about is a t-test and that is where we compare the means of a continuous numerical variable the same variable between two different groups now if you want to use a t-test and remember there are various t-tests if i want to use a t-test i must make sure that my data meets the assumptions for the use of that test so that's exactly what i've asked you i've told chat gpd what analysis i want to do i want to compare the means of the age values for these two groups people with heart disease and without but first let's make sure if the assumptions for the use of this t-test now specified here an equal variance t-test so that means it's also going to include those assumptions of you know whether the variances are equal so let's have a look at this responses and i think it's absolutely brilliant because remember in many postgraduate introduction to uh by statistics for public health research we're not necessarily going to look at some of these tests we might just mention these assumptions and for the examples that we use we'll usually say that the data you know do meet these assumptions but it actually you know gives us the important ones here it says independence of uh independence of observations now it cannot determine that from the data that that that we gave it but it can say here the data should be sampled independently from the two groups this is typically an experimental design issue rather than something we can test for so you've got to know that about your data normality each group should come from a population that follows a normal distribution so age should be normally distributed in the population from which the sample was taken and it says this can be tested using methods like the Shapiro-Wilke test now you can read up on these tests you know how good they are how well they perform and criticism of these tests you can read all about that but it's going to tell you that this would be a possible test that it could use and they should also be homogeneity of variances now the variances of the two groups should be equal this can be tested using Levine's test or Bartlett's test so you know wonderful things that you can read about here and even if you didn't cover this in class well you can use the LLM to learn about this first let's create separate lists for the age values for each of the two classes in the heart disease column and once again there's your code it'll show you in Python how to do that if you're interested in that let's just carry on then with the results the normality test told us it used the Shapiro-Wilke test and for participants without heart disease it had a p-value of 0.00483 now if our level of significance was 0.05 this will be less than 0.05 in other words this suggests that the age distribution for the participants without heart disease might deviate slightly from normality and when we look at the distribution of ages in those with heart disease the p-value is very very small and suggesting that the age distribution for participants with heart disease deviates from normality so we are we are not fulfilling or meeting that assumption for the use of students t-test so we're in trouble here with the homogeneity of variance Levine's test that was also below a level of significance of 0.05 and that suggests that the variances between the two groups are not equal so if we wanted to use a t-test we would have to consider an unequal variance t-test and all that information is there now it's going to say given these results the data does not meet the assumptions for an equal variance t-test specifically neither groups age distribution appears to be perfectly normal and the variances of the two groups are not homogeneous or homogeneous I should say in light of this it would be more appropriate to consider Welsh's t-test so that would be for the unequal variances or better still a non-parametric test such as the man Whitney you test if we want to compare the ages of these two groups now once again depending on your course you might cover non-parametric tests but certainly then the man Whitney you test would be used as a non-parametric test instead of a t-test as I mentioned this is not what this little tutorial is all about it was about edae but here we go I couldn't just you know it's told us now to use the man Whitney you test so let's just ask it to do the man Whitney you test so please perform a man Whitney you test to compare the two lists of age values the null hypothesis that there is no difference between the two lists and I'm just saying list list of values and the alternative hypothesis is that there is a difference between the two lists use a five percent level of significance write a full comment of the result so please be creative in what you type here but try to be as specific as possible just to help the large language model you know do what you ask and now it's written there for us the man Whitney you test returned a p value that is basically zero given our level of significance of five percent alpha equals 0.05 the p value is significantly below the threshold now the comment on the result the man Whitney you test revealed a statistically significant difference in the age distribution between the participants with and without heart disease specifically that p value is less than five percent therefore we reject the null hypothesis and conclude that there is a difference in the age distribution between the two groups so wonderful so now think of all the other things that you learned about in your postgraduate by statistics program or lectures or courses and you can well imagine that you can do everything that you learned about here using a large language model okay and that's it for this video I hope you've enjoyed it remember if you have not joined our school follow the link in the description to learn more about the george washington university you will learn a lot here that's a promise