and you'll be able to get more on the record. At this time, we'll move to member statements and I recognize the member from Windsor to come see. Speaker, I'm calling on the Premier, the Minister of the Environment, Conservation and Parks and the Minister of Natural Resources and Forestry to join the partnership in creating a national urban park down in our area. The federal government recently came on board. The city of Windsor is all in favor of it. So is the Essex Region Conservation Authority and all of the areas, natural heritage and environmental groups. What we need from the province is no different than what was required when the Rouge National Urban Park was established in Toronto six years ago. Speaker, Ontario owns and manages the Ojibwe Prairie Provincial Nature Preserve. These 230 acres are the largest protected remnant of native prairie in Ontario. At one time, Speaker, parts of this great province were home to grand stretches of tall grass prairies and savannas. This nature preserve is needed for a natural patchwork quilt, if you will, connecting other pockets of natural areas close to our new international border crossing, the Gordie Howe Bridge. When we put them together, we'll have about 900 acres starting along the Detroit River, connecting Ojibwe Shoresy, Ojibwe Tom Joy Woods, the Spring Garden Natural Area, the Black Oak Heritage Park, along with the Ojibwe Prairie Provincial Nature Preserve, and the Oakwood Bush, now linked by a wildlife corridor across the Herb Gray Parkway, which connects to the Gordie Howe Bridge. Speaker, this concept has been around for 20 years. Now that the feds are on board, it's really just up to the province. I urge the Premier and the ministers to work out a deal with Ottawa and create the Ojibwe National Urban Park. Member Statements, I recognize a member from Mississauga Lakeshore. Thank you, Speaker. I'm pleased to rise here today to speak about a very special and unique historical exhibition happening now in Mississauga, in a 10,000 square foot gallery at the Air Mills Town Center. Thousands of pictures, documents, artifacts are now on display. The showcase, remarkable life, and the incredible achievements of my mentor, my advisor, my friend, the legendary Mayor of Mississauga, Hazel McCallion. Curator, Madalina Van Duzer, put together an extraordinary collection and educational expression about Hazel's many decades, breaking barriers in business, sport, and her leadership from the Mississauga Miracle in 1979 to the transformation of Mississauga into a world-class city. Speaker, many items are from McCallion's own home, including a picture of the Mayor, then 92, reeling in a 16-pound Chinook salmon at a fishing derby off the Port Credit as Toronto Mayor Rob Ford held on to stop her from falling into Lake Ontario. One of Van Duzer's favorite items in mind is a lawn sign from Hazel's first campaign in 1978. She ran against an incumbent Mayor who used the slogan, a good Mayor. Hazel's slogan was, a better Mayor. And she was. And she never needed another lawn sign again. It was an honor for me to attend the grand opening on October 26th, along with people from around the province, including the mayors of Brampton, Caledon, and Milton. And the sponsors included the Art Gallery of Mississauga, Leona 183, and Lakeview Community Partners. I encourage everyone to visit Hazel McCallion's 100 Years Memorial. The exhibit is open until February 28th, and it's free to everyone. So I hope that you all attend. Thank you. I recognize a member from Algoma, Manitoulin. Thank you, Speaker. And I want to talk about the Superior Children's Center, particularly Lauren Stefanic, the coordinator out of the Horn Pain Early on Child and Family Center. And I think I better use her words because what they do there is almost a little bit of a miracle. She says, as a professional registered early childhood educator working in an early on child and family center, I consider myself to be a mental health care provider. We feel a critical role in supporting families in their daily struggles to maintain their mental health and well-being. Individuals within our professional have been engaging in numerous strategies to connect with families during stressful times, through music and movement sessions, story times, baby wellness program, parent and caregiver chats, parenting workshop discussion groups, community stories, walks and scavenger hunts, just to name a few of the things they do. We have been creating nurturing relationship with families to meet the needs of being able to connect with others during an extremely difficult time in their lives. We reach out to them on a daily basis and provide programs that are aimed at engaging and encouraging them to interact with their children. We provide informal and connection, information and connections to specialized services and we connect families to other programs and services by promoting community activities and programs. We are often the lifeline of many families without them even realizing it. I take off to my hat to these individuals who are working at these early on centers and the positive impacts that they bring to the community, to families and the mental wellness of us all across Northern Ontario. Thank you. Let's offer everyone a reminder that member statements are 90 seconds if you could please try to adhere to the time. I now turn to the member from Markham Thornhill for a member statement. Thank you, Mr. Speaker. Today I would like to recognize all those affected by chronic obstructive pulmonary disease, otherwise known as COPD. This chronic disease caused airflow blockage and breathing related problem. As a fourth leading cause of death in Canada, COPD affect more than 2.5 million Canadian and over 900,000 Ontarians. Mr. Speaker, as many of our loved ones continue to battle respiratory illness throughout this pandemic. It is a critical time to bring awareness to this deadly disease, especially as the people with COPD are the higher risk to become severely ill from COVID-19. More than half of those living with COPD are unaware they have this disease. That is why in December 2019, I introduced a private member bill, Bill 157, to proclaim the third Wednesday of every November COPD awareness day. My aim was to increase the public awareness of COPD so that we can promote early detection and the treatment and the early diagnosis. Mr. Speaker, after Bill 157 received royal ascent this June, I am pleased to recognize today, Wednesday, November 17th as the first COPD awareness day in Ontario. I encourage everyone to advocate yourself on the risk of COPD and to be proactive in maintaining good healthcare. Thank you, Mr. Speaker. Thank you. I recognize a member from Humber River, Black Creek. Thank you, Speaker. Faith is a central part of many people's lives. And as part of their faith, they go to a safe place to pray with others, to reflect, to find peace and tranquility. But last week in my community, that tranquility was broken when an individual threw a huge rock through the window of the tarik mosque while people were praying. Thankfully, no one was injured, but not all injuries are physical. The Muslim community has been shaken by ongoing acts of Islamophobia and hate. Last June, four members of an entire family were murdered in a targeted attack while they went out for a walk simply because of their faith. In September, 2020, an elderly man was murdered in another hateful Islamophobic attack as he sat outside of the IMO mosque in Rexdale, where he was volunteering to help worshipers follow COVID-19 guidelines. And Speaker Sadli, there have been many more incidents as a vandalism and Islamophobic hate that has left Muslims feeling unsafe. There's no place for Islamophobia or hate in any of its forms here in our province. Last Sunday, I visited the tarik mosque in solidarity with the Muslim community. We must stop this hate. It's past time for this government to take action. The National Council of Canadian Muslims have made 61 recommendations to all levels of government to combat Islamophobia in Canada. This government must implement the NCCM's provincial recommendations so we can take real action to stop this hatred. Every Ontarian deserves to feel safe. Thank you very much. Member Statements, the member for Mississauga Centre. Thank you so much, Speaker. I have had... It has been an active few weeks for the Polish-Canadian community with many events and initiatives that I have had the privilege of being a part of. First, there was the recent second reading of Bill 18 that will, if passed, declare the month of May as Polish Heritage Month. A month to reflect on the contributions that Polish-Canadians have made to Ontario's history, culture, and economy. Sponsored by my colleagues, the member for Renfrew-Nipisic-Pembroke and the member for Etobicole Lakeshore, this bill was met with strong support in the local Polish community. In celebration of this, we welcome the new consul-general of the Republic of Poland, Mrs. Magdalena Bztukowska, for a small meet and greet. But the month of November was also a time for somber reflection. Coinciding with Remembrance Day, the Polish community came together to commemorate Polish Independence Day by paying our respects to Poles who paid the ultimate sacrifice in defending Poland's sovereignty, democracy, and freedoms. With the messages of Remembrance Day and Polish Independence Day being so closely related, it reminded many of us that the struggle for freedom and democracy is one that resonates with nations around the world. Finally, speaker, beginning this Friday is the 12th annual Polish Toronto Film Festival organized by Ekran Polish Film Association. The festival will showcase films with both a Polish and multicultural focus, all featuring English titles for everyone to enjoy. For more information and film listings, I encourage everyone to check out ekran.ca and go see some incredible Polish filmmaking. Thank you very much. Member Statements, the member for Toronto Danforth. Thank you, speaker. Speaker, everyone's been following the news. You know what's going on in British Columbia. Climate-driven flood rains are having huge impact wreaking havoc in that province. At least one woman was swept to her death by a massive mudslide that buried the highway she was driving on. Towns have been flooded, thousands of people are being evacuated. This is a taste of the climate crisis, the future that's wreaking havoc today. And what's extraordinary to me is that this government can ignore that reality. It's plowing ahead with Highway 413. It's plowing ahead with the Bradford Bypass. When we all know that these highways will be adding substantially to the climate crisis, they will accelerate the heating that will put people's homes, their livelihoods and their lives at risk in the years to come. We've seen it in Northern Ontario. Communities have to be evacuated by aggressive, because of aggressive forest fires. We know what's coming at us. The Premier needs to abandon these projects as soon as possible, and he needs to shift course and take aggressive steps to reduce our emissions so we can at least slow down the climate crisis, at least slow it down. It is not too late to act, so act now. Thank you. Member Stavins, the Member for York Centre. Exactly 20 months later, and in response to rising case numbers, the head of Ontario Science Tables said Thursday that we need two more weeks to flatten the curve. Apparently, lockdown school closures, passports, mandates and the erosion of democracy didn't work. The government subjected Ontarians to the second longest and harshest lockdown in the world. It costs countless deaths, and many of us will not rest until we get a fair audit so history can judge lockdowns fairly. The government caused our children irreparable harm with the longest school closure in the world, despite seeking and getting unanimous advice to open the schools. For 20 months, Ontario's pandemic response leaders denied science by denying natural immunity while peddling herd immunity. Now the science cut up and they can no longer deny it. The increase in deaths from overdose alone under age 65 is three times greater than all COVID deaths under age 65. According to a McMaster pediatric surgeon, multiple children died from a late cancer diagnosis and mental health catastrophe is gripping the province. The chief medical officer finally admitted that natural immunity is good immunity. The governor of California acknowledged that it's seasonality that accounts for the rise in COVID cases. And finally, the CDC abandoned any plans for herd immunity because you cannot obtain herd immunity with a leaky vaccine. For 20 months, the science deniers told us to listen to the science. 20 months later, they want two more weeks to flatten the curve. Thank you. The next member's statement, the member for Perry saw Ms. Coco. Thank you, Mr. Speaker. I rise today to celebrate a milestone in my riding. Dear Hearst Resort and Huntsville celebrated its 125th anniversary this summer and is one of Ontario's oldest resorts and greatest hospitality success stories. Dear Hearst has grown from a family run seasonal hotel with just two guests during its initial season in 1896 to year round operation that can accommodate more than 1,000 guests at a time. Today, Dear Hearst boasts exceptional recreational amenities including two golf courses, a treetop trekking park, many water sports in the summer and cross-country skiing, snowmobiling and snowshoeing in the winter. Dear Hearst boasts one of the biggest conference facilities north of Toronto, a facility that hosted the 36th G8 summit. And country music fans may know Dear Hearst as the place where Shania Twain got her start as a professional singer. Through it all, Ms. Coco's beautiful lakeside surroundings and the congeniality of Dear Hearst staff remain its biggest assets. Speaking of Dear Hearst staff, I want to congratulate Executive Chef Rory Golden on receiving the Tourism Industry Association of Ontario Lifetime Achievement Award. With more than 30 years of experience at Dear Hearst, Mr. Golden's passion has helped put Ms. Coco on the provincial, national and international culinary map. And his dedication to using local ingredients has supported many other local businesses. Dear Hearst is a huge driver of the Tourism Industry. Ms. Coco normally attracting visitors from around the world. As we rebound from COVID-19, I hope that our government's staycation tax credit will inspire more Ontarians to visit Dear Hearst next year. Thank you. Thank you very much. That concludes our Member Statements for this morning.


Hey tribal journeymen and women Give me a sec. I'll take off this mask and we'll get into a subject, which is gonna be Really interesting. We're gonna do it on our favorite bench by the way In our nice location for that aside the story we're about to go into is Digging down into understanding Akito's philosophy Which is a worthwhile subject already. I think honestly, I think it's a It's actually a great philosophy and There's a lot of nice ideas in it but it's everything it also has a dark side and if you hang out in Doing something for long enough You usually bump into the dark side to usually start to reach the limitations of that aspect and that definitely helped It happened to me with Akito if you know my background you probably know a lot about it, but Usually when I talk about Akito, I talk about the technical side of it like You know the hierarchy structure and how it pollutes the dynamics in community and the abuse of power by Instructors and the lack of critical thinking and pressure testing so all of that It's more than a technical level and it's been a while since I actually spoke about what specifically the Akito philosophy is But again, well, oh Attacked me, but again while there's a lot of awesome stuff in the Akito philosophy Which I'll be actually enthusiastic to share because it's that it's been a long time since I spoke about it at the same time there are I think personally, I think Akito fails in delivering that philosophy in living up to what it's supposed to be and There are good reasons for why it fails so if you're interested to learn all about that stay tuned for this episode and Let's get going so in order to understand the Akito philosophy first of all It's important to know at least a little bit about the history of Akito or more specifically the history of Akito's founder who kind of created the whole philosophy and and eventually it started to kind of Become very confusing because of certain aspects, but that's down the line initially everything started from Morhio Shiba and Now I do need to say that Morhio Shiba is he's one of those characters one of those figures in history where he was Apparently able to do some things which other people weren't able to do like he was stronger than others or he was able to do some kind of tricks, which seemed supernatural and I think when that happens when you have that kind of legendary status and Especially since also you're involved in spirituality, which he was he was you could say very spiritual Basically, you could say also religious But then when you have that combination Usually it happens so that those people get tied like flies are attacking me today. What heck is this? so Usually what happens is you become tied with a whole mythology or People when you leech reached that kind of living legend status stories about you start to surface which are Most of them are not true, but they get passed around You know, maybe some part of it was true and they get expanded like you know I caught this big fish and you expand the fish kind of the same dynamics and The same I believe it happened with more here Shiba and it there's actually a funny story I had already I went for a personal experience of this. It was really crazy But I'll give you a personal experience example so you would know what I'm talking about So big very brief reminder I was a yoga a keto instructor and I would often be invited to schools too because I Seems I'm very apparently I'm very good with especially teenagers or kids I'm good at inspiring them kind of engaging them and so schools wouldn't might need to talk to them and motivate them and I was I went to one of the schools I think to introduce kind of a keto or something like that. So I was dressed in my a keto gear you know with a whole Haka mine everything it looks quite impressive and the main teacher who was Hosting me or welcoming me When we stayed in the room just her me and my senior student who was helping me out She kind of came close to me and she said so Will you be able to show us your magical trick? I was like What what are you talking about? And she's like I heard I heard that you're able to pass through a pen for a room without touching and I'm like What I'm like, I don't get it like what is she talking about and I start digging into what she means and I realized It was a misunderstanding because when I was doing some projects in schools There was one exercise like a teamwork exercise Where I would take a bunch of kids and I would give them an exercise Like a brainstorming exercise that would tell them you need to pass on this pen From one side of the room to the other without touching it Physically with your hands and so they would have to come up with creative ways Which one of the best ones is just gather a bunch of pieces of papers or notebooks and you know create this line and and you pass it down and But so I try to explain to her I said so that's what it is and she's like she's looking at me like no No, no, no, I know and she's like dead serious. It's like I It's like like don't don't lie to me. I know I know you're able to do that It's like so come on. Will you show it and I'm like, oh, I'm like, oh, well, yeah, maybe not today. So basically There was this legend in her mind that I'm able to pass through it pen Through a room without touching it because it was a misunderstanding But then you know, she would tell that to others obviously and others would believe someone believe and then you know because I think because I was also part of that Mythology of spirituality and martial arts and they're mystified often I guess that gives a better gateway for these legends to spread So it's crazy that I actually even went through a personal experience of bumping into that But I'm dead sure that that's exactly what happened with more. He is she but and there are a lot of crazy and Interesting stories about him like people getting knocked out but just being touched by him and so on and you know It's hard to say whether it's hypnotic susceptibility Which I made a video on one of my channel in my main channel about that in past or or what it was but I think it's like a mix of everything mix of unique abilities that that individual was able to show like kind of special abilities, but But then mixed with all types of talk So so so when I'm gonna tell that story the reason I'm bringing this up is I'll do my best to portray a quick story of more yeshiva also known as all sensei the great teacher but Note that I'm not like, you know a history expert and I dug into his history quite a bit back in the day So I will probably portray quite well, but it's it's it's also a mess of you know Legends and stories and so on so I'll just give you a brief introduction But you know take it with a grain of salt and some some places I may be mistaken But I'll give you the main essence the main picture so What it's important to know about the founder that based on his histories that from early days he was inspired and enthusiastic about Kind of the mystical or the religious the supernatural and he was into a shintoism the you know pagan tradition of Japan He apparently was a very weak child And very introvertive so he would spend time a lot of time thinking and observing things around him and Based on the story he that's how he got exposed The whole spirituality traditions and rituals of shintoism And he became really fast about it and later he picked up martial arts And I think those two things always kind of went toe to toe in his life He apparently trained a lot and became very Very effective very effective martial artist very powerful one His devotion can be seen by the interesting moment where He even built a house for a martial arts instructor so kakutakeda descendant of a samurai line practitioner of Daichiru Aiki Jujitsu And so he built or more he actually built a house for him and hosted him there And like I think provided everything for him just so he would teach him my Not Aikido Aikido didn't exist back then but he's like a Jujitsu So you can see he was kind of very you know Devoted and very kind of intense. There's a lot of stories about how he was like that But besides him training martial arts another significant moment in his life is that he met Anisaburo Daiguchi it's been a while since I said those names, but I think I'm right He was basically a cult leader like a spiritual religious cult leader. Uh, and he had his own Religion I think it was in Omo Tokyo If I'm not mistaking it or whether it was it was another one, but I'll write it to you down somewhere Not that it matched I guess but he had his own religion which apparently from what I gathered I was aiming to unite all religions But apparently it was like really spiritual and there's this moment where they went to korea I believe and try to create this kind of spiritual hub Like an independent city and they got in trouble and they nearly died That's the moment where stories say that moriashiba was able to see And I think that's how he perceives it himself. He was able to see bullet lines Like before the guns shot and he was able to avoid those bullets Uh, and that's how he survived and he would I think that that story is documented and one of the interviews he gave so Apparently he believed in it himself Interesting that like a quick note now that I'm looking back about It's been a while since I thought about it all but, uh, if you think about the theory of flow And there's a great book about it With a weird name the name is the rise of superman But it's a great scientific book about the state of flow like that in deadly conditions your brain goes into maximum capacity And it's able to do things which you normally wouldn't be able to like you you perceive things as slow motion and so on Like it's a legit thing. So, you know, there is a chance that Moriashiba he went in that near-death experience where he was shot at from distance You know, his brain went into the flow state and he started avoiding those, uh bullets Maybe you know, I'm not saying like bullets bullets I think the way he expressed that story in one of the translations is that He perceived the lines of the guns that were aiming where they were aiming and he would be able to position himself Like where he wouldn't get shot, which sounds more realistic of it than dodging bullets directly Uh, but yeah, so, you know, maybe he did have some some of these extraordinary experiences which made him even more into this mystical figure But uh, one rear another, uh Eventually, he got encouraged by his, um Spiritual leader the Gucci to kind of continue to train martial arts not to drop them I think if I remember well, but you correct me I think he was at a crossroad where he was kind of considering well if I'm doing spirituality Maybe I should just drop martial arts, but he was very, you know, kind of proficient at them So so his teacher suggested him to continue on and he would teach, you know, the the spiritual cult they had martial arts But a very significant point in his life aside that I consider to be is When Hiroshima and Nagasaki happened, you know, the nuclear bombs were dropped on Japan and I think the story goes that that really impacted more Hiroshima And it was interesting because I think there's there's kind of a dark side to his history that I think it's not commonly spoken of but Some people addressed that to me a few times and I got fastened about it, but never dug into it But I think initially in his young days Mori Yoshiba was very pro-japan. He was very nationalistic like I guess most Japanese And then he was all about, you know Japan rules and let's let's make this happen But I think with over the years he kind of became a bit more open-minded and especially when Hiroshima and Nagasaki happened he That really made him think apparently based on the story that he realized that war is such a mass destructive Thing, you know second world war is happening over those years and it ended with that note And I think that made where she'd understand that if we will continue like many people I guess that if we will continue down this road and if we'll have, you know more nuclear wars We're fucked, you know humanity is not going to survive Uh that that kind of relates to the quote from einstein, I believe which is a great idea I think it's einstein if i'm correct that he said that You know, uh I don't know how world war three is going to look like but I know that world war four is going to be fought by sticks and stones Meaning, you know, the nuclear war will just blow away everything and then we'll have to restart civilization so I think a lot of people were exposed to that idea and That made where she book kind of reconsidered.  I know he was struggling with the same idea that notion that People were not so hyped about martial arts anymore, especially the second world war because that gave just destruction and and just most people wouldn't relate to samurai And so jigoro kano started to make it more ethical and kind of bring values into it and kind of bring a progression system To make it more accessible to people and to make it kind of a dough Which in japanese means the way kind of a practice versus a jutsu, which is means a technique So there was aiki jutsu Uh But then uh, morishio shiba went from aiki jutsu. He went to there was aiki budo, but then eventually there was aiki dough Which basically good. It's a it's a tough way to explain what aikido means the name And that's because aikido Japanese languages like that. It's it's kind of more intuitive or or there's more meanings to one word than one But some of the best ways to explain what he meant by So i it's three words i means unity or harmony or Or shiba like to say that stress sometimes that it was he would mean love By that by the word i think he decided that later because love actually the i has a different kanji from what I know But still unity love connection peace Then ki is either breathing or or kind of Universe or energy and dou is the way the path that you walk the discipline So if you unite all those words many people like to make different interpretations based on what's most comfortable for them But you know from what I learned about where shiba and his kind of the way his mind works Uh, I would guess that for him it meant more or less Now the way of unity With the universe or the way of love and unity With life kind of that that would be probably the best direction or some people say the art of peace And I think that's fair to say but you know, it's kind of a mix of all those terms But then coming back to his story. So I think he was already between that time establishing aikido as As as aikido he transitioned into his own martial art creating his own martial art and after Hiroshima Nagasaki he isolated himself he moved to iwama A village where I think he bought some land or was given some land and cut out some trees and built a dojo Where he kind of secluded himself and he devoted himself to perfecting the martial art of aikido And he would have uchi deshi living students who would travel to him and live with him and that dojo is actually still there. It's called the iwama dojo long story another video But uh, so he would be surrounded by students and they would work the farm and and train and he would travel and Teach seminars, but he would always come back there and uh from what I understand. He was basically just uh focusing a hundred percent on Creating this new form of a martial art which Uh, which was coming from the notion the understanding that martial arts are destructive and through Hiroshima Nagasaki the war in his life experience realized that destruction is not the way You know that it doesn't lead to real solution and that's when he started speaking a lot about kind of unity and harmony and And there's another significant moment in washiba's life, uh, which he spoke about as well where he apparently the story goes that he was facing a a challenge from like high-ranking army guy, I think who was a swordsman And the story goes that the swordsman was trying to attack more shiba with a sword and or shiba was just dating and he would see like Again, he would have that flow state. I believe like a death life situation and he had that flow state and he started avoiding all those the sword strikes and After he survived that that battle eventually, you know, the guy gave up He sat down by the by well and he kind of went into this unity state of kind of opening up And actually I have this whole video about that state and what I believe it actually means it's called in life And it's not what you think so check it out if you want to dig it down deeper into that subject but basically I or since he had that, uh experience of unity and In that flow state if you look at science It kind of makes sense because in that flow state when you're in that state of unity The brain part shuts down which which localizes you as an individual as a separate being It shuts down and then you feel like you're part of everything and people experience that it's not like an uncommon thing to experience and When many people associate that to be enlightenment But basically that's what happened to more here shiba and he perceived that he's one with everything and I think that drove him to understand the martial art of like, you know, even better that He would he actually started to perceive and that's what he would speak about often is that um Aikido or no, I said, you know, but that we are all We're all one kind of that zen saying that big zen state phrase that we're all united We're all connected that we're not separate and that means that we're all we are all one family and Basically when you look at it that way And there's actually a great story, but I'm seeing that you know this video is already getting into 20 minutes And I've spoken a lot about ostensia's history And what I think I'll do I'll just cut it make this episode into two parts And I'll focus this one on ostensia's history Uh, kind of giving a background of where Aikido came from in my understanding in my perception And then I'll dig into the main subject that I wanted to introduce in this episode I'll introduce the next one about You know the whole what what the essence of Aikido is and why I think it fails to deliver that It's a big subject and a worthy one to put attention in But to just summarize the the kind of journey of ostensia and Morhio Shiba So he understood that we are all Connected we're all one And and that obviously made him question basically like so how do you practice some martial art? Which is about destroying someone else killing someone else How do you practice it with that spiritual realization that we're all all one? And That would let him to create Aikido. He started developing in martial art, which he felt was Uh a peaceful way to end a conflict that it's it's redirecting energy and it's flowing It's kind of uniting energies and and his idea was that Aikido using Aikido you would defend yourself and defend others without hurting them Now that's where controversy hits and you know what? I think I'll just I got you probably intrigued But I'll stop the episode here. You got the background And I'll get into the controversy in the next one Sorry for leaving you hanging here, but let's do it this way Keep questioning. I'll continue the next one


Maksimulaikeuteistimation on yleensä käyttävä, että esim. mediaism-modellista. Yksi common modeling strategy on ensimmäinen esim. full-mediaism-modellista, niin katsotaan, jos se on dataa, jos se ei ole, sitten vaikuttaa parcellimiaism-modellista. Tämä strategia, jotenkin, on vähän asioita. Let's take a look at what the full-mediaism-modell actually tests. So this is from my model testing video, and what this model test does is not testing the absence of this path, rather what is tested is whether this model zxxy is adequate in explaining the correlation between z and y. There are of course a number of different alternative models that could be considered when this model is rejected, as it is in this example. This graphic is from Klein's article, and he lists a subset of the models that you can form using these three variables that are all just identified. So all these models fit the data well, and they could be perfectly, and they could be used as alternatives for the full-mediaism model that I just demonstrated. So because there are multiple different equivalent models that explain the data equally well, then the rejection of the full-mediaism model does not imply that the particular alternative should be accepted. So model acceptance choices should be made based on theory. However, the partial-mediaism model may not be the theoretically the most desirable model. Let's take a look at an example. So this example comes from Unsworth, who studied creative requirements and creativity in the context of a hospital. So creative requirements basically are how much creativity the task or the job of a person requires, and then they had some antecedence, and they built a theory that these are characteristics of leaders, and the work environment lead to creative requirement, which in turn influences individual-level creativity. So this is a full-mediaism model. This model did not fit the data, and then the researchers went for partial-mediaism model. However, that is not the only choice that they could have made. Another appealing alternative is to simply have these error terms to be correlated. So the full-mediaism model simply states that the full-mediaism relationship is not adequate for explaining the correlation between creativity and autonomy, and if we add this endogenous relationship here, then we can improve the model field. So which one is more theoretically appealing? Having these omitted causes of creativity and creative requirement to be correlated or having a partial-mediaism model. There are two good arguments for why we should allow these error terms to be correlated when we are doing these full-mediaism models. The argument number one is that M and Y are often conceptually related, and therefore they probably have a common cause. So if we think about creative requirement of a task or job, and then creativity of an individual, perhaps those are both related to the overall level of creativity required in the organization, and if the organization is something that works in an environment where creativity is emphasized, then that may be a cause for creative requirement for individual tasks or jobs, and that could also cause the organization to hire creative people. So there could be an omitted common cause because these are conceptually related. Another argument for including this correlation is that we don't know what the omitted causes of M and Y are, and thus we cannot justify the assumption that they are uncorrelated. And we cannot even in principle know what are all the causes of creativity. If we knew all the causes of creativity, then this study of whether creative requirement causes creativity would not even be needed. So if we don't know what these omitted causes are, then how could we possibly make or justify the assumption that they are uncorrelated. And this is particularly well made by this article by John Antonakis and co-authors, who state that in their opinion, in principle, this correlation should be always freed, unless there is a strong a prior reason for not doing so. And this is something that any researcher who does mediation models, particularly if the theory suggests the full mediation, should consider.


a simple linear regression model to the data and once the model has been fitted then we need to determine the goodness of the fit. So, and also we need to test the statistical significance of the regression coefficients. Well, so one way to do this one like we in the last lecture we have tested the hypothesis H naught which is beta 1 equal to 0 against the alternative hypothesis that that beta 1 is not equal to 0 and we have used the test statistics t to test this hypothesis. So, another way to approach this problem is the analysis of variance. So, today we will be basically talking about ANOVA. So, the content of lecture 4 is analysis of variance in abbreviation it is ANOVA and also we will be talking about the coefficient of determination. Well, so our model is y equal to beta naught plus beta 1 x plus epsilon. So, given a set of data say for example, x i y i for i equal to 1 to n we know how to fit a simple linear regression model to this data that is y hat equal to beta naught hat plus beta 1 hat x. And once the model has been constructed it is important to confirm the goodness of fit and that is statistical significance of the regression coefficients. So, we have tested the hypothesis H naught which is equal to beta 1 equal to 0 against the alternative hypothesis H 1 which says that beta 1 is not equal to 0. And in lecture 3 we have used the test statistic t which is equal to beta 1 hat by m s residual by s x x root over which follows t distribution with degree of freedom n minus 2 and this is under H naught. So, we have used this test statistic to test the hypothesis H naught and we reject H naught if this t value is greater than t alpha by 2 n minus 2 at the level of significance here is equal to alpha. So, now another approach to solve this problem is called ANOVA technique that is analysis of variance. So, here given the set of data x i y i. So, I am talking about ANOVA now the variation in response variable the total variation data. So, the variation in data I mean the variation in response variable which is equal to summation y i minus y bar square i equal to 1 to n. So, this y i minus y bar is basically the deviation of the i th observation from the total from the overall mean well. Now, the question is so this is the total variation in response variable. Now, how much of this variability is explained by the regressor variable and how much of this variation is left unexplained. Well, the question is how much of the variation is explained by the model model or the regressor variable. Now, consider the identity y i minus y i hat which is equal to y i minus y bar minus y i hat minus y bar. So, this one is basically the deviation of i th observation from its predicted value and this quantity is deviation of the i th observation from overall mean. So, this is the deviation of the i th observation from overall mean. Similarly, this quantity is you know this is the deviation of the i th predicted value from the overall mean. Now, this identity can be written as y i minus y bar which is equal to y i hat minus y bar plus y i minus y i hat. So, the basically the significance of this identity is that this is the deviation of the i th observation from overall mean. And this is the deviation of the i th observation i th fitted observation fitted value of the i th observation from overall mean and this is the residual basically this is e i. So, how much of the variation I mean I am talking about the i th observation. So, how much deviation of the i th observation from overall mean is explained by the model and this is the portion which is remain unexplained. Now, let me just draw a figure suppose given a set of observation x i y i I have the fitted model this is my fitted model and my i th observation is here this is my i th observation. So, basically this is x i and this height is y i this is y i this is y i hat because this point is basically x i y i hat and suppose the overall mean of the response variable or of the data y is y bar which is this well now you see that this is this distance is y i minus y bar. So, this is the deviation of the i th observation from the overall mean. Now, part of this deviation is explained by the regression model and this distance basically this distance is basically it is y i hat minus y bar and this portion is y i minus y i hat well. So, the total deviation is this much and part of this deviation is explained by the regression model and the remaining portion is the unexplained part. Now, if we if we square both sides both sides of this equation and sum from 1 to n then we get summation y i minus y bar whole square is equal to y i hat minus y bar plus y i minus y i hat from i equal to 1 to n i equal to 1 to n. So, this is basically the variation in the response variable or variation in the data. Now, we want to split this variation into several parts basically two parts the part which is which is explained by the regressor variable and the part of the variation which is not explained by the by the regressor variable. So, and we want to the part which is not explained by the regressor variable is is basically s s residual and we want to minimize the part we want to minimize s s residual. So, we want the model to be such that so that it can explained the variation in observation I mean most of the part is explained by the model that is what we want well. So, this is equal to summation y i hat minus y bar whole square plus summation y i minus y i hat whole square plus 2 times 1 to n 1 to n plus 2 times y i hat minus y bar into y i minus y bar right and I am going to prove that this cross product term is equal to 0 well. So, the cross product term t is equal to summation y i hat minus y bar. Now, you can check that y i hat minus y bar this is nothing, but beta 1 hat into x i minus x bar and similarly y i minus y i minus y i minus y i minus y hat is basically y i minus beta naught hat plus beta 1 hat x i. So, just replacing y i hat by the fitted value and now I replace beta naught that is basically y i minus y bar plus beta 1 hat x bar minus y i minus y i minus y i minus y i minus y i so I can write this is equal to x i minus x bar. So, if I now replace this 2 quantity here I equal to 1 to n. So, I will get sum over beta 1 hat x i minus x bar into y i minus 1 hat x i minus x bar into y i minus y bar. So, here it is minus beta 1 hat x i minus x bar. So, basically it is beta 1 hat s x y minus x i minus x bar into y i minus x bar beta 1 hat square s x x this is the notation for the summation which is equal to beta 1 hat s x y minus beta 1 hat s x x and this quantity is equal to 0 this is equal to 0 because we know that beta 1 hat is equal to s x y by s x x. So, what we proved is that the cross product term is equal to 0. So, we are left with then summation x i minus y i minus y bar whole square is equal to summation y i hat minus y bar whole square plus summation y i minus y i hat.  So, what we have is that s s total is equal to s s regression plus s s residual well. So, this is the splitting of total sum of square into into two parts the total variation in y is splitted into two parts the variation due to the regression and the variation residual sum of square that means the variation which is not been explained by the regressor variable. Well, now we have been proved that now what is s s residual s s sorry s s regression is equal to summation y i hat minus y bar whole square and this quantity is nothing, but just now we prove I mean we have proved that this is this quantity is equal to beta 1 hat x i minus x bar. So, square here square here summation y i minus y i minus y i minus y bar whole square and this is going to be beta 1 hat square s x x. So, s s residual sorry s s regression is this quantity. Now, s s residual which is equal to summation y i minus y i hat whole square 1 to n this is nothing, but the ith residual. So, I can write this one as summation e i square 1 to n and we have proved that this quantity is equal to minus t is I mean this follows chi square distribution with degree of freedom is not n it is the degree of freedom is n minus 2 because you know all the e i's they are not independent we know that the residuals they satisfy the constraint that summation e i is equal to 0 and the another constraint is summation e i x i is equal to 0. So, because of this due to this 2 constraint all the e i's are not independent you know out of n e i's you can choose n minus 2 e i's independently and the remaining 2 have to be chosen in such a way that they satisfy these 2 constraints. So, we are losing the 2 degree of freedom because of because of this 2 constraint because e i satisfies 2 constraint that is why s s residual here it follows chi square n minus 2 anyway I have proved this thing before also. Now, s s t sum of square due to total sum of square. So, s s t is equal to sum y i minus y bar whole square i equal to 1 2 n and this has this has degree of freedom n minus 1 because of the fact that you know you have y 1 minus y bar y 2 minus y bar y 2 minus y bar and y n minus y bar and this satisfy the condition that of course, it is always true that sum y i minus y bar is equal to 0 i equal to 1 2 n. So, for this reason you know out of n quantities n minus 1 can be chosen independently and the n th 1 has to be chosen in such a way that this constraint is satisfied. So, that is why total sum of square has n minus 1 degree of freedom and also you know we came to know that s s t is equal to s s regression plus s s residual the variation which has been explained by the model and this is the variation which has which is not explained by the regression variable. So, this has degree of freedom and also degree of freedom has the additive property. So, degree of freedom total is equal to degree of freedom of regression plus degree of freedom of residual. So, this quantity is equal to is n minus 1 and we know that s s residual has degree of freedom n minus 2 and then the degree of freedom of s s regression is equal to 1. Now, we will make the ANOVA table well source of variation degree of freedom sum of square well let me write here total sum of square and the source of variations are regression and the residual. So, this has degree of freedom 1 the residual has degree of freedom n minus 2 and this has degree of freedom n minus 1. This one is denoted by n minus 1 and we know what is this quantity this is denoted by s s regression this is called s s residual and this is called s s t. Now, m s mean square which is obtained by dividing the s s by degree of freedom. So, here it is m s regression is equal to s s regression by 1 and similarly m s residual is equal to s s residual by degree of freedom that is n minus 2 s. Now, we already know that expected value of m s regression is equal to sigma square this we have proved before and it can be proved that expected value of sorry this is m s residual m s residual it can be proved that m s regression is equal to sigma square plus beta 1 hat square s x x right and also we know that n minus 2 m s residual by sigma square this follows chi square with degree of freedom n minus 2 and it can be proved that m s regression by sigma square this follows chi square with degree of freedom n minus 2 and it can be proved that m s regression by sigma square this follows chi square with degree of freedom 1 that is under h naught that is beta 1 equal to 0 and these two quantities are these two these are basically this is a function of random variables y i y. So, and they are independent. Now, a statistical theorem we have seen we have theorem says that let x follows chi square m and y follows chi square n and they are independent then x by m by y by n this follows f by n this follows f by n this follows with degree of freedom m and n this quantity is denoted by f this is basically the ratio of two chi squares they follow f distribution. So, from there from this theorem we can say that we can define now for one f for our ANOVA table that f is equal to m s regression by m s residual this follows f with degree of freedom 1 n minus 2 and obviously, looking at these two expected values. So, what we are going to do is that in the ANOVA table next we are going to compute f with degree of freedom 1 n minus 2 and obviously, looking at these two expected values. So, what we are going to do is that in the ANOVA table next we are going to compute f this f is equal to m s regression by m s residual and looking at their expected value it is intuitively clear that in the ANOVA table next we are if f is large then it is likely that this beta 1 is not equal to 0 if beta 1 is equal to 0 then this ratio is going to be close to close to 1. So, from there we can say that to test the hypothesis H naught beta 1 equal to 0 we compute f and reject H naught if f is greater than f alpha with degree of freedom 1 n minus 2. So, this is another way to another approach to test the hypothesis beta 1 equal to 0 I mean the test the same test we can do using the T distribution also basically those two are same I am going to prove that one first let me give one example for this ANOVA table well I am going to consider the same example cost on advertisement that is x i and this is the sales amount y i and we have the data 1, 1, 2, 1, 3, 2, 4, 2, 5, 4 and we know that the fitted model is y i hat is x i and x i equal to minus 0.1 plus 0.7 x i and from here we can you know before also we have computed e i's and we know that SS residual for this problem is for this data is equal to 1.1 and what we need to compute is that we need to compute what is the total variation in the data that is s s t which is equal to summation y i minus y bar whole square. You can check that your y bar is equal to 5 here and what is the total variation in the data that it is not difficult to check that this is equal to 6 and also we know that s s regression which is equal to beta 1 hat square s x x we know that beta 1 is 0.7. So, this is equal to 0.7 whole square and one can check that s x x is basically equal to 10. So, this quantity is equal to 4.9 and here is my ANOVA table for this problem ANOVA the source of variation this is regression residual total degree of freedom degree of freedom for this one is equal to 1. Well the total degree of freedom here is n minus 1 and n is equal to 5. So, total degree of freedom is 4 and the degree of freedom residual is n minus 2 that is equal to 3 and hence the degree of freedom for regression is equal to 1 and the s s values are 4.9, 1.1 and the total variation is equal to 6. So, here you can see that for this problem the fitted model is really good because the total variation in y is 6 and most of the part of this variation has been explained by the regression. So, out of 6 4.9 has been this is the part of the variation which has been explained by the regression model. So, most of the part has been explained by the regression model and the portion which is not explained by the regression model is 1.1 well. So, the f value here is equal to 4.9 sorry sorry first we have to we need to compute m s value the m s value is s s by degree of freedom.  So, 4.9 by 0.3 is equal to 0.367 which is going to be 13.6 and now you you know this f follows this f here that follows f distribution with degree of freedom 1, 3 and you find the value of f 0.05, 1, 2 and 3 which is going to be equal to 10 point. So, you can check this value from the statistical table now you check you can you can see that our computed f value which is 13.6 is larger than the tabulated value. So, we can conclude that which I mean this computed value is is larger than f 0.05, 1 with degree of freedom 1 and 3. So, we can conclude that we can reject H naught is rejected at the level of significance of this test is equal to alpha is equal to 0.05. So, basically we we have got the same value same result using using the t test. Now, I am going to prove that these two tests are basically you know these two whether you are using f test or t test it does not matter in the case of simple linear regression basically these two tests are the same.  So, f is nothing but t square I mean t square value well well. So, to test this hypothesis beta 1 is equal to 0 against the alternative hypothesis beta 1 not equal to 0 either you can go for the t test which says that t is equal to beta 1 hat square and t is equal to 0. Sorry beta 1 hat by m s residual by s x x this is the t statistic to test this hypothesis. Now, you compute t square which is going to be beta 1 hat square into t square by m s into s x x by m s residual right and and this quantity is well. So, this quantity is nothing but m s regression and the denominator is m s residual which is nothing but the f test so the value of the f distribution with a degree of freedom 1 n minus 2 is same as the value of the t distribution with degree n minus 2. Now, just for we can we can check this one in our previous example what we got is that for testing this hypothesis we got f equal to 13.61. Now, if you go for the t statistic to test this hypothesis we will have this is beta 1 is equal to beta 1 hat is equal to 0.07 and m s residual is 0.367 by s x x is equal to 10 and this is going to be equal to 3.655 and you can check that beta 1 hat is equal you can check that this 3 I mean the t square which is basically equal to 3.655 is is equal to equal to 13.61 which is equal to f. So, whether you use the t statistic to test this hypothesis or the f ANOVA approach that is the f statistic to test this hypothesis they are basically the same and basically the same for simple linear regression model, but once we will be talking about the multiple linear regression then we need to follow the ANOVA approach only. So, let the next I will I will be talking about the coefficient of determination well. So, what is this is that this is denoted by the n minus 2. So, n minus 2 is equal to denoted by is this is defined by defined as r square which is basically the ratio of s s regression by s s total well you know there are several approach to evaluate the performance of fitted model. So, this is one parameter which can be which is used to evaluate the performance of the fitted model here this quantity is nothing, but 1 minus s s residual by s s t.  So, that is why and obviously the range for r square is going to be from 0 to 1 it can be at most 1 if the s s residual is equal to 0. So, this r square it is basically determines that the proportion of variability that has been explained by the by the regression model because r square is equal to s s regression by s s total. So, this ratio will give you the proportion of variability that has been you know explained by the regression model well let me just give this is a very important parameter when r square is going to be equal to 1. So, r square is going to be equal to 1 if s s if s s residual is equal to 0. So, s s residual is equal to 0 and this will happen if the fitted model explained by the regression this will happen if the fitted model model explain all the variability in y. That means there is no part which remain unexplained by the model and the example of this one is this is the case basically suppose you have the data like this then your fitted model is going to be this. So, here r square is going to be equal to 1 and in this case it is intuitively clear that s s residual is going to be equal to 0 well if suppose in some example r square is equal to 0.8 for a maybe this is the case. These are the three data point and you have fitted this model and intuitively you know this is the r square is going to be very high and what we say here is that what is the meaning of r square is equal to 0.8 is that approximately 80 percent of the total variability in y is y that has been explained by the regression model and the remaining 20 percent of the variability in y remains unexplained by the model. So, the higher the value of the regress r square value the better the model is. So, that is all for today and next class we will be talking about talking more about r square. Thank you very much.