Thanks in a million! Very well explained. This is the nth time that I am watching this again. Great content. Awesome. I couldn't find this explanation--simply put anywhere else. “Great teachers are hard to find”. Grade: A++ 💥
Very nice video. I would love to get more insight about the explanations on "why is it so" and no just what to apply. I'm reading more theoretical material but I'm still trying to connect the dots.
I think there is small mistake on the slide. SSE(yellow) is actually distance from the actual point to regression line, and SSR(green) is supposed to be from mean line to regression line.
Hello, your video is very useful. I have a doubt when 0 or value less than cero appears in the confidence interval, You mention that there is no linear relationship between x and y values. If this happens can a quadratic or cubic model be given? or what could be the model? Please, woul you explain me. Thanks.
Valuable video!! Can you please explain how the regression results in excel can be used to tell If the coefficient sufficiently different from zero or it is sufficiently different from one
correct me if I'm wrong but I'm a bit confused here. Doesn't the rule say that if the t-statistic or the calculated value is more than the critical value, we reject the null hypothesis? Then how are we passing the test here? According to the curve, the t value should lie between -2.228
Null hypothesis means "m" is = 0 so y would become y=b which means x is not related to y. We don't want that...it would mean no relationship between x and y, thus we reject this and accept alternative... meaning m different from zero...thus there is a relationship between y and x...that would be y =mx+b
Really informative slides thank you, what would have helped is at the end if you slowed down and went into a bit more detail as to what exactly each of the tests were used for and what they meant during our conclusion, this is what usually comes up in exams. Great work nonetheless!
Here's the question: IS THE ANSWER E?) Which of the following tells us how strong the relationship is between two variables? a) the slope of a line b) the intercept of a line c) the coefficient of determination d) the coefficient of correlation e) both C and D are correct
calculate critical and" f " statistic value considering the following information : Significance level 0.05 Numerator 11. denominator 3. Total sum of Square 160. Treatment sum of square 60. Observation number 25. treatment number 5. By solving this someone help me.