Teward Huang Faculty Manager Gu Wk 7 Relationship
Relationship of Height and Weight
Each week, you will be asked to respond to the prompt or prompts in the discussion forum. Your initial post should be 75-150 words in length, and is due on Sunday. By Tuesday, you should respond to two additional posts from your peers.
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Week 7 discussion
I had to send a Word document of my discussion this week. its attached at the bottom.
Week 7 Discussion.docx (13.484 KB)
teward Huang Professors resonse don not respond
RE: Week 7 discussion
Correct. Yes, based on the chapter we learned how regression analysis can be used to determine how a dependent variable (y) is related to an independent variable (x). In simple linear regression, the regression model is y = β0 + β1x + ϵ, which related to the simple linear regression equation and sample data along with the least squares method is used to develop the estimated simple linear regression equation y ̂ = b0 + b1x, where b0 and b1 are sample statistics used to estimate the population parameters β0 and β1.
In this discussion example, the intercept is -207.7 and the height is 5.25 so the formula
Weight= -207.7 + 5.25 Height
Week 7 Discussion- Relationship of Height and Weight
When we say that there is a relationship between two variables then it’s mean that when one is changing (increasing or decreasing), then another variable is also changing by the change of the first variable.
The relationship might be positive or negative. In positive relationships, if one variable is increasing, then other is also increasing and vice versa.
We have the equation
Y= 5.2536x -207.75
Y = 133.734
Y= 5.2536(100) – 207.75
Since the information of the stature of the individuals is somewhere in the range of 60 and 80 so 100 inches is not in the regression. Yet, as we probably are aware of R^2=0.5129*100 = 51.29% which implies the percent of variety of y that clarifies for the lineal model. We can discover that it isn’t very exact, we generally will encounter an error.
RE: Week 7 Discussion- Relationship of Height and Weight
Sounds good. The simple linear regression formula for the Height/weight data is y= 5.2536(x) – 207.75. To compute the estimated weight for a person who is 65 inches tall and a person who is 100 inches tall, you should substitute these values for x. The equations look like the following. Estimate weight for 65 inches = y(weight) = 5.2536 (65) – 207.75. The estimated weight is 133.7 lbs. Estimated weight for 100 inches = y(weight) = 5.2536 (100) – 207.75. The estimated weight is 317.7 lbs.