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Simple Linear Regression. Deterministic Relationship If the value of y (dependent) is completely determined by the value of x (Independent variable) (Like.

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Presentation on theme: "Simple Linear Regression. Deterministic Relationship If the value of y (dependent) is completely determined by the value of x (Independent variable) (Like."— Presentation transcript:

1 Simple Linear Regression

2 Deterministic Relationship If the value of y (dependent) is completely determined by the value of x (Independent variable) (Like an equation in the form y = 2x + 10, or f(x) = 5x-1) However, in most situations, the variables of interest are not deterministically related! For example, the value of y = 1 st year college GPA is certainly not determined solely by x = high school GPA.

3 Probabilistic Model

4 Let x * denote the value of x…. Without the random deviation e, all observed (x, y) points would fall exactly on the population regression line. The inclusion of e in the model equation recognizes that points will deviate from the line.

5 Simple Linear Regression Model:

6 Slope Population Regression Line

7 Summary

8 X * denotes a specified value of the predictor variable x …. So has 2 different interpretations  It is a point estimate of the true mean y value when x = x *.  It is a point predictor of an individual y value that would be observed when x = x *.

9 Find the point estimate of the mean y-value for the following: Age (x)15171815161917161820 Weight (y)2289339332712648289733272970253531383573 So what’s the point estimate for an 18 year old mom?

10 Point estimate and point prediction are identical – only the interpretation is different. Prediction – weight of single baby who mom is 18 Estimate – average weight of all babies born to 18 year- olds

11 Answer the following: Explain the slope in context of the problem Explain the y-intercept in context of the problem.

12 Find SS Resid. On calculator – every time you calculate a linear regression – it calculates the residuals. Put them in list 3 and square them & add the list.

13 It represents the typical deviation in the y-variable from the least squares line.

14 Find the residual for a mother who is 19.

15 Find the probability that a 19 year old mother has a baby that is more than 3000 g.

16 Coefficient of determination (r 2 ) It’s the amount of variation in the y-variables that can be explained by the least squares line.

17 Homework Worksheet


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