1. Introduction to Statistics for the Social Sciences SBS200, COMM200, GEOG200, PA200, POL200, or SOC200 Lecture Section 001, Spring 2016 Room 150 Harvill Building 9:00 - 9:50 Mondays, Wednesdays & Fridays
Welcome

3. Schedule of readings Study guide for Exam 4 is online
Before our fourth and final exam (May 2nd)
OpenStax
Chapters 1 – 13 (Chapter 12 is emphasized)
Plous
Chapter 17: Social Influences
Chapter 18: Group Judgments and Decisions

4. Homework
On class website:
Please complete homework worksheet #25
Regressions Worksheet
Due: Monday, April 25th
No class on
Friday April 22nd

5. By the end of lecture today 4/20/16
Simple and Multiple Regression
Using correlation for predictions
r versus r2
Regression uses the predictor variable (independent) to make predictions about the predicted variable (dependent) Coefficient of correlation is name for “r” Coefficient of determination is name for “r2” (remember it is always positive – no direction info) Standard error of the estimate is our measure of the variability of the dots around the regression line (average deviation of each data point from the regression line – like standard deviation)
Coefficient of regression will “b” for each variable (like slope)

7. Sample memorandum and general instructions for Project 4 are both online

8. Sample memorandum and general instructions for Project 4 are both online

9. Sample memorandum and general instructions for Project 4 are both online

10. Starting next week there will be no more
Lab sessions
Starting next week there will be no more
labs this semester

11. Some useful terms
Regression uses the predictor variable (independent) to make predictions about the predicted variable (dependent)
Coefficient of correlation is name for “r”
Coefficient of determination is name for “r2” (remember it is always positive – no direction info)
Standard error of the estimate is our measure of the variability of the dots around the regression line (average deviation of each data point from the regression line – like standard deviation)

12. Describe relationship Regression line (and equation) r = 0.71
Rory’s Regression: Predicting sales from number of visits (sales calls)
Describe relationship
Regression line (and equation)
r = 0.71
Correlation: This is a strong positive correlation. Sales tend to increase as sales calls increase
Predict using regression line
(and regression equation)
b = (slope)
Slope: as sales calls increase by 1, sales should increase by
Dependent
Variable
Intercept: suggests that we can assume each salesperson will sell at least systems
a = (intercept)
Independent
Variable
Review

13. Review 50% is explained so the other 50% has yet to be explained
(0.71 > 0.632)
Review

14. Summary
Intercept: suggests that we can assume each salesperson will sell at least systems
Slope: as sales calls increase by one, more systems should be sold
Review

15. Pop Quiz – First 5 Questions
1. What is regression used for?
Include and example
2. What is a residual? How would you find it?
3. What is Standard Error of the Estimate (How is it related to residuals?)
4. Give one fact about r2
5. How is regression line like a mean?

16. Writing Assignment - 5 Solutions
1. What is regression used for?
Include and example
Regressions are used to take advantage of relationships
between variables described in correlations. We choose a value
on the independent variable (on x axis) to predict values for
the dependent variable (on y axis).

17. Writing Assignment - 5 solutions
2. What is a residual? How would you find it?
Residuals are the difference between our predicted y (y’)
and the actual y data points. Once we choose a value on our
independent variable and predict a value for our dependent
variable, we look to see how close our prediction was. We
are measuring how “wrong” we were, or the amount of “error”
for that guess.
Y – Y’

18. Writing Assignment - 5 solutions
3. What is Standard Error of the Estimate (How is it related to residuals?)
The average length of the residuals
The average error of our guess
The average length of the green lines
The standard deviation of the regression line

19. Writing Assignment - 5 solutions
4. Give one fact about r2
It is called a coefficient of determination
It is the square of the value for r
It is the proportion of variance of the dependent
variable that is accounted for by its relationship
with the independent variable
5. How is regression line like a mean?
The regression line attempts to get as
close as possible to the average of the
Y values for any particular x score

20. Thank you!
See you next time!!