Lecture 17

Question 1

What do statistical procedures look at between two samples?

Answer 1

The relationships rather than differences between 2 ratio-interval scale variables

Question 2

Purpose of simple linear regression?

Answer 2

Looking for a causal relationship between two variables where one affects the other

Question 3

What is the purpose of a simple linear correlation?

Answer 3

Used when looking for a relationship between two ratio-interval scale variables where no causal relationship is implied

Question 4

How is the change in the dependent variable assessed for a given change in the independent variable?

Answer 4

Find the equation for slope that relates to our variables (x,y)

Question 5

How is the strength of the relationship determined between two variables?

Answer 5

Test with normal hypothesis techniques

Question 6

In the simple linear equation, what is alpha?

Answer 6

The population y-intercept

Question 7

In the simple linear regression equation, what is ß?

Answer 7

The population slope

Question 8

In the simple linear regression line, what is E?

Answer 8

The residual value

Question 9

What is residual?

Answer 9

Between the expected Y and the actual Y; comparable to error in ANOVA

Question 10

Where is the best-fit line used in?

Answer 10

Sample statistics = no greek letters

Question 11

Why is there no residual component to the best-fit line?

Answer 11

Each data point is expected to fall directly on the line

Question 12

How is the best-fit line determined?

Answer 12

Using the least squares method

Question 13

What is the least squares method?

Answer 13

The residuals are squared and then summed

Question 14

What are the sources of variation in simple linear regression?

Answer 14

Total, regression, and residual

Question 15

In simple linear regression, what is the total variation?

Answer 15

All the variation in the Y-variable

Question 16

In simple linear regression, what is the regression variation?

Answer 16

(Relationship) the variation in Y that is due to its relationship with X; the most of interest we are looking at

Question 17

In simple linear regression, what is the variation in residuals?

Answer 17

The variation in Y due to all other things other than its relationship with X

Question 18

What is conclusive if the regression line perfectly fit the data (all data points fell on the line)?

Answer 18

No residual deviations = regression explains all of the total variation in the dependent variable Y

Question 19

What is conclusive if the data points were spread very widely?

Answer 19

The regression line will not fit the data therefore residual deviations would account for more of the variation in the Y variable

Question 20

What does the hypothesis test for a simple linear regression?

Answer 20

Tests for a significant relationship between the two variables

Question 21

What is the coefficient of determination? (r^2)

Answer 21

The proportion of the total variation in the dependent variable Y that is explained by the regression

Question 22

What does regression mean?

Answer 22

The relationship to the independent variable X

Question 23

What does a an r^2 value closer to 1 indicate?

Answer 23

A closer relationship

Question 24

What is the standard error of the estimate? (Syx)

Answer 24

The standard deviation of the Y values about the regression line, Syx = 0 = perfect relationship

Question 25

What do smaller values of the standard error of the estimate represent?

Answer 25

A better fit to the line

Question 26

What is the established relationship between X and Y used to predict?

Answer 26

The unknown values of Y using known values of X

Question 27

When the relationship between X and Y is established, making predictions for Y is valid as long as?

Answer 27

X stays within the range that was used to establish the regression equation