Lecture 7 Chapter 8

Question 1

What does the correlation coefficients tell us?

Answer 1

Tell us about the strength and direction of the linear relationship between 2 variables.

Question 2

What is the range for correlation coefficients?

Answer 2

Can range from -1.00 to +1.00

Question 3

What range has a strong relationship
close to -1or+1
or closer to 0

Answer 3

close to -1or+1

Question 4

what is a ‘perfect’ linear relationship?

Answer 4

When one variable changes by one unit, so does the other.

Question 5

Does effect size translate into an actual clinical or practical significance?

Answer 5

no

Question 6

What is the definition of regression analysis?

Answer 6

Used for predicting dependent variables from other independent variables. We wouldn’t want to try to predict a variable from another if the variables weren’t related/correlated. Correlation and regression analysis thus go hand in hand.

Question 7

what is a simple linear regression?

Answer 7

Simple linear regression tries to predict one dependent variable from one independent variable using the formula for one of the lines of best fit through a scatterplot of the variables.
DV must be scale (continuous) level of measurement.

Question 8

What measurement does the DV have to be for a simple linear regression?

Answer 8

DV must be scale (continuous) level of measurement.

Question 9

what is multiple linear regression?

Answer 9

Multiple linear regression tries to predict one dependent variable from two or more independent variables using the formula for one of the lines of best fit through a multi-dimensional scatterplot of all the variables.

Question 10

What measurement does the DV have to be for a multiple linear regression?

Answer 10

DV must be scale (continuous) level of measurement.

Question 11

For a simple linear regression, what is the formula name that is used?

Answer 11

Line of best fit

Question 12

What is the regression equation?

Answer 12

Ŷ = bX + a

Question 13

In the regression equation, what is the Ŷ?

Answer 13

Ŷ = variable being predicted (the DV)

Question 14

In the regression equation, what is the X?

Answer 14

X = variable being used to make the prediction (the IV)

Question 15

In the regression equation, what is the b?

Answer 15

b = the ‘slope” of the line, or how ‘steep’ it is (rise over run; change in Y per unit change in X). It is the ‘regression coefficient’

Question 16

In the regression equation, what is the a?

Answer 16

a = a constant; the “Y intercept”; the value of Y when X is zero

Question 17

What is the symbol for the correlation coefficient?

Answer 17

R

Question 18

What does the correlation coefficient tell us?

Answer 18

The strength of the relationship between the DV (variable being predicted and the IV

Question 19

The strength of the relationship between the DV (variable being predicted and the IV is called?

Answer 19

Correlation coefficient

Question 20

correlation coefficient also tells us our?

Answer 20

effect size

Question 21

what does the Adjusted R Square tell us?

Answer 21

% of the variance in the DV can be explained by the IV

Question 22

what is the binary logistic and multinomial logistic regression used for?

Answer 22

predicting categorical DV

Question 23

What is another name for multiple linear regression?

Answer 23

multiple regression

Question 24

Multiple linear regression has # iv’s # dv’s?

Answer 24

One scale DV and two or more Iv’s

Question 25

A binary or bivariate Logistic regression is similar to simple linear regression except that it is used when the outcome (DV) is_______?

Answer 25

Dichotomous

Question 26

Multinomial (Polychotomous) logistic regression is used when the outcome (DV) has more than _________

Answer 26

2 categories so it is nominal

Question 27

Bivariate Regression (Simple Linear Regression) is for predicting 1 ________ dependent variable from 1 other independent variable

Answer 27

Scale

Question 28

Multiple Linear Regression is for predicting 1 Scale/Normal dependent variable from __________ IVs

Answer 28

2+ IVs

Question 29

Binary Logistic Regression is for predicting 1 _________ dependent variable from 2 or more other IVs

Answer 29

dichotomous

Question 30

Y axis the IV or DV?

Answer 30

DV and prediction

Question 31

X axis is the IV or DV?

Answer 31

X is the IV or IV’s