Chapter 13

Question 1

A group of techniques to measure the relationship between two variables

Answer 1

Correlation analysis

Question 2

The variable that is being predicted or estimated

Answer 2

dependent variable

Question 3

The dependent variable is measured on which axis

Answer 3

Y-axis

Question 4

A measure of strength of the linear relationship between two variables of interval or ratio scale

Answer 4

Correlation coefficient

Question 5

6 characteristics of a correlation coefficient

Answer 5

1. Designated with letter r
2. Between -1 and 1
3. Shows direction and strength of linear relationship between two variables
4. Closer to 0 means less of a correlation
5. Near 1 shows strong correlation
6. near -1 shows strong correlation

Question 6

an equation that expresses the linear relationship between two variables

Answer 6

Regression equation

Question 7

A mathematical procedure that uses the data to position a line with the objective of minimizing the sum of the squares of the vertical distances between the actual y-values and the predicted values of y.

Answer 7

Least squares principle

Question 8

What is the symbol y hat

Answer 8

The estimated y value for a given x

Question 9

What is the y hat formula for linear regression equation

Answer 9

y hat = a+bx

Question 10

The difference between the actual y values and the predicted y values, known as the error values

Answer 10

Residuals

Question 11

A measure of dispersion, or scatter, of the observed values around the line of regression for a given value of x

Answer 11

Standard error of estimate

Question 12

What does a small standard error mean

Answer 12

The data is close to the regression line
Predicted Y will have small error

Question 13

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

Answer 13

The coefficient of determination

Question 14

Assumptions for linear regression

Answer 14

1. Corresponding y values are normally distributed
2. The means of the distributions lie on the regression line
3. The standard deviations are the same.
4. Y values are statistically independent

Question 15

If the standard error of estimate is large, what would you expect for the coefficient of determination

Answer 15

It would be small

Question 16

Is used when the regression equation is used to predict the mean value of Y for a given value of X

Answer 16

Confidence interval

Question 17

Is used when the regression equation is used to predict an individual y for a given value of x

Answer 17

Prediction interval