chapter 7

Question 1

These two characteristics are the
basis for an equation for a straight
line

Answer 1

Slope and Intercept

Question 2

With a linear regression, we are trying
to _________ ___ based on values of
___.

Answer 2

Predict Y based on values of X

Question 3

The differences between the observed and
predicted values in a regression represent:
______.

Answer 3

Error

Question 4

The sum of the prediction errors (Σ (Y - Y’)) always equals ___.

Answer 4

zero

Question 5

Name the components of:

Y’ = bᵧX + aᵧ

Y’ refers to:

Answer 5

The estimated value of Y

Question 6

Name the components of:

Y’ = bᵧX + aᵧ

bᵧ refers to:

Answer 6

the slope of the line of best fit

Question 7

Name the components of:

Y’ = bᵧX + aᵧ

X refers to:

Answer 7

the value of X for predicting Y

Question 8

Name the components of:

Y’ = bᵧX + aᵧ

aᵧ refers to:

Answer 8

the Y axis intercept

Question 9

Given the following set of X, we should not try to predict Y when X > ?

X = [2, 2.5, 2.8, 3.0, 3.2, 3.5, 4.0, 4.2, 4.4, 4.9, 5.0]

Answer 9

The highest value of X (5.0)

Question 10

This statistic is much like the standard deviation and is used to quantify prediction errors. This is the ________________

Answer 10

Standard error of estimate

Question 11

Approximately _____ percent of the observations will fall within one standard error of the estimate

Answer 11

68

Question 12

The standard error of estimate tells us ___

Answer 12

how far away, on average, a point will be from the regression line

Question 13

The lower the standard error of estimate…

Answer 13

the more confident you can be

Question 14

Regression =

Answer 14

progression