Question

Question 1

A residual is:

choose one

• The difference between a data point and the regression line.

• A value that can be 1 or zero.

• A value that is always negative because it is a difference

• The difference between two different lines.

Question 2

The correlation coefficient:

choose one

• Is a number with a range from -1 to 1

• If there is no correlation, the coefficient is negative

• If the correlation coefficient is negative, it indicates a strong positive relationship between x and y

• All of the above

Question 3

The assumptions we use to determine the validity of predictions include:

choose one

• For every specific value of y, the value of x must be normally distributed about the regression line.

• The sample was collected carefully

• The standard deviation of each dependent variable must be the same for each independent variable

• All of the above

Question 4

A positive straight line relationship:

choose one

• Show no change in the variables

• Show that both variables increase in value

• Shows that as the values of x increases, the values of y decreases

• Slopes down

Question 5

Because some people are unable to stand to have their height measured, doctors use the height from the floor to the knee to approximate their patients’ height (in cm).

Height of Knee	Overall Height
57	192
47	153
43	146
44	160
55	171
54	176

a. Use Excel to determine the correlation coefficient of this data

b. Use Excel to determine the regression equation of this data

c. Find the overall height from a knee height of 45.3 cm

d. Find the overall height from a knee height of 52.7 cm

Choose one

• a. r = 0.73220213

  b. Equation: y = 2.0217x + 67.746

  c. 159.32901

  d. 174.28959

• a. r = 0.82544241

  b. Equation: y = 2.5109x + 40.79

  c. 154.53377

  d. 173.11443

• a. r = 0.53611996

  b. Equation: y = 2.0217x + 67.746

  c. 159.32901

  d. 174.28959

• a. r = 0.908553861

  b. Equation: y = 2.5109x + 40.79

  c. 154.53377

  d. 173.11443

Question 6

The coefficient of determination:

Choose one

• Represents the percentage of the data that can be explained by the correlation

• Is equal to the ratio of the explained variation to the total variation

• Is calculated by squaring the correlation coefficient.

• All of the above

Question 7

A simple regression model uses a straight line to make predictions about future events.

Choose one

• True

• False

Question 8

Once we have a simple regression line, we can use it to predict values for the independent variable X and the dependent variable Y.

Choose one

• True

• False

Question 9

The independent variable is represented by a y.

Choose one

• True

• False

Question 10

Outliers:

Choose one

• Greatly affect the value of r

• Should be identified and taken out of the data before any correlation analysis

• Are easily identified in a scatterplot

• All of the above

Answer 1

1)A residual is: the difffdiffe between a datapoint and the regression line.

2) The correlation coefficient is: A number with a range from -1 to 1

3)The assumption we use to determine the validity of predictions include: For every specific value of y, the value of x must be normally distributed about the regression line.

4) A positive straight line relationship : shows that both variables increase in value .

5)a) correlation coefficient, r = 0.90853861

b) regression equation , y= 2.5109x + 40.79

c) 154.53377

d) 173.1143

6)The coefficient of determination : is calculated by squaring the correlation.

7)A simple regression model uses a straight line to make predictions about the future events. True

8) once we have a simple regression line,we can use it to predict values for the independent variable X and the dependent variable Y. True

9)The independent variable represented by Y. False ( it is represented by X)

10) Outliers: All of the above.