17 Questions | Attempts: 143  Settings  • 1.
Load Data Set 111 I run a linear regression and find the equation for the line, then use it to predict the value for y when x = 12. Which of the following features would be a concern in terms of accuracy?
• A.

Least squares regression line

• B.

Extrapolation

• C.

Interpolation

• D.

Y squared transformation

• E.

X squared transformation

• F.

Pattern in the residual plot

• 2.
I have the equation for the best transformation for a set of data : y = 27 - 3.4 * log(x) To predict the value of y when x = 12, which App should I use?
• 3.
Load Data Set 111 What is the equation for the least squares linear regression? (2 decimal places, no spaces)
• 4.
Load Data Set 111 Which quadrant does the shape of the data fit?
• 5.
Load Data Set 111 Which transformations apply to this data set?
• A.

X squared

• B.

Y squared

• C.

Log x

• D.

Log y

• E.

1/x

• F.

1/y

• 6.
Load Data Set 111 I run a linear regression and find the equation for the line, then use it to predict the value for y when x = 12. Which of the following features would be a concern in terms of accuracy?
• A.

Least squares regression line

• B.

Extrapolation

• C.

Interpolation

• D.

Y squared transformation

• E.

X squared transformation

• F.

Pattern in the residual plot

• 7.
The accuracy of any prediction using least squares regression, including transformations, is dependent on :
• A.

The regression line or transformation being linear

• B.

Residual plot being random

• C.

High r value

• D.

Interpolation

• E.

Extrapolation

• F.

Positive correlation coefficient

• G.

Scatter plot being random

• 8.
The two main ways to indicate a predictions from a linear regression line or transformation will be accurate are:
• A.

Extrapolation and linearity

• B.

Interpolation and extrapolation

• C.

Linearity and residual plot being random

• D.

Interpolation and linearity

• E.

Residual plot being random and extrapolation

• F.

Interpolation and positive correlation coefficient

• 9.
In any linear regression equation, the value of b represents
• A.

The strength of the relationship

• B.

The rate of change in the relationship

• C.

The y intercept

• D.

The spread of the residual plot

• E.

• F.

The planet of the transformation

• 10.
In any linear regression equation, the value of a represents
• A.

The strength of the relationship

• B.

The rate of change in the relationship

• C.

The y intercept

• D.

The spread of the residual plot

• E.

• F.

The planet of the transformation

• 11.
Enter Data Set 111 Using the equation of the regression line to two decimal places, what is the value of y when x is 3.5?
• 12.
Enter Data Set 111 The data represents the migration of birds over the winter. The y values show the number of birds nesting in a cave. The x values indicate the number of weeks into winter the sample was taken. birds in cave = 62.43 - 8.14 * weeks into winter What is the prediction for the 10th week.
• 13.
Enter Data Set 131 The data represents the sales of properties in a housing development by JCon Developers. Properties are developed and sold in stages of 10 houses. JCon decide to promote the properties for a month before putting them on sale. After the extensive advertising blitz for a month, JCon Developers have a total of 70 properties. The x values represent the number of months since the start of the advertising blitz. The y values represent the number of houses remaining. number of house remaining = 67.62 - 63.37 * log(months since advertising blitz) How many months will it take to sell out the development?
• 14.
Enter Data Set 131 The data represents the sales of properties in a housing development by JCon Developers. Properties are developed and sold in stages of 10 houses. JCon decide to promote the properties for a month before putting them on sale. After the extensive advertising blitz for a month, JCon Developers have a total of 70 properties. The x values represent the number of months since the start of the advertising blitz. The y values represent the number of houses remaining. number of house remaining = 67.62 - 63.37 * log(months since advertising blitz) How many houses would remain to be sold four months after the advertising blitz?
• 15.
Enter Data Set 131 The data represents the sales of properties in a housing development by JCon Constructions. Properties are developed and sold in stages of 10 houses, with seven stages planned. JCon decide to promote the properties for a month before putting them on sale. After the extensive advertising blitz for a month, JCon Developers have a total of 70 properties. The x values represent the number of months since the start of the advertising blitz. The y values represent the number of houses remaining. number of house remaining = 67.62 - 63.37 * log(months since advertising blitz) Using the transformation equation, predict how many houses have been sold 6 months after the advertising blitz? Back to top