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SCENARIO 13-11
a Computer Software Developer Would Like to Use H0:b1=0H _ { 0 } : b _ { 1 } = 0

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SCENARIO 13-11
A computer software developer would like to use the number of downloads (in thousands) for the trial
version of his new shareware to predict the amount of revenue (in thousands of dollars) he can make
on the full version of the new shareware. Following is the output from a simple linear regression
along with the residual plot and normal probability plot obtained from a data set of 30 different
sharewares that he has developed:  SCENARIO 13-11 A computer software developer would like to use the number of downloads (in thousands) for the trial version of his new shareware to predict the amount of revenue (in thousands of dollars) he can make on the full version of the new shareware. Following is the output from a simple linear regression along with the residual plot and normal probability plot obtained from a data set of 30 different sharewares that he has developed:       -Referring to Scenario 13-11, which of the following is the correct null hypothesis for testing whether there is a linear relationship between revenue and the number of downloads? a)  H _ { 0 } : b _ { 1 } = 0  b)  H _ { 0 } : b _ { 1 } \neq 0  c)  H _ { 0 } : \beta _ { 1 } = 0  d)  H _ { 0 } : \beta _ { 1 } \neq 0  SCENARIO 13-11 A computer software developer would like to use the number of downloads (in thousands) for the trial version of his new shareware to predict the amount of revenue (in thousands of dollars) he can make on the full version of the new shareware. Following is the output from a simple linear regression along with the residual plot and normal probability plot obtained from a data set of 30 different sharewares that he has developed:       -Referring to Scenario 13-11, which of the following is the correct null hypothesis for testing whether there is a linear relationship between revenue and the number of downloads? a)  H _ { 0 } : b _ { 1 } = 0  b)  H _ { 0 } : b _ { 1 } \neq 0  c)  H _ { 0 } : \beta _ { 1 } = 0  d)  H _ { 0 } : \beta _ { 1 } \neq 0  SCENARIO 13-11 A computer software developer would like to use the number of downloads (in thousands) for the trial version of his new shareware to predict the amount of revenue (in thousands of dollars) he can make on the full version of the new shareware. Following is the output from a simple linear regression along with the residual plot and normal probability plot obtained from a data set of 30 different sharewares that he has developed:       -Referring to Scenario 13-11, which of the following is the correct null hypothesis for testing whether there is a linear relationship between revenue and the number of downloads? a)  H _ { 0 } : b _ { 1 } = 0  b)  H _ { 0 } : b _ { 1 } \neq 0  c)  H _ { 0 } : \beta _ { 1 } = 0  d)  H _ { 0 } : \beta _ { 1 } \neq 0
-Referring to Scenario 13-11, which of the following is the correct null hypothesis for testing whether there is a linear relationship between revenue and the number of downloads? a) H0:b1=0H _ { 0 } : b _ { 1 } = 0
b) H0:b10H _ { 0 } : b _ { 1 } \neq 0
c) H0:β1=0H _ { 0 } : \beta _ { 1 } = 0
d) H0:β10H _ { 0 } : \beta _ { 1 } \neq 0


Definitions:

Neutralize

To render something inactive by exerting a contrary force or influence, commonly utilized in the realms of chemistry and electricity.

Battery Posts

The positive and negative protruding terminals on a battery through which electrical power is provided to or received from a vehicle's or device's electrical system.

Baking Soda

A common household sodium bicarbonate powder used for baking, cleaning, and odor neutralizing.

Sectional Diameter

The diameter of a circular object or a section thereof, often used in the context of mechanical parts or engineering to describe specific measurements.

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