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TABLE 13-11 A Computer Software Developer Would Like to Use the Number

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TABLE 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: TABLE 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 Table 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<sub>0</sub> : b<sub>1</sub> = 0 B) H<sub>0</sub> : b<sub>1</sub> ≠ 0 C) H<sub>0</sub> : β<sub>1</sub> = 0 D) H<sub>0</sub> : β<sub>1</sub> ≠ 0 TABLE 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 Table 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<sub>0</sub> : b<sub>1</sub> = 0 B) H<sub>0</sub> : b<sub>1</sub> ≠ 0 C) H<sub>0</sub> : β<sub>1</sub> = 0 D) H<sub>0</sub> : β<sub>1</sub> ≠ 0 TABLE 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 Table 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<sub>0</sub> : b<sub>1</sub> = 0 B) H<sub>0</sub> : b<sub>1</sub> ≠ 0 C) H<sub>0</sub> : β<sub>1</sub> = 0 D) H<sub>0</sub> : β<sub>1</sub> ≠ 0
-Referring to Table 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?

Definitions:

Standard Error

The standard deviation of the sample distribution of a statistic, often used in the context of mean.

Mean

The central or typical value in a distribution, calculated as the sum of all observations divided by the number of observations.

Confidence Interval

A swath of values, taken from statistical analyses of a sample, anticipated to hold within it the value of a not-yet-known population trait.

Standard Error

The standard deviation of the sampling distribution of a statistic, typically the mean.

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