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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, there appears to be autocorrelation in the residuals.
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, there appears to be autocorrelation in the residuals.
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, there appears to be autocorrelation in the residuals.
-Referring to Table 13-11, there appears to be autocorrelation in the residuals.


Definitions:

Categorical Data

Data that can be separated into specific categories according to distinct characteristics that are non-numeric.

Geographical Areas

Refers to specific physical locations defined by natural or artificial boundaries.

Quantitative Data

Numerical data representing the quantity, amount, or range of something.

Data Dashboard

A set of visual displays that organizes and presents information that is used to monitor the performance of a company or organization in a manner that is easy to read, understand, and interpret.

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