Instruction 12-11 a Computer Software Developer Would Like to UseANOVA-Referring to Instruction 12-11,the Null Hypothesis That There Is No

The Answer of Instruction 12-11 a Computer Software Developer Would Like to UseANOVA-Referring to Instruction 12-11,the Null Hypothesis That There Is No

Instruction 12-11 a Computer Software Developer Would Like to UseANOVA-Referring to Instruction 12-11,the Null Hypothesis That There Is No

The Answer of Instruction 12-11 a Computer Software Developer Would Like to UseANOVA-Referring to Instruction 12-11,the Null Hypothesis That There Is No

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Instruction 12-11
a Computer Software Developer Would Like to Use

question 4

True/False

Instruction 12-11
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:
$\begin{array}{lr}\hline {\text { Regression Statistics }} \\\hline \text { Multiple R } & 0.8691 \\\hline \text { R Square } & 0.7554 \\\hline \text { Adjusted R Square } & 0.7467 \\\hline \text { Standard Error } & 44.4765 \\\hline \text { Observations } & 30.0000 \\\hline\end{array}$
ANOVA
$\begin{array}{|l|r|r|r|r|r|}& d f & \text { SS } & {M S} & F & \text { Significance } F \\\hline \text { Regression } & 1 & 171062.9193 & 171062.9193 & 86.4759 & 0.0000 \\\hline \text { Residuall } & 28 & 55388.4309 & 1978.1582 & \\\hline \text { Total } & 29 & 226451.3503 & &\end{array}$

$\begin{array}{lrrrrrrr}\hline & \text { Coefficients } & \text { Standard Eror } &{t \text { Stat }} & \text { P-value } & \text { Lower 95\% } & \text { Upper 95\% } \\\hline \text { Intercept } & -95.0614 & 26.9183 & -3.5315 & 0.0015 & -150.2009 & -39.9218 \\\hline \text { Download } & 3.7297 & 0.4011 & 9.2992 & 0.0000 & 2.9082 & 4.5513\end{array}$ $Instruction 12-11 A computer software developer would like to use the number of downloads (in thousands)for the trial version of his new shareware to predict the amount of revenue (in thousands of dollars)he can make on the full version of the new shareware.Following is the output from a simple linear regression along with the residual plot and normal probability plot obtained from a data set of 30 different sharewares that he has developed: \begin{array}{lr} \hline {\text { Regression Statistics }} \\ \hline \text { Multiple R } & 0.8691 \\ \hline \text { R Square } & 0.7554 \\ \hline \text { Adjusted R Square } & 0.7467 \\ \hline \text { Standard Error } & 44.4765 \\ \hline \text { Observations } & 30.0000 \\ \hline \end{array} ANOVA \begin{array}{|l|r|r|r|r|r|} & d f & \text { SS } & {M S} & F & \text { Significance } F \\ \hline \text { Regression } & 1 & 171062.9193 & 171062.9193 & 86.4759 & 0.0000 \\ \hline \text { Residuall } & 28 & 55388.4309 & 1978.1582 & \\ \hline \text { Total } & 29 & 226451.3503 & & \end{array} \begin{array}{lrrrrrrr} \hline & \text { Coefficients } & \text { Standard Eror } &{t \text { Stat }} & \text { P-value } & \text { Lower 95\% } & \text { Upper 95\% } \\ \hline \text { Intercept } & -95.0614 & 26.9183 & -3.5315 & 0.0015 & -150.2009 & -39.9218 \\ \hline \text { Download } & 3.7297 & 0.4011 & 9.2992 & 0.0000 & 2.9082 & 4.5513 \end{array} -Referring to Instruction 12-11,the null hypothesis that there is no linear relationship between revenue and number of downloads should be rejected at a 5% level of significance.$ $Instruction 12-11 A computer software developer would like to use the number of downloads (in thousands)for the trial version of his new shareware to predict the amount of revenue (in thousands of dollars)he can make on the full version of the new shareware.Following is the output from a simple linear regression along with the residual plot and normal probability plot obtained from a data set of 30 different sharewares that he has developed: \begin{array}{lr} \hline {\text { Regression Statistics }} \\ \hline \text { Multiple R } & 0.8691 \\ \hline \text { R Square } & 0.7554 \\ \hline \text { Adjusted R Square } & 0.7467 \\ \hline \text { Standard Error } & 44.4765 \\ \hline \text { Observations } & 30.0000 \\ \hline \end{array} ANOVA \begin{array}{|l|r|r|r|r|r|} & d f & \text { SS } & {M S} & F & \text { Significance } F \\ \hline \text { Regression } & 1 & 171062.9193 & 171062.9193 & 86.4759 & 0.0000 \\ \hline \text { Residuall } & 28 & 55388.4309 & 1978.1582 & \\ \hline \text { Total } & 29 & 226451.3503 & & \end{array} \begin{array}{lrrrrrrr} \hline & \text { Coefficients } & \text { Standard Eror } &{t \text { Stat }} & \text { P-value } & \text { Lower 95\% } & \text { Upper 95\% } \\ \hline \text { Intercept } & -95.0614 & 26.9183 & -3.5315 & 0.0015 & -150.2009 & -39.9218 \\ \hline \text { Download } & 3.7297 & 0.4011 & 9.2992 & 0.0000 & 2.9082 & 4.5513 \end{array} -Referring to Instruction 12-11,the null hypothesis that there is no linear relationship between revenue and number of downloads should be rejected at a 5% level of significance.$
-Referring to Instruction 12-11,the null hypothesis that there is no linear relationship between revenue and number of downloads should be rejected at a 5% level of significance.

Definitions:

William McDougall

A British psychologist and one of the founding figures of social psychology, known for his work on instinct and the social nature of human beings.

Instincts

are innate, typically fixed patterns of behavior in animals and humans that are responses to specific stimuli and serve survival and reproductive purposes.

Cognition

Refers to the mental processes involved in gaining knowledge and comprehension, including thinking, knowing, remembering, judging, and problem-solving.

Seligman

Refers to Martin Seligman, a psychologist known for his work on the theory of learned helplessness and for promoting positive psychology.