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Instruction 13  OUTPUT \text { OUTPUT } Note: Adj R Square = Adjusted R Square; Std

question 77

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Instruction 13.13
A financial analyst wanted to examine the relationship between salary (in $1,000) and four variables: age (X1 = Age), experience in the field (X2 = Exper), number of degrees (X3 = Degrees) and number of previous jobs in the field (X4 = Prevjobs). He took a sample of 20 employees and obtained the following Microsoft Excel output:
 OUTPUT \text { OUTPUT }
 SUMMARY Regression  Statistics Multiple R 0.992 R Square 0.984 Adj. R Square 0.979 Std. Error 2.26743 Observations 20\begin{array}{ll}\text { SUMMARY}\\\text { Regression }&\text { Statistics}\\\text { Multiple R } & 0.992 \\\text { R Square } & 0.984 \\\text { Adj. R Square } & 0.979 \\\text { Std. Error } & 2.26743 \\\text { Observations } & 20\end{array}

 ANOVA  df  SS  MS F Signif F  Regression 44609.831641152.45791224.1600.0001 Residual 1577.118365.14122 Total 194686.95000\begin{array}{l}\text { ANOVA }\\\begin{array}{llllll} & \text { df } & \text { SS } & \text { MS } & F & \text { Signif F } \\\text { Regression } & 4 & 4609.83164 & 1152.45791 & 224.160 & 0.0001 \\\text { Residual } & 15 & 77.11836 & 5.14122 & & \\\text { Total } & 19 & 4686.95000 & & &\end{array}\end{array}

 Coeff  Std Error t Stat p value  Intercept 9.6111982.779886383.4570.0035 Age 1.3276950.1149193011.5530.0001 Exper 0.1067050.142655590.7480.4660 Degrees 7.3113320.803241879.1020.0001 Prevjobs 0.5041680.447715731.1260.2778\begin{array}{lllll} & \text { Coeff } & \text { Std Error } & t \text { Stat } & p \text { value } \\\text { Intercept } & -9.611198 & 2.77988638 & -3.457 & 0.0035 \\\text { Age } & 1.327695 & 0.11491930 & 11.553 & 0.0001 \\\text { Exper } & -0.106705 & 0.14265559 & -0.748 & 0.4660 \\\text { Degrees } & 7.311332 & 0.80324187 & 9.102 & 0.0001 \\\text { Prevjobs } & -0.504168 & 0.44771573 & -1.126 & 0.2778\end{array}

Note: Adj. R Square = Adjusted R Square; Std. Error = Standard Error
-Referring to Instruction 13.13,the p-value of the F test for the significance of the entire regression is ___________.


Definitions:

Termination

The act of ending or concluding something, such as a therapy session, employment, or a contract.

Outcomes

The results or consequences of actions taken in a healthcare context, often used to measure the efficiency of treatments or interventions.

Positive Regard

An attitude of acceptance and respect towards others, regardless of their actions or beliefs.

Growth

The process of increasing in size, maturity, or development, often characterized by progress or evolution in a particular aspect.

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