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A Statistician Estimated the Multiple Regression Model y=β0+β1x1+β2x2+ξy = \beta _ { 0 } + \beta _ { 1 } x _ { 1 } + \beta _ { 2 } x _ { 2 } + \xi

question 114

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A statistician estimated the multiple regression model y=β0+β1x1+β2x2+ξy = \beta _ { 0 } + \beta _ { 1 } x _ { 1 } + \beta _ { 2 } x _ { 2 } + \xi , with 45 observations. The computer output is shown below. However, because of a printer malfunction, some of the results are not shown. These are indicated by the boldface letters a to l. Fill in the missing results (up to three decimal places).  Predictor  Coef  StDev  T  Constant 2.794a6.404x1b0.0070.025x20.3830.072c\begin{array} { | c | c c c | } \hline \text { Predictor } & \text { Coef } & \text { StDev } & \text { T } \\\hline \text { Constant } & 2.794 & a & 6.404 \\x _ { 1 } & b & 0.007 & - 0.025 \\x _ { 2 } & 0.383 & 0.072 & c \\\hline\end{array} S = d R-Sq = e.  ANALYSIS OF VARIANCE  Source of  Variation dfSSMSF Regression fijl Error g11.884k Total h26.887\begin{array}{l}\text { ANALYSIS OF VARIANCE }\\\begin{array} { | l | c c c c | } \hline \begin{array} { l } \text { Source of } \\\text { Variation }\end{array} & \mathrm { df } & \mathrm { SS } & \mathrm { MS } & \mathrm { F } \\\hline \text { Regression } & f & i & j & l \\\text { Error } & g & 11.884 & k & \\\hline \text { Total } & h & 26.887 & & \\\hline\end{array}\end{array}


Definitions:

Arithmetic

A branch of mathematics dealing with the properties and manipulation of numbers, including operations such as addition, subtraction, multiplication, and division.

Selective Attrition

The process where certain kinds of participants drop out of a study over time, potentially skewing the results.

Demand Characteristics

Subtle cues or signals in an experimental setup that suggest to participants what behavior is expected or desired, potentially influencing the outcomes of the study.

Replicability

The ability of a study or experiment to be repeated or reproduced to verify results and confirm reliability and validity of findings.

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