Calculate the estimated standard error of the regression model. (Your answer must be accurate within ±0.001 thousand euros). Answer:

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An HR expert at an insurance company is considering the introduction of personality tests in the
process of recruiting sales agents. It is hypothesised that certain personality traits may contribute to
being a successful sales agent, and therefore personality profiles can be used to select the best
applicants for open positions. The introduction of personality measures in the recruitment process,
however, is only meaningful if there is evidence that certain personality characteristics are related to
job performance. To test whether success in this occupation is related to personality features, the
expert conducts a study, in which a random sample of currently employed sales agents fill in a
questionnaire measuring three traits: (1) extraversion, (2) conscientiousness and (3) agreeableness.
Each trait is measured on a scale ranging between 0 and 10 points. To test whether the annual total
value of insurance policies sold by an agent can be predicted from personality scores, a multiple
linear regression model is constructed, in which an agent's 12-month total sales (in thousand euros)
serve as the dependent variable and the agent's scores on the three personality dimensions function
as the independent variables. The analysis is conducted in SPSS. A partial printout of the analysis is
shown below.
Model
1
Regression
Residual
Sum of
Squares
12583.535
ANOVA
41471.862
df
Mean Square
F
Total
28
a. Dependent Variable: Sales (thousand euros)
b. Predictors: (Constant), Agreeableness, Conscientiousness, Extraversion
Sig.
Transcribed Image Text:An HR expert at an insurance company is considering the introduction of personality tests in the process of recruiting sales agents. It is hypothesised that certain personality traits may contribute to being a successful sales agent, and therefore personality profiles can be used to select the best applicants for open positions. The introduction of personality measures in the recruitment process, however, is only meaningful if there is evidence that certain personality characteristics are related to job performance. To test whether success in this occupation is related to personality features, the expert conducts a study, in which a random sample of currently employed sales agents fill in a questionnaire measuring three traits: (1) extraversion, (2) conscientiousness and (3) agreeableness. Each trait is measured on a scale ranging between 0 and 10 points. To test whether the annual total value of insurance policies sold by an agent can be predicted from personality scores, a multiple linear regression model is constructed, in which an agent's 12-month total sales (in thousand euros) serve as the dependent variable and the agent's scores on the three personality dimensions function as the independent variables. The analysis is conducted in SPSS. A partial printout of the analysis is shown below. Model 1 Regression Residual Sum of Squares 12583.535 ANOVA 41471.862 df Mean Square F Total 28 a. Dependent Variable: Sales (thousand euros) b. Predictors: (Constant), Agreeableness, Conscientiousness, Extraversion Sig.
Model
1
(Constant)
Extraversion
Answer:
Coefficients
9.126
5.565
5.479
3.001
a. Dependent Variable: Sales (thousand euros)
Conscientiousness
Agreeableness
Unstandardized Coefficients
B
Std. Error
23.150
2.129
2.539
2.113
Standardized
Coefficients
Beta
.449
.365
.241
t
.394
2.614
2.158
1.420
Sig.
.697
.015
.041
.168
Calculate the estimated standard error of the regression model. (Your answer must be accurate
within ±0.001 thousand euros).
Transcribed Image Text:Model 1 (Constant) Extraversion Answer: Coefficients 9.126 5.565 5.479 3.001 a. Dependent Variable: Sales (thousand euros) Conscientiousness Agreeableness Unstandardized Coefficients B Std. Error 23.150 2.129 2.539 2.113 Standardized Coefficients Beta .449 .365 .241 t .394 2.614 2.158 1.420 Sig. .697 .015 .041 .168 Calculate the estimated standard error of the regression model. (Your answer must be accurate within ±0.001 thousand euros).
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