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. The printout is shown below. Model 1 Model 1 R .763ª Model 1 Model Summary R Square .582 (Constant) Extraversion a. Predictors: (Constant), Agreeableness, Extraversion, Conscientiousness Adjusted R Square Sum of Squares 27513.173 19788.785 47301.958 .519 Conscientiousness Agreeableness ANOVA df Regression Residual Total a. Dependent Variable: Sales (thousand euros) b. Predictors: (Constant), Agreeableness, Extraversion, Conscientiousness 3 Std. Error of the Estimate 31.455 20 23 Mean Square 9171.058 989.439 -69.238 7.916 6.102 12.962 a. Dependent Variable: Sales (thousand euros) Coefficients Unstandardized Coefficients B Std. Error F 9.269 29.434 2.305 2.483 2.849 Standardized Coefficients Beta .507 .390 .730 Sig. .000 t -2.352 3.435 2.458 4.550 Sig. .029 .003 .023 .000 Find the estimated parameters in the output and write the prediction equation in the following form: SALES= +. x EXTRAVERSION + x CONSCIENTIOUSNESS + x AGREEABLENESS. (Fill in the gaps with the appropriate values.)
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. The printout is shown below. Model 1 Model 1 R .763ª Model 1 Model Summary R Square .582 (Constant) Extraversion a. Predictors: (Constant), Agreeableness, Extraversion, Conscientiousness Adjusted R Square Sum of Squares 27513.173 19788.785 47301.958 .519 Conscientiousness Agreeableness ANOVA df Regression Residual Total a. Dependent Variable: Sales (thousand euros) b. Predictors: (Constant), Agreeableness, Extraversion, Conscientiousness 3 Std. Error of the Estimate 31.455 20 23 Mean Square 9171.058 989.439 -69.238 7.916 6.102 12.962 a. Dependent Variable: Sales (thousand euros) Coefficients Unstandardized Coefficients B Std. Error F 9.269 29.434 2.305 2.483 2.849 Standardized Coefficients Beta .507 .390 .730 Sig. .000 t -2.352 3.435 2.458 4.550 Sig. .029 .003 .023 .000 Find the estimated parameters in the output and write the prediction equation in the following form: SALES= +. x EXTRAVERSION + x CONSCIENTIOUSNESS + x AGREEABLENESS. (Fill in the gaps with the appropriate values.)
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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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. The printout is shown below.
<
Model
1
R
.763ª
Model
1
Model Summary
Conscientiousness
Model
1
R Square
.582
a. Predictors: (Constant), Agreeableness, Extraversion,
(Constant)
Extraversion
Adjusted R
Square
Sum of
Squares
27513.173
19788.785
47301.958
.519
Conscientiousness
Agreeableness
ANOVA
df
Regression
Residual
Total
a. Dependent Variable: Sales (thousand euros)
b. Predictors: (Constant), Agreeableness, Extraversion, Conscientiousness
3
Std. Error of
the Estimate
31.455
20
23
-69.238
7.916
6.102
12.962
a. Dependent Variable: Sales (thousand euros)
Mean Square
9171.058
989.439
Coefficients
Unstandardized Coefficients
B
Std. Error
F
9.269
29.434
2.305
2.483
2.849
Standardized
Coefficients
Beta
.507
.390
.730
Sig.
.000b
t
-2.352
3.435
2.458
4.550
Sig.
.029
.003
.023
.000
Find the estimated parameters in the output and write the prediction equation in the following form:
x CONSCIENTIOUSNESS + x AGREEABLENESS. (Fill in
+
SALES=+
x EXTRAVERSION +
the gaps with the appropriate values.)
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