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.
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.
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
1
Model
R
.547
Model Summary
Conscientiousness
Model
R Square
299
Regression
Residual
a. Predictors: (Constant), Agreeableness, Extraversion,
Adjusted R
Square
(Constant)
Extraversion:
Sum of
Squares
10333.355
24242.384
34575.739
.188
Conscientiousness
Agreeableness
ANOVA
df
Std. Error of
the Estimate
35.720
3
19
22
Total
a. Dependent Variable: Sales (thousand euros)
b. Predictors: (Constant), Agreeableness, Extraversion, Conscientiousness
Mean Square
3444.452
1275.915
34.883
5.149
4.482
628
a
Coefficients
Unstandardized Coefficients
B
Std. Error
F
2.700
24.005
2.702
2.613
3.054
Standardized
Coefficients
Beta
1376
339
040
Sig.
075b
t
1.453
1.905
1.716
205
Sig.
163
.072
102
839
a. Dependent Variable: Sales (thousand euros)
The output contains the results of several statistical tests. Which of these tests must be checked
first? Conduct this test at the .05 level of significance. State your conclusion and explain how you
arrived at that conclusion. Interpret the result of the test as it applies to personality dimensions and
sales performance.
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