Hello Daniel, I hope you are well.
I have a quantitative methods for business assignment on Friday. It is a timed assignment and the topics are : descriptive method, probability distributions, sampling distributions, interval estimation, hypothesis testing and simple and multiple linear regression. I was wondering you are available to help.
Kind Regards,
John
Question I (30
Employees sometimes face the need to work overtime. This may happen, for example, when they are regularly
interrupted with unforeseen tasks (i.e., task uncertainty). In this question, we will use data from the 2010
European Working Conditions Survey on a random sample of 18,321 European employees drawn from
Europe's working population. Table A describes the variables used in the subsequent regression analysis.
Table A : Variable de tions
mean
1.757
1.167
0.671
0.484
40421
0.826
2.300
std. dev. mininum maximum
4.470
0.927
0.470
o .5tn
11.411
0479
1.621
descri On
number of days in a month that an employee
works more than 10 hours
frequency of with unforeseen tasks,
task uncertainty
often
ran •n from O never to 3
sector Of employee (O public sector: I private
employee geMer (0 female; | male)
employee age years
I if fulltime contract; O pad-time contract
firm size, ranging from O (small) to 6 (large)
private sector
gender
firm size
a.
How many of the sampled employees work in the public sector? And how many work fulltime?
(5 marks)
For each of the ratio variables in Table A, explain whether its distribution is negatively skewed, positively
skewed, or symmetrical.
(5 marks)
Which of the variables are nominal or ordinal? Please explain.
(5 marks)
Table B shows a linear regression equation to investigate the association between task uncertainty on the one
hand , and overtime on the other.
Table B: Estimated regression equation of overtime
Std. Error
0.035
0.072
0.068
0.003
0.089
0.021
0.163
adjusted R-square:
Dependent variable:
F 6' 18 314 : 100.17
task uncertainty
private sector
gender
age
fulltime
firm size
constant
0.032
overtime
s 0.000
0.226
0.103
0.902
-0.011
1.320
0.024
0.273
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