Overall Job Satisfaction

Overall Job Satisfaction:

Abstract:

Employee performance will highly depend on job satisfaction. This paper highlights the difference in job satisfaction with reference to gender, from the analysis male employees have higher job satisfaction than female following the rejection of the null hypothesis test at the 95% level of test that male satisfaction is equal to female satisfaction, it is also evident from the analysis that job satisfaction will depend on age and gender.

Introduction:

Data was retrieved from a study by Rose, M., (2001) regarding job satisfaction, the data contains variables that depict the age, gender and overall job satisfaction of workers. The job satisfaction data scale ranged from 1 to 7 with one depicting least satisfaction and 7 depicting most satisfied. it is expected that male workers will have a higher mean value of overall job satisfaction and that older workers are less satisfied with their job than younger workers. The following is an analysis of the data and also a hypothesis test to determine whether male workers are more satisfied with their job than female workers.

Data:

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The data shows that overall job satisfaction for male workers is 4.64 and the overall satisfaction for female is 1.59. The standard deviation for overall job satisfaction for male workers is 1.51 and for female the standard deviation is 1.34, the following chart summarizes the mean overall satisfaction.

Age groups and overall job satisfaction:

The sample contains three age categories and this includes those aged below 21 years, those aged between 22 and 49 years and those aged above 50 years, 45% of the sample were aged between 22 and 49 years, 14% were aged over 50 years and 41% were aged 21 years and below.

The following chart summarizes the results:

The following chart summarizes the mean values for the age groups.

From the above chart it is evident that those aged above 50 years have a higher job satisfaction than the other age groups. The mean overall job satisfaction for those aged above 50 and over was 4.75, the mean for those aged 22 to 49 years was 4.16 and for those aged below 21 years was 4.17.

Importance of this analysis:

This analysis is important given that the level of job satisfaction will determine the performance of workers; this analysis will also highlight differences in job satisfaction among the age groups and gender and therefore will help companies to device ways to increase job satisfaction in

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order to improve performance of workers.

Hypothesis testing:

This section determines whether male workers have higher job satisfaction than female workers at the 95% level of test, the null and alternative hypothesis is stated as follows:

Hypothesis:

Null hypothesis:

H0:M=F

M stands for the mean job satisfaction value for male and F stands for female job satisfaction female mean value.

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Alternative hypothesis:

Ha: M > F

Test statistics

The SPSS program is used to compute the test statistics at the 95% level of test, the following output summarizes the results:

Independent Samples Test

t-test for Equality of  Means

t

df

Sig. (2-tailed)

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Mean Difference

Std.  Error Difference

-.857

23.259

.400

-.46263

.53976

The T statistics value is -0.857, the T critical 2 tail values from the above output is negative or positive 0.4.

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Decision:

When the calculated T value is greater than the T test value then this means that we reject the null hypothesis, when the calculated T value is less than the T critical value then we accept the null hypothesis, in our case the T calculated value is greater than the T critical value and therefore we reject the null hypothesis.

Interpretation:

From the above analysis it is evident that the null hypothesis that the two mean values ware equal was rejected, this means that the alternative hypothesis is accepted and this means that the job satisfaction value for male workers is greater than the value for the female workers.

Probability:

Z test:

Another question that arises is the probability that overall job satisfaction is greater than 5, the mean overall job satisfaction is 4.4562 and the standard deviation is 1.38096, the Z table will be appropriate in determining the probability than the overall job satisfaction is greater than 5. The first step is to determine the Z score value; this is done using the formula:

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Z = (X – mean)/ standard deviation

Z = (5 – 4.4562)/1.38096

Z = 0.3938

From the Z table the probability value is 0.987038742, this means that the probability that the overall satisfaction value is 5 is 98.70%

Binomial distribution:

The other question is the probability of choosing 3 male workers from the sample when 4 independent trails are undertaken, given that 62% in the sample are male and we want 3 male workers chosen from the four trials

The binomial distribution function is a s follows:

P(x) = (nCK ) Pk ( 1-p)n-k

In this case n = 4, p = 0.62, k =3

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P(x) = 0.362259

This means that the probability of choosing 3 male participants from 4 trials is 0.362259.

Poisson distribution:

Another question that may arise is the probability that given that 10 individuals will quit their job every year, what is the probability that 20 individual will quit their job in one year? The Poisson probability function is stated as follows

P(x) = (λ k e- λ)/ k!

In this case k = 10, e is the natural log and λ is 2

P(x) = 0.005816307

Therefore the probability that 20 individuals will quit their job in one year is 0.0058.

Correlation:

In this section we analysis the correlation coefficient of the two variables age and overall job satisfaction, The correlation coefficient of the two variable is -0.062 and this shows that there is a weak correlation between the two variables, also the negative value means that as one variable increases the other variable is declining.

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Regression:

This section estimates a model that depicts overall job satisfaction as the dependent variable and age as the independent variable. The estimated model will take the following form:

Y = a + B1 A

Where Y is overall job satisfaction and A is age, the following table surmises the results:

Coefficients (a)

Model

Unstandardized  Coefficients

Standardized  Coefficients

t

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Sig.

B

Std.  Error

Beta

1

(Constant)

4.687

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.734

6.387

.000

age

-.127

.395

-.062

-.321

.751

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a Dependent Variable: overall satisfaction

From the above results the estimated model can be stated as follows:

y = 4.687- 0.127 age

The model states as the value of age increases then overall job satisfaction also declines, it also states that if all the factors were held constant and the value of the age variable is zero then the overall job satisfaction value will be 4.687. The model therefore states that older workers are less satisfied with their job than younger workers.

Conclusion:

From the above analysis it is evident that there are differences in the overall job satisfaction with reference to gender and age, male workers are more satisfied than female workers, also it is evident that the age will also affect job satisfaction whereby older workers have lower levels of job satisfaction. Further research should be aimed at determined the most effective ways to increase job satisfaction and also other factors that influence job satisfaction among workers.

References:

John Cummings and William Bailey (2002) Statistics, McGraw Hill Press, New York

December, from http://www.iser.essex.ac.uk/bhps/2001/docs/pdf/papers/rose.pdf

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