A Strong Link Between Age and Salary

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Research indicates that there is a strong link between age and salary. Much of this relates to experience. Essentially in order to assess whether there is a correlation between the age of an employee and his/her salary a portion of the data from employee records from Northcross, Plc was utilized. This data contained information with regards to staff grade, department, salary and age was utilized. This data contained information for one hundred and twenty-eight (128) employees. A scatter plot was first done to determine if there was a concentration of employees who had a lower salary and were younger or visa versa. It was determined that there was. Salary was plotted on the x-axis and age on the Y. See Figure 1 for a picture of the resulting scatter plot.

Scatter Plot
Figure 1. Scatter Plot

The scatter plot indicated that there is a positive correlation between age and salary. As such a Pearson’s two-tailed bivariate analysis was conducted on this data to assess whether there was a correlation between salary and age. The results of this analysis yielded a correlation which was significant at the 0.01 level and a correlation coefficient of.661. This correlation, however, was low. When examining correlation, it is vital to know that correlation does not imply causation and as such, no inferences can be made. See table 1 for a complete breakdown of the correlation analysis.

Table 1: Pearson’s Two-tailed Bivariate Analysis

Correlations
Salary Age
Salary Pearson Correlation 1 .611**
Sig. (2-tailed) .000
N 128 128
Age Pearson Correlation .611** 1
Sig. (2-tailed) .000
N 128 128
**. Correlation is significant at the 0.01 level (2-tailed).

In addition to a Pearson’s correlation, regression analysis was conducted whereby salary served as the dependent variable and age was the independent variable. In the process, an ANOVA was conducted in order to ascertain whether there was a linear relationship between salary and age. In this case, the ratio of the two mean squares, labeled F, is 2.798. Since the observed significance level is less than 0.0005, you are able to reject the null hypothesis that there is no linear relationship between salary and age. Essentially, you are able to conclude that there is a linear relationship between age and salary and infer that as an individual ages, his/her salary will increase. Refer to table 2 for the complete ANOVA results.

Table 2. ANOVA results.

ANOVA
Salary
Sum of Squares df Mean Square F Sig.
Between Groups 1.179E10 37 3.186E8 2.798 .000
Within Groups 1.025E10 90 1.139E8
Total 2.204E10 127
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