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Business Data Analysis

The value of correlation coefficient is positive. Therefore it can be said that as age increases so does income.
The level of dissatisfaction is significantly higher in women as compared to men. There were 14 ‘extremely dissatisfied’ responses from women as compared to only 6 from men. On the other hand the positive responses were 117 as compared to only 89 from women. However almost 21 males very a little dissatisfied as compared to only 8 from women.
a. Predictors: (Constant), How many promotions, if any, have you received while working for your present employer?, How many traumatic events did you experience last year?, How many hours did you work last week, at all jobs?, How many years of school have you completed?, In your household, how many family members, including yourself, were employed last year?, Age, Your pre-tax income last year ($000), Total family pre-tax income last year ($000), Since you were 16 years old, about how many years have you worked for full-time pay?
The age of employees at the company varies between 69 and 18. This is a very large level of diversity. This diversity can be help in creating creativity but also can be a tough task to manage such a diverse workforce. The major workforce has their age in the mid thirties. The age of employees can affect their output. Therefore it was important to analyze the affect of employee age on different variables. The analysis revealed that as the age of employees was increases their number of hours worked were becoming less. This means that older people were working less as compared to the younger workforce. This can be due to the higher posts of senior employees and managerial roles. The increase in pretax income with an increase in age also supports this theory. As the employees get older they become senior and therefore have a better pay scale and have to put in fewer hours. The age however was totally unrelated to union membership. Therefore we can that there was an ...Show more

Summary

As can be seen in the graphs the highest frequency of employees lay around the age of mid thirties. The highest frequency is of the age thirty seven.
The relationship between age and number of hours worked is strong. This…
Author : hanetamara
Business Data Analysis essay example
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