Samples, Hypothesis Testing/Variance, and Regression Analysis - Essay Example

For example, if we are considering the data of job satisfaction so we must decide that do we want to analyze the satisfaction level of employee according to gender or as a whole. This decision may affect the sample size. If we want greater level of accuracy in our results so there is a large sample required and it costs more. Many researchers aim for a maximum range of error of ±5.0% at a 95% confidence level, whereas some have set internal ranges of error between ±5.0% and ±10%, depending on the type of decisions to be made. A ± 5.0% level of accuracy means that if the same study were repeated 100 times, in 95 of those times the results would not vary more than 5.

0 percentage points, higher or lower, from the results of the original study (Ball, 2004). By using the MS Excel we can get the Descriptive Statistics of the data that help us to know the average, standard deviation and the minimum and the maximum values. In the job satisfaction data the MS Excel can helps to find the association among the variables by doing the correlation analysis. That can describe us that what is the impact of one variable on another, for example we can find that what is the effect of satisfaction with the benefits with the overall satisfaction with the employee.

Along with it the graphical presentation of data helps us to understand the data more easily. For the manager of any organization it is easy to understand that what the steps should be taken in order to satisfy their customer along with it the difference of the age and gender can also understand easily. There are nine variables in the data set of job satisfaction that are Gender, Age, Department, Position, Tenure, Overall, Intrinsic, Extrinsic Job Satisfaction, Benefits. By using this data set any company can create an ideal profile in which the company can define that what could be the impact of Gender,