Results of the survey:

The results of the survey can be used in various ways in the work place, Horace (1990) highlights some uses of statistics in business, using this uses highlighted the case study results will be used for the following reasons. One use of statistics is that it helps in summarising data values which make it even easier to understand, this involves determination of mean, median and mode and also use of tables and graphs that help in describing data.

According to Horace (1990) statistical results of a survey will also be used when comparing results of an organisation with other organisations or even comparing changes over a time for the same organisation. the third way in which these results will be used is that they can be used in making decisions, the results can be used in decision making where the managers will determine the best way to improve job satisfaction, finally statistical results will be used in better understanding of the organisation whereby managers will be aware of the job satisfaction mean level and the most appropriate ways to improve the workplace.

Correlational research:

Correlational research according to Fox (1999) is a research design that aims at establishing the relationship between two variables or more, these form of research studies are aimed at showing the relationship between two variables and not how one variable causes the another variable to change, this means that there is a difference between correlation and causation. Causation refers to how one variable causes another study variable to change while correlation refers to the strength of the relationship between variables.

Results of the Survey

From the case study the age and the overall variable can be used to undertake a correlational study, this is because previous studies have show that older individuals have higher job satisfaction levels than younger workers, for this reason the correlation coefficient of the two variables is expected to be positive whereby as age increases job satisfaction levels also increase. The reason why these variables are appropriate is that these two variables have a high correlation value from the AIU data set, and also that this hypothesis that there is a relationship between job satisfaction and age has been studied in the past.

From the course there are number of concepts learnt about correlation and causation, one is that even when the correlation coefficient of tow variables is high due not mean that one variable in the study causes the other variable to change, however it is evident that when studying causation it is important that the correlation between the variables is determined in order to first establish the relationship between variables.

Comments on postings:

The positing by Azur Hamidovic summarizes the AIU data set and also reports various probability values, probability according to the paper is calculated using the relatively frequency of each variable under study, given that this is a report all variables should have been summarized whereby mean and measures of deviation should have been reported, the only variables summarized in the paper are tenure, age and gender.

The report contains only one graph whereas an appropriate report should contain a number of charts that summarize results for each variable. However the paper clearly describes the calculation of probabilities of given variable for example, the probability of picking an individual whose age is between 16 and 21 years, these values are calculated by dividing the number of

Results of the Survey

individuals aged 16 and 21 and by the total individuals. Finally the layout of the report is excellent and contains in text citations that indicate how additional information of concepts can be obtained.

Results of the Survey


Horace, S. (1990). Statistics in business: their analysis, charting and use, New York: McGraw Hill Press.

Levin, J. and Fox, J. (1999). Elementary Statistics in Social Research, New Jersey: Prentice hall.