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Quantitative Methods and Analysis Ip U1

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Unit 1 - Fundamentals of Statistics
Jeanna Starr
American InterContinental University

Abstract A data analysis was done on job satisfaction for the company AIU categorized by age, gender, tenure, position, and department. Overall job satisfaction as well as intrinsic (satisfaction with the actual performance of the job) and extrinsic (office location or work colleagues) job satisfaction were considered in this survey.

Introduction AIU assembled a team of researchers to study job satisfaction. I was selected as part of a group to participate in a massive global undertaking. The study required me to examine data and analyze the results. The study consists of job satisfaction, which is extremely important to an organization’s overall success. This particular study will allow managers to gain understanding and knowledge about what type of human behaviors can be used to strengthen an organization’s performance.
Chosen Variables I have chosen gender for my qualitative data and intrinsic for my quantitative data. The reason that I have chosen these two variables is because I thought it would be interesting to analyze if males or females were more satisfied with their job, and how the actual job performance reflected their job satisfaction rating.
Difference in variable types Qualitative variables include subjects that are non-numerical, such as gender. Quantitative variables include subjects that are numerical and give us a clear visual as to what the subject looks like. For instance, if we see a qualitative variable such as cat, we only know that the variable is a cat. A quantitative variable could tell us the weight of the cat, giving us a visual to compare the different sizes of the different cats, i.e. cat one weighs ten pounds, cat two weighs fifteen pounds. In this situation, the descriptive statistics are relatively useless

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