Fundamentals of Statistics

Abstract

Data which is obtained from a study should be properly applied and summarized with the help of various research methods. This study is devoted to the examination of survey data and the analysis of the results of this survey. Moreover, it centers on the importance of appropriate usage of measures for qualitative and quantitative variables. The results of analysis of qualitative and quantitative data sections are provided in a visual format which makes the understanding of the results easier.

Introduction

In this study I am going to examine data from a sample of a survey about the job satisfaction, analyze the results, using qualitative and quantitative variables. Differences between both methods of research mean usage of specific types of measurements which sometimes cannot be appropriate for a particular type of data analysis. The results of examination of the two chosen sections will be provided in a visual format.

Chosen Variables

I have chosen the following sections of data for the variables – Position for a qualitative variable and Extrinsic Job Satisfaction for a quantitative one. My decision is mainly based on the hypothesis that position of an employee can influence his/her satisfaction with external factors of the position, for example, personal office – especially when an employee is said to work overtime in the office. If position of an employee is closely connected with the quality of job environment, it may affect his/her satisfaction with external aspects of the job.

Difference in variable types

The main difference between qualitative and quantitative variables is the type of data measurement. Quantitative variable is expressed in numbers or quantities, while qualitative variable is mainly a category of data which actually cannot be measured, like race or gender. Some descriptive statistics can be appropriate for the only variable. To illustrate, frequency distributions like mode or range are used for qualitative variables in order to evaluate the frequency of each category implemented to the study. Quantitative variable is expressed in numerical form and thus measures of central tendency and dispersion should be used for this type of data analysis.

Descriptive statistics: Qualitative variable

Explanation of descriptive statistics

The participants were divided into two categories which correspond to the position of employees – either hourly or salaried employed. The mode of this data section is the first category. I would recommend to AIU to involve more salaried employees to the survey because the number of salaried employees is a half less than those hourly employed (42 – all participants, 28 – hourly employees, and 14 – salaried employees).

Descriptive statistics: Quantitative variable

Explanation of descriptive statistics

= 0,18, and standard deviation is √0,18 = 0,42. In this case, one standard deviation above the mean is 5,81 and one standard deviation below the mean is 4,97. In fact, 78,6% of scores are between those two limits which is actually above the normal distribution. The analysis of this data allows to claim that most of the participants are satisfied with their job.

Chart/Graph for qualitative variable

Description of Chart

The above pie chart depicts the division of survey participants by their job …
Posted by: Lissa Kimble

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