Making Sense of Variable Data

Abstract

The following paper will discuss the application of statistical data analysis to a survey taken by an American company. It will highlight two variables from the survey and discuss how they are classified as either qualitative or quantitative and why. The descriptive statistics of each variable will be discussed and a visual representation of the data will be provided in the form of a chart or graph. An explanation of standard deviation and variance will be provided as well as a discussion on the importance of charts and graphs.

Keywords: statistics, data analysis, qualitative, quantitative, variable, standard deviation, variance, extrinsic

Introduction

The American Intellectual Union has conducted a study on job satisfaction. Vast amounts of data were collected. The data must be examined and analyzed so that the results can be communicated. This is a massive undertaking that will require the use of data analysis. Data analysis will make the statistical data coherent, so that it can be used to increase productivity and job satisfaction in the work force.

Chosen Variables

The data collected from the American intellectual Union has many variables. Two variables were chosen for closer examination. These variables are qualitative gender statistics and quantitative extrinsic job satisfaction statistics. These two variables were chosen because they represent different types of statistical data analysis.

Difference in variable types

There are differences between qualitative and quantitative variables. Variables that cannot be described as numbers are qualitative. These variables describe characteristics, such as hair color, race and eye color. Gender was chosen as the qualitative variable because male and female designations cannot be assigned to a specific number. Quantitative variables can be characterized in numerical terms (Qualitative Variable and Quantitative Variable. 2000).

Qualitative and quantitative variables...