DESCRIPTIVE STATISTICS

Descriptive Statistics

Measures of Central Tendency and Dispersion

Introduction

Measures of central tendency (mean, median and mode) serve as points of reference for interpreting Measures of Central Tendency and Dispersion provides a basis for conducting further tests on the data. In order to analyze the measure of central tendency and dispersion for this research paper, data has been taken from the General Social Survey (GSS) Data Disk file of Year 2008 labeled as 2008 Cross Panel Data.

The purpose of a measure of central tendency is to summarize in one number the typical value or the most representative of a result set. There are different measures of central tendency. The best known methods to measure the central tendency of the data include arithmetic mean, mode, and the median. To variables have been included from the data file in this study; one is measured as a continuous variable, whereas another variable is measured on a nominal scale.

These include “Respondent Income in Dollars” as continuous Variable and the “Region of the Interviewer” as nominal variable. “Respondent Income in Dollars” is a continuous variable measuring the number of hours on Likert scale due to continuity in the respondent's responses. Overall, there are 2044 respondents, who have been covered in the survey. Since the data is considerably large, therefore, it enhances the accuracy of the results because the error is spread across a large number of respondents that were included in the GSS Cross Panel Data Study for the year 2008. This research paper examines the measure of central tendency and dispersion for the two variables selected from on the data file. Historical evidences show that the income of an individual is significantly linked with the region of the individual. Region of the interviewer is categorized in nine segments that have been included in the analysis. These segments were categorized on the basis of location of the interviewer. These include New England; middle Atlantic, East North Central, West North Central, South Central, East South Central, West South Central, Mountain, and Pacific region. Since income is taken as a continuous variable therefore, no segment has been created for the total income of the respondent.

Descriptive Statistics Analysis

Standard deviation was higher for respondent income in respondents belonging to New England region. Standard deviation of respondent income in respondents belonging to New England region stood at 35658.14 compare to 27219.41 for the respondent income in respondents belonging to Middle Atlantic region. Std. error mean of respondent income in respondents belonging to New England region was 5375.66 with mean value of $45904 income level compare to the mean value of $34904 for income level of respondents belonging to Middle Atlantic region. Because sample size was significantly large, therefore lower deviation rate of respondent income shows that income level is consistent in a group of respondents belonging to Middle Atlantic region. Higher sample size and test result for large population size may increase the viability of results based for predicting the family income of people belonging to New England and Middle Atlantic region ...