Data analysis report - Factors influencing pocket expenses of college students

GCSE ICT

DATA ANALYSIS REPORT

FACTORS INFLUENCING POCKET EXPENSES

OF COLLEGE STUDENTS

Date: 11th June, 2004

TABLE OF CONTENTS

Executive Summary

Introduction

Methodology

3. Descriptive Analysis

4. Inferential Analysis

5. Conclusion

6. Excel Functions Used

7. Appendix: The Questionnaire

INTRODUCTION

The area under discussion in the following report is the relationship between the factors affecting pocket expenses of college students. It envelops a range of processes and techniques, which were employed to collect data regarding the above-mentioned theme, as well as a detailed analysis of the same. Suitable diagrams and graphs have been included in the report so as to make it interesting and simple for the reader. Concurrently it puts in numerous tests like f-distribution test, chi square distribution test, test for goodness of fit, z-test for correlation and other miscellaneous tests to clarify the subject matter. In addition it enlightens the Excel functions being used for the analysis as well as a brief summary and conclusion of the whole report.

METHODOLOGY

The key word in statistics is ‘data’. Data refers is all the information collected in any form for analysis. Data may be expressly collected for a specific purpose. Such data are known as primary data. The collection of facts and figures relating to the population in the census provides primary data. Often, however data collected for some purpose, frequently for administrative reasons, may be used. Such data are known as secondary data. The following methods are generally adopted for collecting the data.

Postal questionnaire
Questionnaires to be filled in by enumerators
Telephonic interview
Observation Reports
Results of experiments

Some other modern techniques used for collecting data are:

E-mail
Having questionnaires put up on chat rooms

Collection of Data

We followed a planned strategy for the collection of data. As our topic was concerned with college students we targeted the universities, cafeterias, call centres, cinemas and other rendezvous places such as Priya’s, DT malls etc. As we were a group of 3 we divided these places according to locations convenient for each. As it was time for admissions we knew the target would be the Delhi University and there is where we got most of our data. We stood near the admission office and as students came to collect admission forms we asked them to spare a minute explaining them the purpose of the questionnaires. To get a wide array of people we also went to colleges of fashion designing (NIFD), interior decoration, engineering colleges and other colleges of vocational studies.
We also e-mailed the questionnaires to our friends staying or studying abroad in order to see how their expenditure differs from ours. The questionnaires were mailed to U.S.A, U.K and Australia. We converted their currency in rupees to have the data in the same currency in order to make interpretation easier. We also posted the questionnaires on the yahoo chat room notice board for others to fill in n give their opinion. As we kept the name as optional most of them filled in as they knew their identity would be kept secret.

DESCRIPTIVE ANALYSIS

Statistics is a subject, which can be (and is) applied to every aspect of our lives. The aim of statistical methods is simple: to present information in a clear, concise and accurate manner. The difficulty in analysing many phenomena, be they economic, social or otherwise, is that there is simply too much information for the mind to assimilate. The task of descriptive methods is therefore to summarize all this information and draw out the main features, without distorting the picture. Descriptive statistic uses graphs and statistical formulae in order to interpret the information and get desired results.

Our research considered various quantitative as well as qualitative factors that influence the pocket expenses of college students. The qualitative data was made quantifiable with the help of dummy variables. Also, factors like the highest level of education of parents were converted into years of education. All data was clearly represented in a spreadsheet format in Microsoft Excel, where the serial number of the entry corresponded to the survey form number on the questionnaire. Here functions such as ‘sort in ascending order’ were used. With the help of this it was evident that the sample space used was appropriate to comment on the population. [As the monthly pocket money, ‘Y’ ranged from Rs.500 to Rs.15000.]

This section on descriptive analysis involves the inferences drawn out when different variables are linked either individually with the ‘Y’ factor or with each other with the help of histograms, pie charts, and other data analysis tools.

The observations were as follows:

1. Relation of time devoted to self-study with the monthly pocket money:

An inverse relation is evident, when plotting monthly pocket money against the time devoted to self-study (hrs per week). It was observed that on an average, college students receiving pocket money around Rs.500 per month utilize about 30-50 hrs per week for self-study. On the other hand, as the pocket money rises, study time falls to as low as ...