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• Level: GCSE
• Subject: ICT
• Word count: 3975

# Data analysis report - Factors influencing pocket expenses of college students

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Introduction

DATA ANALYSIS REPORT FACTORS INFLUENCING POCKET EXPENSES OF COLLEGE STUDENTS Date: 11th June, 2004 TABLE OF CONTENTS Executive Summary 1. Introduction 2. 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. ...read more.

Middle

To be exactly the same, as the equation estimated from the sample observations, Y = a + b1X1 + b2X2 +........+ bkXk Even so we can use the value of b1, one of the factors, we calculate from the sample, to test hypotheses value of B1, one of the factors of the regression plane for the entire population. We test the following Hypothesis about B1. H0 : B1 = 0 Null Hypotheses H1 : B1 � 0 Alternate Hypotheses If H0 is rejected, we will conclude that B1 � 0 and that the two variables have a statistically significant relationship. However, if H0 cannot be rejected [We reject H0 if (t < -ta/2) or if (t > ta/2)], we would not have sufficient evidence to conclude that there is a relation between the variables. Age: Here, test statistic, t = 2.891083 t0.025 = 1.50 With 2.891083>1.50 (t0.025), we reject H0 and conclude at the 0.05 significance that B1 is not equal to zero. The statistical evidence shows that there is a significant relationship between age and monthly expenses. Number of working parents: Here, test statistic, t = 2.155667 t0.025 = 1.50 With 2.155667>1.50 (t0.025), we reject H0 and conclude at the 0.05 significance that B1 is not equal to zero. The statistical evidence shows that there is significant relationship between Number of working parents with monthly expense of students. Monthly income: Here, test statistic, t = 2.613987 t0.025 = 1.50 With 2.613987<>.50 (t0.025), we reject H0 and conclude at the 0.05 significance that B1 is not equal to zero. The statistical evidence shows that there is significant relationship between family monthly income and monthly expenses of students, Number of siblings: Here, test statistic, t = -0.902742 t0.025 = 1.50 With -0.902742<1.50 (t0.025), we accept H0 and conclude at the 0.05 significance that B1 is equal to zero. The statistical evidence shows that there is no significant relationship between number of siblings and monthly expenses of students, Number of movies seen in a month: Here, ...read more.

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