Data Analysis

Table of Contents

1.0 Introduction 3

2.0 Outliers 3

3.0 Distribution of exam results 3

4.0 Bivariate Analysis 4

4.1 Impact of Gender 5

4.2 Impact of Quiz Results 6

4.3 Impact of Lecture Attendance 7

4.4 Impact of SGT Attendance 8

5.0 Conclusion 9

6.0 Bibliography 10

7.0 APPENDIX 11

Appendix 1. 11

Appendix 2 12

1.0 Introduction

In most countries, Australia included, universities play a critical role in the provision of higher education. In order for universities to provide high quality educational experience, it is prudent that they conduct continuous research geared towards finding ways in which to better understand learning so as to assist students to achieve their full potential. The purpose of this study is therefore to determine which educational factors influence the exam results. It also aims to examine the influence of gender on the performance of university students.

2.0 Outliers

An outlier is present when an observation or figure exemplifies extreme abnormalities and significantly lies in distance to a survey of variables. Outliers are considered because they are potential candidates for data errors and their presence can significantly skew data analysis results and lead to incorrect and misleading conclusions. The lowest z-score for the exam data set was -2.075 whereas the highest was 2.756 (see appendix). This implies that no outliers were present in the exam results data as no z-score was less than -3 or greater than +3 (Anderson & Sweeney, 2011).  

3.0 Distribution of exam results

With the continual prospect to foster economic growth; it is a well-established concept that markets are seeking alternative means of production to maximize utility and preserve cash-flows. With the technological frontier, the use of human capital has decreased. Consequently, individuals are opting for tertiary education to maximize personal utility and increase knowledge. Subsequently,...