Abstract
The research work is about the modern computer technology and their impart on statistical analysis. Some works have been done concerning approaches to the analysis of survey data and modern approaches to the analysis of experimental data. Previously users were often distracted form their direct needs of learning how to process their data, by the more pressing software. There was much to lean because of the varied methods that depended on the types of data.In this “new world’ we hope that users will find both the statistical ideas and the analysis of their work. We hope this guide has indicated when project objectives and data might benefit form these methods despite the considerable challenge in using them unaided.On the major side of findings, conclusion and recommendation, modern computer technology has a great impact on statistical analysis, this is because it makes data easier to process and recommendations were drawn for the improvement of statistical analysis.
TABLE OF CONTENTS
Title page————————————————- i
Approval page——————————————- ii
Dedication———————————————– iii
Acknowledgement————————————– iv
Table of contents————————————— v
Abstract————————————————- vii
CHAPTER ONE
- Introduction————————————– 1
- Statement of the problem———————- 3
- Research Questions—————————– 3
- Justification of study————————— 3
- Scope of the study—————————– 4
- Objective of the study————————- 4
CHAPTER TWO
- Literature Review—————————— 5
2.1 Introduction———————————— 5
2.2 Exploratory methods————————— 5
2.3 Multivariate methods————————– 7
2.4 Cluster analysis——————————– 9
2.5 Principal component analysis—————– 12
2.6 Generalized linear Methods——————- 14
2.7 Multilevel models—————————— 17
CHAPTER THREE
- Methodology———————————- 20
3.1 Introduction———————————- 20
3.2 Sample size and why———————— 20
3.3 Resource material————————— 21
3.4 The research design adopted————— 21
3.5 Limitations of the study——————– 22
3.6 Definitions of terms———————— 22
CHAPTER FOUR
- Presentation and analysis of data——— 24
4.1 Introduction——————————– 24
4.2 Data analysis technique——————- 24
4.3 Data presentation————————- 24
4.4 Data analysis—————————– 28
CHAPTER FIVE
- Summary, Findings, Conclusion
and Recommendation——————- 31
5.1 Introduction—————————– 31
5.2 Summary——————————– 31
5.3 Findings——————————— 32
5.4 Conclusion—————————— 33
5.5 Recommendations———————- 34
References—————————— 36
CHAPTER ONE
- INRODUCTION
This is the third guide concerned with the analysis of research data. The ideas apply whatever the method of data collection. They extend the methods described in the basis guides titled Approaches to the Analysis of survey data a modem approaches to the analysis of experimental data.
The previous guides were both concerned with methods of analysis that researchers should be able to handle themselves. They showed that a large proportion of the analysis often only involved descriptive methods. But research studies do normally includes some elements of generalizing form the sampled data to a larger population. This generalization requires the notions of “statistical inference” which are described in the guide confidence and significance key concepts of inferential statistics.
We first distinguish between “the modern approaches” that are outlined in the basic guides and the “modern methods” that we describe here. The former consists mainly of methods that were already available in pre-computer days some were not easy to apply without running into computational difficulties. Current computing software has taken away the strain and the methods can now be used easily.
The methods described in this guide are technically more advanced and are not practical without modern computer software. They are rarely applied in non- statistical research. We describe the most important of these methods and illustrate their uses. Our aim is to permit users to asses whether any of this method would be of valued for their analysis. We concentrate on two areas. These are modern exploratory tools applicable at initial stages of the analysis. Descriptive multivariate techniques, extensions of regression, modeling to generalized linear, models and multi level modeling techniques.
1.2 STATEMENT OF THE PROBLEM
Here the statement of the problems includes the approaches to the analysis of survey data and analysis of experimental data. This generalization requires the notion of statistical inference which are described in the guide as confidence and significance being the key concepts of inferential statistics.
