The Modern Computer Technology And Their Impact On Statistical Analysis

Project and Seminar Material for Mathematics and Statistics

The Modern Computer Technology And Their Impact On Statistical Analysis


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


Preliminary Page(s)

  • Title page
  • Approval page
  • Dedication
  • Acknowledgement
  • Table of contents
  • Abstract

Chapter One

1.0 Introduction

  • 1.1 Background of the study
  • 1.2 Statement of the problem
  • 1.3 Research Questions
  • 1.4 Justification of study
  • 1.5 Scope of the study
  • 1.6 Objective of the study

Chapter Two

2.0 Literature Review

  • 2.1 Introduction
  • 2.2 Exploratory methods
  • 2.3 Multivariate methods
  • 2.4 Cluster analysis
  • 2.5 Principal component analysis
  • 2.6 Generalized linear Methods
  • 2.7 Multilevel models

Chapter Three

3.0 Methodology

  • 3.2 Sample size and why
  • 3.3 Resource material
  • 3.4 The research design adopted
  • 3.5 Limitations of the study
  • 3.6 Definitions of terms

Chapter Four

4.0 Presentation and Analysis of Data

  • 4.1 Introduction
  • 4.2 Data analysis technique
  • 4.3 Data presentation
  • 4.4 Data analysis

Chapter Five

5.0 Summary, Findings, Conclusion and Recommendation

  • 5.1 Introduction
  • 5.2 Summary
  • 5.3 Findings
  • 5.4 Conclusion
  • 5.5 Recommendations
  • References

Chapter One


1.0 Introduction

1.1 Background Of The Study

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.


1.3 Research Question

This is one of a series of guides for research and support staff involved in natural resources projects. The subject matter here is modern computer. Technology and their input on statistical analysis.


1.4 Justification Of Study

This research is important to the readers and statisticians, as it reaches forth compendium on result of the research work carried on the modern methods of analysis.

To the readers who are opportune to read this research work, it will acquaint him/her on the modern methods of analysis.

To the statistician, the findings and recommendations will be a focus point each time they needs the modern methods of analysis in their work.


1.5 Scope Of The Study

The research work was gotten from the internet through the statistical good practice guidelines.

The work was studied in order to reduce constraint (limitations) that may limit the research work and we were able to generalize the entire work.


1.6 Objective Of The Study

Consequently upon the identified problems of this study, the research had the basis objective measures of;

  1. To know the modern exploratory tools applicable at initial stages of data analysis
  2. To know descriptive multivariate data techniques.

Chapter Five


5.0 Summary Of Findings, Conclusions And Recommendations

5.1 Introduction

This chapter focuses on the summary of findings, conclusions and recommendation resulting form the field study conducted in the question selected from the researcher work.


5.2 Summary

However, in the course of this study, the modern computer technology and their impact on statistical analysis, the researcher was subjected to the modern methods of analysis on the review, according to the statistical good practice guidelines, current computing software has taken away the strain and the methods can now be used early.

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 use.


5.3 Findings

  1. From the research conducted, it was observed that modern computer technology has a greater impact on statistical analysis as it permits users to asses any of method easily for their analysis.
  2. Some of the methods described were not easy to apply without running into computerization difficulties.
  3. Exploratory Methods in modern computer software enables the researcher to examine large datasets, since they are harder to handle, but by that means you examine the data, rather than avoiding them.
  4. The common use of multivariate methods is about the exploratory tools that help the researcher to find hidden structures in your data especially during statistical analysis.
  5. In the multivariate methods under cluster analysis it is found that cluster analysis is a two-step process. The first step is to find a measure of similarity (or dissimilarity) between the respondents. The second step is to decide how the cluster are to be formed.
  6. Hence often the cluster analysis will rediscover structure that is well known, but was not used in the analysis.
  7. It is sometimes valuable to find that structure of the study is confirmed by the data, i.e. people within the same village are more similar than people in different, villages but that is rarely a key point in the analysis.
  8. It is found that one of the major difficulties with principal component analysis is the need to give a sensible interpretation to each of the components which summarizes the data.

5.4 Conclusion

Until recently it has also been quite difficult to use statistical software for the data analysis. Particularly if the analysis was not sample. Each statistics package had its own language, and their required both statistical and computing skills to master. The time needed was such that, statistician apart, users would not consider learning more than one package.

This has also changed. Data can now easily be transferred between packages and it is straightforward to use a variety of statistical software, to a reasonable level, without learning the underlying language.


5.5 Recommendations

However, after thorough check of the result of this study, it should be noted that the impart on statistical analysis. In the light of the above the following recommendations were made.

  1. The value of these modern techniques is in giving more insights than simpler analysis where they do not; it is advisable to stick with simpler approaches that may be easier to explain in reports.
  2. Since a common feature of all these models is that they involve a data transformation and a specific distribution describing its variability. I recommend that modern computer technology on statistical analysis to be sufficiently well accepted by statisticians.
  3. When the key measurement is a categorical response involving more than two categories, e.g. low medium high recommend that that data can be modeled using log-linear modeling techniques as it is a modern computer software for statistical analysis.
  4. Moreover, I recommend for further research on the effect of modeling on statistical analysis.

The Modern Computer Technology And Their Impact On Statistical Analysis


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