Research Methods and Statistics for Cross-Cutting Research : Handbook for Multidisciplinary Research.

Format:

Book

Author/Creator:

Matanda, Ephraim, author.

Mawere, Munyaradz, author.

Language:

English

Subjects (All):

Research--Methodology.

Research.

Physical Description:

1 online resource (254 pages)

Edition:

1st ed.

Place of Publication:

African Books Collective 2022

Summary:

This book is on research methods and statistics for cross-cutting research. Framed from a multi-disciplinary perspective, the book presents and grapples with research methods and approaches used in research across disciplines. It magnifies the different contexts where research methods intersect and complement each other for effective data collection and analysis. Noting that most of the texts on research are field or subject specific regardless of the fact that most research methods and approaches today are complementary and overlapping, the book advances the argument that it is high time that researchers consider producing and using research texts that are multi-disciplinary and promote generative dialogue across fields. The novelty and richness of the book lie in its attempt to offer nuanced research methods and statistics, all in one book, which can be used in different disciplines and situations. More importantly and without romanticising the potential of multi-disciplinary research, the book offers added insights and pointers on trends and evolutions in contemporary research. The book is an important addition to debates on contemporary research and multi-disciplinary discourses that have taken centre stage in recent years in many universities across the world. The book is handy to students and practitioners across fields.

Contents:

Cover

Title page

Copyright page

About the Authors

Dedication

Acknowledgements

Contents

Foreword

PART A: RESEARCH ACROSS DISCIPLINES

Chapter 1 - Research Concept and Theories

Introduction

The concept of research

Characteristics of research

Types of research

Purpose of research

Research designs and methods

Research design

Research theories

Advantages of deductive approach

Difference between deductive and inductive approaches

Different types of inductive theory

Conclusion

Chapter 2 - Academic Research Proposal

Developing an academic research proposal

Topic or title

Background to the study

Problem statement/Statement of the problem

Research questions

Research objectives

Hypothesis of the study

Assumptions of the study

Research rationale

Scope or Delimitations of the study

Limitations of the study

Definitions of key terms

Theoretical/Conceptual framework

Literature review

Research methodology

Ethical considerations

Academic research proposal formulation processes

Step 1: Identification of the problem/opportunity

Step 2: Statement of problem

Step 3: Research hypothesis &amp

assumptions

Step 4: Detailed literature review

Step 5: Research methodology

Step 6: Data collection methods

Step 7: Data presentation &amp

analysis

Step 8: Conclusions and recommendations of the study

Step 9: Theoretical Formulations

Step 10: Research Time and Resources Budget

Chapter 3 - Business Research Proposal

Conceptualisation of business research proposal

Types of business research proposals

The importance of a business research proposal to entrepreneurs

When is business research proposal written/formulated?.

Format/Structure of a business research proposal

Distinction between business and academic research proposals

PART B: RESEARCH DESIGNS

Chapter 4 - Research Designs

Central elements of research designs

Essential characteristics of a good research design

Common types of research designs

Grouping of research designs

Identification of research designs

Types of research statistics

Mean of a set of data

Regression analysis

Skewness of data

Kurtosis

Variance

Chapter 5 - Qualitative Research

Characteristics of qualitative research

Conditions for use of qualitative research methods

Types of qualitative research methods

Categories of qualitative research

Characteristics of descriptive research

Data collection and analysis in qualitative research

Application of qualitative research methods

Chapter 6 - Quantitative Research

Understanding quantitative research

a). Primary quantitative research

b). Secondary quantitative research methods

Survey distributions and data collection

Types of quantitative research

Comparison of explanatory and descriptive research

Characteristics of quantitative research

Best practices to conduct quantitative research

Quantitative data and generalisation of results

Comparing quantitative and qualitative research

Chapter 7 - Mixed Research Across Disciplines

Mixed research designs

Fundamentals and types of mixed research designs

a). Mixed-methods research

b). Design research

c). Sequential explanatory design

d). Sequential exploratory design

e). Concurrent triangulation design

f). Concurrent nested research design

Advantages and disadvantages of concurrent nested research design.

Conditions for use of mixed methods designs

Characteristics of mixed methods designs

Uses of mixed methods research designs

Advantages of using mixed research

Disadvantages of using mixed research

Mixed research design proposals

a). Gather data and conduct research

b). Draft an outline of the proposal

Types of action research designs

a). Individual research

b). Collaborative research

c). School-wide research

d). District-wide research

Small Business Survey Research

a). Survey research

b). Rationale for use of surveys

The importance of market research

Primary, secondary and tertiary stakeholders

a). Stakeholder analysis

b). Primary stakeholders

c). Secondary stakeholders

d). Tertiary stakeholders

PART C: DATA COLLECTION, PRESENTATION AND ANALYSIS

Chapter 8 - Data Collection Instruments And Methods

Instruments used in collection of data

Advantages of self-Administered questionnaires

a). Involve considerably low cost

b). Can be used for large samples

c). Provide room for greater anonymity

d). Less chance of biasing error

e). Have a standardized wording

f). Make it easy to locate respondents

g). They are time saving

h). They are convenient to respondents

i). Make it easier for the researcher to secure information

j). Allow greater accessibility to respondents

Disadvantages of self-administered questionnaires

a). Low response rate

b). Probing of questions

c). Completion of questionnaires

d). Limitations of the questionnaires

e). Inflexibility

f). Verbal behaviours

g). Reasons for refusal not known

h). No control over the sequence

i). No control over the environment

j). High item non-response bias

k). Cannot record spontaneous answers

l). No way to supplement the answers.

m). No way to check the correct identity of the respondents

n). Dealing with Non-Response in Mailed Interviews

Improving response rates in mail surveys

Electronic self-administered questionnaires

E-mail interviews

Internet interviews

Categories of Research Interviews

Advantages of personal interviews

Disadvantages of personal interviews

Interview approaches or techniques

Conditions for successful interviews

Dealing with interview problems

Dealing with non-responses

Measurement errors

Telephone interview methods

Benefits of telephone interviews

Data collection methodologies

Data sampling methods

Data collection techniques

Chapter 9 - Data Presentation and Analysis Techniques

Presentation of research data

Normal distribution and its characteristics

Standard normal distribution curve

Tests of significance

Regression and correlation analyses

Data analysis techniques

Testing data for reliability

Data validity tests

Sources of sampling errors

Research Variables

PART D: INFERENTIAL STATISTICS AND PARAMETRIC TESTS

Chapter 10 - Descriptive Statistics for Sample Data

Theory of descriptive statistics

Levels of measurement in statistics

Nominal scale of measurement

Ordinal scale of measurement

Interval scale of measurement

Ratio scale of measurement

Ungrouped and grouped sample data

Measures of central tendency for ungrouped data

Measures of central tendency for grouped data

Measures of position for ungrouped data

Measures of position for grouped data

Measures of dispersion for ungrouped data

Measures of dispersion for grouped data

Chapter 11 - Descriptive Statistics for Population Data

Measures of central tendency for population data.

Measures of position for population data

Measures of dispersion of population data

Chapter 12 - Graphical Representation of Statistical Data

Bar charts and histograms

Data representation by stem and leaf plots

Data representation by pie charts

Histograms and frequency polygons

Box and whisker plots

Cumulative frequency curves or ogives

Chapter 13 - Estimations and Confidence Intervals in Inferential Statistics

Descriptive and Inferential Statistics

Application of inferential statistics

Estimation of population mean and variance

Estimation of population proportions

Confidence Intervals

Confidence intervals under Z distribution

Confidence intervals under student's t-distribution

Chapter 14 - Descriptive Statistics And Parametric Tests

Application of hypothesis in inferential statistics

Hypothesis testing using Z-distribution

Hypothesis Testing Using Student's t Distribution

Pooled variances and hypothesis testing

Chi-Square tests for goodness of fit

Chapter 15 - Conclusion

References

Back cover.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

9956-552-11-9

OCLC:

1347026402