Understanding Quantitative Data in Educational Research

Nicoleta Gaciu - Oxford Brookes University, UK
Understanding Quantitative Data in Educational Research
November 2020 | 376 pages | Sage UK
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Description

This book is designed to help Education students gain confidence in analysing and interpreting quantitative data and using appropriate statistical tests, by exploring, in plain language, a variety of data analysis methods.

Highly practical, each chapter includes step-by-step instructions on how to run specific statistical tests using R, practical tips on how to interpret results correctly and exercises to put into practice what students have learned.

It also includes guidance on how to use R and RStudio, how to visualise quantitative data, and the fundamentals of inferential statistics, estimations and hypothesis testing.

Nicoleta Gaciu is Senior Lecturer in Education at Oxford Brookes University.

Contents

Part 1: Understanding quantitative data and R

  • 1. Introduction to information, knowledge and quantitative data
  • 2. An introduction to R and RStudio

Part 2: Data visualisation

  • 3. Graphical representation of data

Part 3: Providing information about data

  • 4. Descriptive statistics
  • 5. Measures of dispersion and distributions
  • 6. Normal distribution and standardised scores

Part 4: Making estimations and predictions from the data

  • 7. Fundamentals of inferential statistics
  • 8. Estimations and hypothesis testing

Part 5: From sample to population

  • 9. One-sample tests
  • 10. Differences between the independent or dependent two samples
  • 11. Difference between more than two independent samples
  • 12. Difference between more than two dependent samples

Part 6: Relationships and predictions

  • 13. Relationship between variables
  • 14. Predictions for independent and dependent variables

Description

This book is designed to help Education students gain confidence in analysing and interpreting quantitative data and using appropriate statistical tests, by exploring, in plain language, a variety of data analysis methods.

Highly practical, each chapter includes step-by-step instructions on how to run specific statistical tests using R, practical tips on how to interpret results correctly and exercises to put into practice what students have learned.

It also includes guidance on how to use R and RStudio, how to visualise quantitative data, and the fundamentals of inferential statistics, estimations and hypothesis testing.

Nicoleta Gaciu is Senior Lecturer in Education at Oxford Brookes University.

Contents

Part 1: Understanding quantitative data and R

  • 1. Introduction to information, knowledge and quantitative data
  • 2. An introduction to R and RStudio

Part 2: Data visualisation

  • 3. Graphical representation of data

Part 3: Providing information about data

  • 4. Descriptive statistics
  • 5. Measures of dispersion and distributions
  • 6. Normal distribution and standardised scores

Part 4: Making estimations and predictions from the data

  • 7. Fundamentals of inferential statistics
  • 8. Estimations and hypothesis testing

Part 5: From sample to population

  • 9. One-sample tests
  • 10. Differences between the independent or dependent two samples
  • 11. Difference between more than two independent samples
  • 12. Difference between more than two dependent samples

Part 6: Relationships and predictions

  • 13. Relationship between variables
  • 14. Predictions for independent and dependent variables
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Understanding Quantitative Data in Educational Research

Nicoleta Gaciu
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November 2020 | 376 pages | Sage UK

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This book is designed to help Education students gain confidence in analysing and interpreting quantitative data and using appropriate statistical tests, by exploring, in plain language, a variety of data analysis methods.

Highly practical, each chapter includes step-by-step instructions on how to run specific statistical tests using R, practical tips on how to interpret results correctly and exercises to put into practice what students have learned.

It also includes guidance on how to use R and RStudio, how to visualise quantitative data, and the fundamentals of inferential statistics, estimations and hypothesis testing.

Nicoleta Gaciu is Senior Lecturer in Education at Oxford Brookes University.


Table Of Contents:

  • Part 1: Understanding quantitative data and R
  • 1. Introduction to information, knowledge and quantitative data
  • 2. An introduction to R and RStudio
  • Part 2: Data visualisation
  • 3. Graphical representation of data
  • Part 3: Providing information about data
  • 4. Descriptive statistics
  • 5. Measures of dispersion and distributions
  • 6. Normal distribution and standardised scores
  • Part 4: Making estimations and predictions from the data
  • 7. Fundamentals of inferential statistics
  • 8. Estimations and hypothesis testing
  • Part 5: From sample to population
  • 9. One-sample tests
  • 10. Differences between the independent or dependent two samples
  • 11. Difference between more than two independent samples
  • 12. Difference between more than two dependent samples
  • Part 6: Relationships and predictions
  • 13. Relationship between variables
  • 14. Predictions for independent and dependent variables

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