ABSTRACT

Making Sense of Statistics is the ideal introduction to the concepts of descriptive and inferential statistics for students undertaking their first research project. It presents each statistical concept in a series of short steps, then uses worked examples and exercises to enable students to apply their own learning.

It focuses on presenting the why as well as the how of statistical concepts, rather than computations and formulae, so is suitable for students from all disciplines regardless of mathematical background. Only statistical techniques that are almost universally included in introductory statistics courses, and widely reported in journals, have been included. Once students understand and feel comfortable with the statistics that meet these criteria, they should find it easy to master additional statistical concepts.

New to the Seventh Edition

Retaining the key features and organization that have made this book an indispensable text for teaching and learning the basic concepts of statistical analysis, this new edition features:

  • discussion of the use of observation in quantitative and qualitative research
  • the inclusion of introductions to the book, and each Part.
  • section objectives listed at the beginning of each section to guide the reader.
  • new material on key topics such as z-scores, probability, Central Limit Theorem, Standard Deviation and simple and multiple regression
  • Expanded discussion on t test with separate sections for independent and dependent samples t tests, as well as one-sample t test
  • progressive analysis of bivariate vs multivariate statistics (starts with the basic concepts and moves to more complex analysis as the student progresses)
  • updated and extended pedagogical material such as Chapter Objectives, exercises and worked examples to test and enhance student’s understanding of the material presented in the chapter
  • Bolded key terms, with definitions and Glossary for quick referral
  • expanded Appendices include a brief reference list of some common computational formulas and examples.
  • a Glossary of key terms has been added at the end of the book, with references to sections in parenthesis.
  • New online instructor resources for classroom use consisting of test bank questions and Powerpoint slides, plus material on basic math review

chapter |3 pages

Introduction: What is Research?

part A|19 pages

The Research Context

chapter 1|5 pages

The Empirical Approach to Knowledge

chapter 2|4 pages

Types of Empirical Research

chapter 3|5 pages

Scales of Measurement

part B|24 pages

Sampling

chapter 5|5 pages

Introduction to Sampling

chapter 6|6 pages

Variations on Random Sampling

chapter 7|5 pages

Sample Size

chapter 8|6 pages

Standard Error of the Mean

part C|34 pages

Descriptive Statistics

chapter 9|3 pages

Frequencies, Percentages, and Proportions

chapter 10|5 pages

Shapes of Distributions

chapter 11|4 pages

The Mean: An Average

chapter 12|6 pages

Mean, Median, and Mode

chapter 13|5 pages

Range and Interquartile Range

chapter 14|5 pages

Standard Deviation

chapter 15|4 pages

z Score

part D|21 pages

Correlational Statistics

chapter 16|6 pages

Correlation

chapter 17|4 pages

Pearson r

chapter 18|9 pages

Scattergram

part E|14 pages

Inferential Statistics

chapter 19|6 pages

Introduction to Hypothesis Testing

chapter 20|6 pages

Decisions about the Null Hypothesis

part F|44 pages

Means Comparison

chapter 21|7 pages

Introduction to the t Test

chapter 22|6 pages

Independent Samples t Test

chapter 23|5 pages

Dependent Samples t Test

chapter 24|4 pages

One Sample t Test

chapter 25|5 pages

Reports of the Results of t Tests

chapter 26|7 pages

One-Way ANOVA

chapter 27|8 pages

Two-Way ANOVA

part G|36 pages

Predictive Significance

chapter 28|6 pages

Chi-Square Test

chapter 29|6 pages

Limitations of Significance Testing

chapter 30|6 pages

Effect Size

chapter 31|5 pages

Coefficient of Determination

chapter 32|5 pages

Multiple Correlation

chapter 33|6 pages

Simple and Multiple Regression