Using a truly accessible and reader-friendly approach, this comprehensive introduction to statistics redefines the way statistics can be taught and learned. Unlike other books that merely focus on procedures, Reid’s approach balances development of critical thinking skills with application of those skills to contemporary statistical analysis. He goes beyond simply presenting techniques by focusing on the key concepts readers need to master in order to ensure their long-term success. Indeed, this exciting new book offers the perfect foundation upon which readers can build as their studies and careers progress to more advanced forms of statistics. Keeping computational challenges to a minimum, Reid shows readers not only how to conduct a variety of commonly used statistical procedures, but also when each procedure should be utilized and how they are related. Following a review of descriptive statistics, he begins his discussion of inferential statistics with a two-chapter examination of the Chi Square test to introduce students to hypothesis testing, the importance of determining effect size, and the need for post hoc tests. When more complex procedures related to interval/ratio data are covered, students already have a solid understanding of the foundational concepts involved. Exploring challenging topics in an engaging and easy-to-follow manner, Reid builds concepts logically and supports learning through robust pedagogical tools, the use of SPSS, numerous examples, historical quotations, insightful questions, and helpful progress checks.

# Finding Differences With Interval and Ratio Data—II : The Independent Samples t Test and the Dependent Samples t Test

### Finding Differences With Interval and Ratio Data—II : The Independent Samples t Test and the Dependent Samples t Test

Science is simply common sense at its best, that is, rigidly accurate in observation, and merciless to fallacy in logic.

—Thomas Huxley

This chapter will cover two of the most commonly employed statistical tests. Both are conceptually similar and, as you will see, each is closely related to the one-sample t test that was reviewed in Chapter 9. The first of these tests is called the independent samples t test. After discussing this procedure, we will turn to the dependent samples t test. These tests are underlined in Table 10.1.

### Independent Samples t Test

We often see studies that compare one group of subjects that receives a treatment with ...