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.

# Describing Interval and Ratio Data—II : Further Descriptive Statistics Used With Interval or Ratio Data

### Describing Interval and Ratio Data—II : Further Descriptive Statistics Used With Interval or Ratio Data

The most important questions of life are, for the most part, really only problems of probability.

—Pierre-Simon, marquis de Laplace

In Chapter 3, we dealt with the variance and standard deviation (SD) of a population. Fortunately, the situation is virtually identical if you are dealing with a sample. As you recall, a sample is a subset of a population. In our example with the basketball players that began with Table 3.6, we were only interested in the heights of the five starting players. They thus constituted a population. Let us assume, instead, that there were 20 basketball players and our 5 players were chosen from this group. Our 5 players would ...