Statistics For Psychology

One of the best things you can do in college is to build your personal library. You can Google, Yahoo or Bing everything else but you should have a few good books on your shelf. You need a general psych book, one on learning, an abnormal or personality text (to help explain your friends and relatives), and a good stat book. For the last category, here’s one you should consider.

Here is a good, hardcover, standard statistics text. It’s the fifth edition, so it’s been around long enough to get the kinks out. And it has been recently updated (2008), so it can last you for a long time. And it’s got what I’ve come to expect from Pearson (one of my favorite publishers): good paper, great graphics, and not overly flashy. It’s two-color, which is enough to give the pages some interest but not so colorful as to be distracting.

Aron, Aron & Coups do a good job with the material. It’s pretty straightforward. It’s not great writing–compared to me, of course J–but it won’t wear you out. Stats is best when presented straight ahead, and this trio pretty much does that. It doesn’t spend as much time on when to use what technique, or what the underlying assumptions are, but that’s not uncommon. This is a very serviceable book, and I give it high marks.

Aron, Arthur, Aron, Elaine & Coups, Elliot
Statistics for Psychology
1994-2009
5^th edition

Table of Contents
    Chapter 1: Displaying the Order In a Group of Numbers
          See Day 1: Measurement
    Chapter 2: The Mean, Variance, Standard Deviation and Z Scores
          See Day 2: Central Tendency
          See Day 3: Dispersion
          See Day 4: z scores
    Chapter 3: Some Key Ingredients for Inferential Statistics
    Chapter 4: Introduction to Hypothesis Testing
            See Day 1: Measurement
    Chapter 5: Hypothesis Tests With Means of Samples
    Chapter 6: Making Sense of Statistical Significance
          See Day 7: Probability
    Chapter 7: Introduction to the t Test
    Chapter 8: The t Test For Independent Means
          See Day 8: Independent t-Test
    Chapter 9: Introduction to the Analysis of Variance
          See Day 9: One-way ANOVA
    Chapter 10: Factorial Analysis of Variance
          See Day 10: Advanced Procedures
    Chapter 11: Correlation
          See Day 5: Correlation
    Chapter 12: Prediction
          See Day 6: Regression
    Chapter 13: Chi-Square Tests
    Chapter 14: Strategies When Population Distributions Are Not Normal
    Chapter 15: Making Sense of Advd Stat Procedures in Research Articles
          See Day 10: Advanced Procedures