Essentials of Statistics for the Behavioral Sciences
Essentials of Statistics for the Behavioral Sciences by Susan Nolan and Thomas Heinzen is a concise, readable text that covers key statistical concepts. Exploring its wide variety of creative, step-by-step examples, students using Essentials will learn how to choose the appropriate statistical test, understand its conceptual significance, and calculate each statistic. With inviting examples using real-world data, the text teaches students to apply concepts and formulas to statistical questions that they will encounter in their academic lives and outside the classroom.
The clear, accessible explanations highlight a conceptual understanding of statistics that minimize the mathematical. Nolan and Heinzen’s brief text also provides the most opportunities for students to evaluate their understanding, with three tiers of exercises —Clarifying the Concepts, Calculating the Statistic, and Applying the Concepts— integrated after each major topic as well as at the end of each chapter.
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An Introduction to Statistics and Research Design
Visual Displays of Data
Central Tendency and Variability
Sampling and Probability
The Normal Curve Standardization and z Scores
Hypothesis Testing with z Tests
Confidence Intervals Effect Size and Statistical Power
Chi Square and Other Nonparametric Tests
Reference for Basic Mathematics
Answers to the OddNumbered EndofChapter Exercises
Answers to the Check Your Learning Exercises
Choosing the Right Statistical Test
Writing an APA Results Section
a p level a z score assumptions average bar graph cell Chapter CHECK YOUR LEARNING chi-square test Cohen’s column comparison distribution conduct confidence interval critical value cutoff degrees of freedom determine dftotal difference between means distribution of means effect size estimate exam grade example Exercise F statistic fail to reject Figure frequency table gender histogram hypothesis test independent variable independent-samples t test indicate inferential statistics interaction main effect MASTERING THE FORMULA mean difference median negative nominal variable normal curve normally distributed null hypothesis ofthe one-way between-groups ANOVA participants Pearson correlation coefficient percentage percentile population mean predict random assignment raw score regression equation reject the null relation research hypothesis sample mean scale variable scatterplot six steps skewed SStotal standard deviation standard error statistical power statistically significant steps of hypothesis subtract sum of squares symbol test statistic tion ttest two-tailed test z score