# 1. Time and Location

• Time: 10:10 - 12:00, Friday

• Location: Room 202, Teaching Building 2

• Lecturer: Likan Zhan

# 2. Course Information

Statistical procedures provide researchers with objective and systematic methods for describing and interpreting their research results. Scientific research is the system that we use to gather information, and statistics are the tools that we use to distill the information into sensible and justified conclusions. The goal of this course is not only to teach the methods of statistics, but also to convey the basic principles of objectivity and logic that are essential for science and valuable for decision making in everyday life.

This course is an introductory course of Statistics for the the Behavioral Sciences. A primary goal of this course is to make the task of learning statistics as easy and painless as possible. Topics of this course include Frequency Distribution, Centtral Tendency, Variability, z-scores, Probability and Samples, Hypothesis Testing, t-test, ANOVA, Correlation, Regression, Chi-Square test, and Binomal test etc. At the end of the course you should be able to read behavioural research that uses basic statistical methods; to undertake elementary data analysis; and to take more advanced courses in statistics, such as the course R for Modeling and Visualizing Data. More specifically, you will learn:

• to summarize statistical data and to discover patterns in data;
• to draw inferences from a sample to a larger population from which the sample was drawn; and
• to use the computer software R to analyze statistical data.

# 4. Syllabus and Lecture Notes

• Part I. Introduction and Descriptive Statistics
• Chapter 01. Introduction to Statistics. Slides
• Chapter 02. Frequency Distributions. Slides
• Chapter 03. Central Tendency. Slides
• Chapter 04. Variability. Slides
• Part II. Foundations of Inferential Statistics
• Chapter 05. z-Scores: Location of Scores and Standardized Distributions. Slides
• Chapter 06. Probability. Slides
• Chapter 07. Probability and Samples: The Distribution of Sample Means. Slides
• Chapter 08. Introduction to Hypothesis Testing. Slides
• Part III. Using t-Statistics for Inferences
• Chapter 09. Introduction to the t Statistic. Slides
• Chapter 10. The t Test for Two Independent Samples. Slides
• Chapter 11. The t Test for Two Related Samples. Slides
• Part IV. Analysis of Variance
• Chapter 12. Introduction to Analysis of Variance. Slides
• Chapter 13. Repeated-Measures Analysis of Variance. Slides
• Chapter 14. Two-Factor Analysis of Variance (Independent Measures).
• Part V. Correlations and Nonparametric Tests
• Chapter 15. Correlation.
• Chapter 16. Introduction to Regression.
• Chapter 17. The Chi-Square Statistic: Tests for Goodness of Fit and Independence
• Chapter 18. The Binomial Test

# 5. Examination

• Time and location: 08:00-09:50, July 13, Room 104, Teaching Building 4;
• Structure of the exam: 65 multiple choices, selected from the learning check problems of chapters 1 - 13; 2 essay questions, selected from the odd-numbered problems of chapters 9 - 13.