Lectures (Video)
- 1. Sampling and Data
- 2. Descriptive Statistics
- 3. Probability Topics
- 4. Discrete Distributions
- 5. Continuous Random Variables
- 6. The Normal Distribution
- 7. The Central Limit Theorem
- 8. Confidence Intervals
- 9. Hypothesis Testing - Single Mean and Single Proportion
- 10. Hypothesis Testing - Two Means, Two Proportions, Paired Data
- 11. The Chi-Square Distribution
- 12. Linear Regression and Correlation
Introduction to Statistics II
Course Summary
This course is based on Collaborative Statistics made available by Connexions under the Creative Commons Attribution 2.0 license.
This is an introduction to data analysis course that makes use of graphical and numerical techniques to study patterns and departures from patterns. The student studies randomness with emphasis on understanding variation, collects information in the face of uncertainty, checks distributional assumptions, tests hypotheses, uses probability as a tool for anticipating what the distribution of data may look like under a set of assumptions, and uses appropriate statistical models to draw conclusions from data. The lectures were conducted by Dr. Barbara Illowsky. The lectures are based on the book Collaborative Statistics which is available online for viewing or download.
The course introduces the student to applications in engineering, business, economics, medicine, education, the sciences, and other related fields. The use of technology (computers or graphing calculators) will be required in certain applications.
Reading Material
1. Collaborative StatisticsIllowsky, B., & Dean, S. 2009. Collaborative Statistics. Connexions, January 16, 2009.
Collaborative Statistics was written by Barbara Illowsky and Susan Dean, faculty members at De Anza College in Cupertino, California. The textbook was developed over several years and has been used in regular and honors-level classroom settings and in distance learning classes. This textbook is intended for introductory statistics courses being taken by students at two- and four-year colleges who are majoring in fields other than math or engineering. Intermediate algebra is the only prerequisite. The book focuses on applications of statistical knowledge rather than the theory behind it.
(This free ebook can be viewed online and downloaded at the above link.)
Course Material
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