This collection contains the California Open Educational Resources Council (COERC) list of peer-reviewed textbooks for Introduction to Statistics (common course-id MATH 110) , one of the top 50 college courses identified for inclusion in the California Open Online Library for Education (COOLforEd).
General Course Description: MATH 110: Introduction to Statistics
The use of probability techniques, hypothesis testing, and predictive techniques to facilitate decision-making. Topics include descriptive statistics; probability and sampling distributions; statistical inference; correlation and linear regression; analysis of variance, chi-square and t-tests; and application of technology for statistical analysis including the interpretation of the relevance of the statistical findings. Applications using data from disciplines including business, social sciences, psychology, life science, health science, and education.
Minimum Units: 3.0
Any rationale or comment:
Typically satisfies general education quantitative reasoning requirement (CSU GE B4).
Summarizing data graphically and numerically;
Descriptive statistics: measures of central tendency, variation, relative position, and levels/scales of measurement;
Sample spaces and probability;
Random variables and expected value;
Sampling and sampling distributions;
Discrete distributions – Binomial;
Continuous distributions – Normal;
The Central Limit Theorem;
Estimation and confidence intervals;
Hypothesis Testing and inference, including t-tests for one and two populations, and Chi-square test;
Correlation and linear regression and analysis of variance (ANOVA);
Applications using data from disciplines including business, social sciences, psychology, life science, health science, and education; and
Statistical analysis using technology such as SPSS, EXCEL, Minitab, or graphing calculators.
Laboratory Activities (if applicable):
Upon successful completion of the course, students will be able to:
Distinguish among different scales of measurement and their implications;
Interpret data displayed in tables and graphically;
Apply concepts of sample space and probability;
Calculate measures of central tendency and variation for a given data set;
Identify the standard methods of obtaining data and identify advantages and disadvantages of each;
Calculate the mean and variance of a discrete distribution;
Calculate probabilities using normal and student’s t-distributions;
Distinguish the difference between sample and population distributions and analyze the role played by the Central Limit Theorem;
Construct and interpret confidence intervals;
Determine and interpret levels of statistical significance including p-values;
Interpret the output of a technology-based statistical analysis;
Identify the basic concept of hypothesis testing including Type I and II errors;
Formulate hypothesis tests involving samples from one and two populations;
Select the appropriate technique for testing a hypothesis and interpret the result;
Use linear regression and ANOVA analysis for estimation and inference, and interpret the associated statistics; and
Use appropriate statistical techniques to analyze and interpret applications based on data from disciplines including business, social sciences, psychology, life science, health science, and education.
Methods of Evaluation:
Tests, examinations, homework or projects where students demonstrate their mastery of the learning objectives and their ability to devise, organize and present complete solutions to problems.
Illowsky and Dean’s one-semester open textbook is geared towards students not majoring in math and science and focuses on the applications of statistical knowledge rather than the theory behind it. Based on the widely adopted Collaborative Statistics by the same authors, this new version has enhancements in artwork, terminology, and practical applications to enhance the relevance and accessibility for students. The text also includes collaborative exercises, integration with TI-83,83+,84+ calculators, technology integration problems, and statistics labs.
Developed by Rice University, University of Houston at Clear Lake, and Tufts University, this open textbook is a public domain resource for learning and teaching introductory statistics. It contains material presented in textbook format and as video presentations. This resource features interactive demonstrations and simulations, case studies, and an analysis lab.
Shafer and Zhang’s open textbooks is designed as a one-semester statistics course for general education students. The authors believe that students in this course are best served by a focus on the core material and not by an exposure to a plethora of peripheral topics. Therefore in writing this book they sought to present material that comprises fully a central body of knowledge that is defined according to convention, realistic expectation with respect to course duration and students’ maturity level, and their professional judgment and experience.
Each chaper features learning objectives, definitions, key takeaways, exercises, and answers to the exercises.