Course Syllabus
Course Description: Elementary Statistics
This course is an introduction to elementary probability and statistics. Topics covered include descriptive statistics, the basic rules of probability, probability distributions, estimation, hypothesis testing, correlation and regression analysis.
Student Learning Outcomes:
Upon completion of the course, the student should be able to
- Critically analyze statistical information presented in media, journals, etc.
- Convert data to statistical evidence and interpret the evidence.
Course Content:
- Perform statistical analysis using technology such as SPSS, EXCEL, Minitab, or graphing calculators.
- Read and analyze statistical software output.
- Analyze a problem and determine which probability distribution is the best model.
- Create and interpret frequency distributions.
- Solve problems involving probabilities by applying concepts of sample space and probability.
- Recognize and distinguish between independent and mutually exclusive events.
- Recognize and apply the basic definitions and rules of probability theory.
- Applications will use data from disciplines including business, social sciences, psychology, life science, health science, and education.
- Select the appropriate technique for testing a hypothesis and interpret the result.
- Formulate hypothesis tests involving samples from one and two populations.
- Use linear regression and ANOVA analysis for estimating and inference and interpret the associated statistics.
- Identify the basic concept of hypothesis testing including Type I and Type II errors.
- Determine and interpret levels of statistical significance including p-values.
- Construct and interpret confidence intervals.
- Distinguish between sample and population statistics and analyze the role played by the Central Limit Theorem.
- Calculate probabilities using normal and t-distributions.
- Compute the mean and variance of a discrete distribution.
- Compute and interpret statistical measures of data sets of one and two variables including measures of central tendency and variation.
- Identify standard methods of obtaining data and identify advantages and disadvantages of each.
- Distinguish between different scales of measurement and their implications
- Use and interpret graphs representing data.
Textbook:
Great news: your textbook for this class is available for free online!
Statistics from OpenStax
Links to an external site., ISBN 1-947172-05-0
You have several options to obtain this book:
- View online (Links to an external site.) (Links to an external site.)
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You can use whichever formats you want. Web view is recommended -- the responsive design works seamlessly on any device.
Important Notes:
- All first week assignments need to be completed and submitted by the due date to avoid possibly being dropped from the class.
- Any student needing accommodations should inform the instructor. Students with disabilities who may need accommodations for this class are encouraged to notify the instructor and contact the Disability Services Program (DSP) dsp@solano.edu early in the semester so that reasonable accommodations may be implemented as soon as possible. Students may contact the DRC by visiting the Center (located on the Main Campus in Building 100) or by phone (707-864-7136). If you need alternate media or assistive technology ,please use the “Request Alternate Media” link in the above drop-down menu under Disability Services Program to make your request. All information will remain confidential.
- Academic dishonesty and plagiarism will result in a failing grade on the assignment. Using someone else's ideas or phrasing and representing those ideas or phrasing as our own, either on purpose or through carelessness, is a serious offense known as plagiarism. "Ideas or phrasing" includes written or spoken material, from whole papers and paragraphs to sentences, and, indeed, phrases but it also includes statistics, lab results, art work, etc. Please see the Solano Community College Student Handbook Links to an external site. for policies regarding plagiarism, harassment, etc.
Course Summary:
Date | Details | Due |
---|---|---|
Thu Jan 23, 2025 | Assignment Math 11 Spring 2025 CRN 10621 Section 1.1 - Sampling | due by 11:59pm |
Assignment Math 11 Spring 2025 CRN 10621 Section 1.2 - Types of Data | due by 11:59pm | |
Thu Jan 30, 2025 | Assignment Math 11 Spring 2025 CRN 10621 Section 2.1 - Graphical Summaries for Qualitative Data | due by 11:59pm |
Assignment Math 11 Spring 2025 CRN 10621 Section 2.2 - Frequency Distributions and Their Graphs | due by 11:59pm | |
Thu Feb 6, 2025 | Assignment Math 11 Spring 2025 CRN 10621 Section 2.3 - More Graphs for Quantitative Data | due by 11:59pm |
Assignment Math 11 Spring 2025 CRN 10621 Section 2.4 - Graphs Can Be Misleading | due by 11:59pm | |
Assignment Math 11 Spring 2025 CRN 10621 Section 3.1 - Measures of Center | due by 11:59pm | |
Fri Feb 7, 2025 | Quiz Math 11 Spring 2025 CRN 10621 Test #1 Sections 1.1, 1.2, 2.1, 2.2, 2.3, 2.4, 3.1 | due by 2pm |
Thu Feb 13, 2025 | Assignment Math 11 Spring 2025 CRN 10621 Section 3.2 - Measures of Spread | due by 11:59pm |
Thu Feb 20, 2025 | Assignment Math 11 Spring 2025 CRN 10621 Section 3.3 - Measures of Position | due by 11:59pm |
Thu Feb 27, 2025 | Assignment Math 11 Spring 2025 CRN 10621 Section 4.1 - Correlation | due by 11:59pm |
Assignment Math 11 Spring 2025 CRN 10621 Section 4.2 - The Least-Squares Regression Line | due by 11:59pm | |
Assignment Math 11 Spring 2025 CRN 10621 Section 4.3 - Features and Limitations of the Least-Squares Regression Line | due by 11:59pm | |
Thu Mar 6, 2025 | Assignment Math 11 Spring 2025 CRN 10621 Section 5.1 - Basic Concepts of Probability | due by 11:59pm |
Assignment Math 11 Spring 2025 CRN 10621 Section 5.2 - The General Addition Rule and the Rule of Complements | due by 11:59pm | |
Tue Mar 11, 2025 | Quiz Math 11 Spring 2025 CRN 10621 Test #2 Sections 3.2, 3.3, 4.1, 4.2, 4.3, 5.1, 5.2, 5.3 | due by 4pm |
Thu Mar 13, 2025 | Assignment Math 11 Spring 2025 CRN 10621 Section 5.3 - Conditional Probability and the Multiplication Rule | due by 11:59pm |
Assignment Math 11 Spring 2025 CRN 10621 Section 6.1 - Random Variables | due by 11:59pm | |
Thu Mar 27, 2025 | Assignment Math 11 Spring 2025 CRN 10621 Section 6.2 - The Binomial Distribution | due by 11:59pm |
Thu Apr 3, 2025 | Assignment Math 11 Fall 2024 CRN 80490 Section 7.3 - Sampling Distributions and the Central Limit Theorem | due by 11:59pm |
Assignment Math 11 Spring 2025 CRN 10621 Section 7.1 - The Standard Normal Curve | due by 11:59pm | |
Assignment Math 11 Spring 2025 CRN 10621 Section 7.2 - Applications of the Normal Distribution | due by 11:59pm | |
Thu Apr 17, 2025 | Quiz Math 11 Spring 2025 CRN 10621 Test #3 Sections 5.3, 6.1, 6.2, 7.1, 7.2, 7.3, 7.4, 8.1 | due by 12pm |
Assignment Math 11 Spring 2025 CRN 10621 Section 7.4 - The Central Limit Theorem for Proportions | due by 11:59pm | |
Assignment Math 11 Spring 2025 CRN 10621 Section 8.1 - Confidence Intervals for Population Mean, Standard Deviation Known | due by 11:59pm | |
Thu Apr 24, 2025 | Assignment Math 11 Spring 2025 CRN 10621 Section 8.2 - Confidence Interval for Population Mean, Standard Deviation Unknown | due by 11:59pm |
Thu May 1, 2025 | Assignment Math 11 Spring 2025 CRN 10621 Section 8.3 - Confidence Intervals for Population Proportions | due by 11:59pm |
Assignment Accessing Technical Support | ||
Assignment Accessing Technical Support | ||
Assignment Canvas Basics Quiz | ||
Assignment Canvas Basics Quiz | ||
Assignment Fall 2024 CRN 80490 Table A-1. | ||
Assignment Math 11 Fall 2024 CRN 80490 Table A-2 | ||
Assignment Math 11 Fall 2024 CRN 80490 Table A-4 | ||
Assignment Math 11 Fall 2024 CRN 80490 Table A.3 | ||
Assignment Math 11 Spring 2025 CRN 10621 Test #1 Sections 1.1, 1.2, 2.1, 2.2, 2.3, 2.4, 3.1 Review Sheet | ||
Assignment Math 11 Spring 2025 CRN 10621 Test #2 Sections 3.2, 3.3, 4.1, 4.2, 4.3, 5.1, 5.2, 5.3 Review Sheet | ||
Assignment Math 11 Spring 2025 CRN 10621 Test #3 Sections 5.3, 6.1, 6.2, 7.1, 7.2, 7.3, 7.4, 8.1 Review Sheet |