Course Syllabus

Course Description:

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.

Student Learning Outcomes:

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.

Course Content:

  • 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.


You will need a TI-84 scientific calculator.  For access to a TI-84 emulator through Texas Instruments go here.

You will need access to WebAssign.  You can use instructions found here WebAssign Class Key :   solano 9589 3588

Great newsyour textbook for this class is available for free online!
Statistics from OpenStax, ISBN 1-947172-05-0

You have several options to obtain this book:

You can use whichever formats you want. Web view is recommended -- the responsive design works seamlessly on any device.

R-Studio - How to download and install R Studio

Important Notes:

  • All first week assignments need to be completed and submitted by the due date to avoid possibly being dropped from the class.  Most weeks are very busy but the first week is particularly busy.
  • 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 Resource Department (DRD) early in the semester so that reasonable accommodations may be implemented as soon as possible. Students may contact the DRD by visiting the Department in Analy Village (Santa Rosa campus:527-4278) or  101 Jacobs Hall (Petaluma campus:778-2491).  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 Santa Rosa Junior College handbook for policies regarding plagiarism, harassment, etc.

Course Summary:

Date Details Due