Mt. SAC Important Message

New Numbers, Same Classes! Some of our most important general education classes have new course numbers and names effective this Fall. Don't miss your GE requirements and read your Mountie email for more information!

LEARN MORE
Menu

STAT C1000H - Honors Introduction to Statistics

(Formerly MATH 110H - Honors Elementary Statistics)

The following are the Student Learning Outcomes (SLOs) and Course Measurable Objectives (CMOs) for STAT C1000H. A Student Learning Outcome is a measurable outcome statement about what a student will think, know, or be able to do as a result of an educational experience. Course Measurable Objectives focus more on course content, and can be considered to be smaller pieces that build up to the SLOs.

Student Learning Outcomes (SLOs)

  1. Students will be able to determine descriptive statistics from a sample.
  2. Students will be able to use sample statistics to develop a confidence interval for population parameters.
  3. Using sample statistics from one or more samples, students will be able to test a claim made about a population parameter.
  4. Using bivariate data, students will be able to determine whether a significant linear correlation exists between two variables and determine the equation of the regression line.

Course Measurable Objectives (CMOs Effective Beginning Fall 2025)

  1. Assess how data were collected and recognize how data collection affects what conclusions can be drawn from the data. 
  2. Identify appropriate graphs and summary statistics for variables and relationships between them and correctly interpret information from graphs and summary statistics. 
  3. Describe and apply probability concepts and distributions.
  4. Demonstrate an understanding of, and ability to use, basic ideas of statistical processes, including hypothesis tests and confidence interval estimation.
  5. Identify appropriate statistical techniques and use technology-based statistical analysis to describe, interpret, and communicate results.
  6. Evaluate ethical issues in statistical practice.