University General Course Catalog 2020-2021 
    
    May 30, 2024  
University General Course Catalog 2020-2021 ARCHIVED CATALOG: LINKS AND CONTENT ARE OUT OF DATE. CHECK WITH YOUR ADVISOR.

Add to Portfolio (opens a new window)

APST 270 - Introduction to Statistical Methods

(4 units) CO2
Principles of statistics and application to the fields of social, life, and environmental sciences; and economics. Emphasis is given to computer applications. (Depending on the major, students must also achieve a satisfactory score on a placement examination to receive Core credit. This course will fulfill the Core Mathematics requirement for major programs that accept MATH 120.)

Prerequisite(s): ACT 27 or SAT 630 or Accuplacer QAS 276 and AAF 276 or MATH 126  or MATH 127  or MATH 128  or MATH 176  or MATH 181 . Recommended Preparation: Take a math placement test before registering if 10 or more years have passed since completion of the prerequisite coursework.

Units of Lecture: 3
Units of Laboratory/Studio: 1
Offered: Every Fall and Spring

Student Learning Outcomes
Upon completion of this course, students will be able to:
1. engage in critical thinking to justify choice of statistics, legitimate data manipulations, data visualization and expressing verbal variables in algebraic terms; compute statistics using algebraic formulas and statistical software; identify results; design and create appropriate graphics and tables for descriptive statistics.
2. work with algebraic formulas to make basic probability calculations; identify and generate classic probability distributions; compare sample data to the normal distribution; evaluate the degree of similarity and defend that evaluation.
3. provide a foundation (including interpreting a verbal description of a research problem into statistical terms); formulate hypotheses both algebraically and verbally; evaluate alternative candidate statistics (including the assumptions) and defend their choice. Statistics include difference-of-means test (“t-test”), difference-of-proportions test, regression, analysis of variance, chi-squared, and, where appropriate, non-parametric analogs.
4. compute the statistical analyses chosen; identify relevant estimates in output from statistical software; design and produce appropriately labeled and clearly presented graphs and tables of statistical results; write correct summaries of and meaningful conclusions about statistical results, drawing both on hypothesis tests and on confidence intervals.


Click here for course scheduling information. | Check course textbook information



Add to Portfolio (opens a new window)