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 ALEKS PPL of 61 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.

Grading Basis: Graded
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.

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