APST 670 - Linear Regression and Time Series

(3 units)

Application of multiple regression and time series regression models in economics, life and environmental sciences. Computers will be utilized.

Grading Basis: Graded
Units of Lecture: 3
Offered: Every Fall

Student Learning Outcomes
Upon completion of this course, students will be able to:
1. identify key elements in a prose research question or data description (cases/ experimental units, variables, types of variables/ levels of measurement) and make inferences about implicit causal assumptions and parameter of interest.
2. formulate hypotheses symbolically and in writing.
3. calculate descriptive statistics and the statistical test of interest using a statistical package.
4. identify key elements correctly in output, and prepare informative graphics (including confidence bands for regression lines) and tables.
5. outline in prose the descriptive statistics, statistical test, magnitude estimates, PVAR estimates, and graphics for inferential statistics prepared in SLO 3.
6. assess the implications for the hypotheses and compose an appropriate conclusion about them.
7. interpret the magnitudes of associations using both point estimates and confidence intervals, reporting results orally and in writing.

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