COMPUTER SCIENCE


Course Credits: 3 Units

Prerequisites: Stat 105

Stat 106 - Advanced Statistical Analysis

Course Description

Regression and correlation analysis; non-parametric methods; experimental design; time series analysis.

Course Learning Outcomes

After completion of the course, the student should be able to:

  1. Demonstrate mastery of advanced statistical terms and concepts;
  2. Formulate steps in explaining phenomena and making decisions based on available data;
  3. Generate and present appropriate statistical analysis given statistical data; and
  4. Apply statistical procedures using software that are appropriate for different types of data.
Course Outline

UNIT 1. 1. Nonparametric Methods

  1. Introduction to Nonparametric Statistics
  2. Testing Hypotheses about a Single Population
  3. Testing Hypotheses about Two Populations
  4. Testing Hypotheses about Three or More Populations
  5. Choosing an Appropriate Test

UNIT 2. Regression and Correlation Analysis

  1. Simple Linear Regression
  2. Multiple Linear Regression
  3. Model Building
  4. Diagnostic Checking
  5. Remedial Measures

UNIT 3. Design and Analysis of Experiments

  1. Introduction to DOE
  2. Completely Randomized Design (CRD)
  3. Randomized Complete Block Design (RCBD)
  4. Other Designs

UNIT 4.Time Series Analysis

  1. Time Series Data
  2. Moving Average Processes
  3. Autoregressive Processes
  4. ARMA Processes