Course

Course Summary
Credit Type:
Course
ACE ID:
STAT-0009
Organization's ID:
#642
Organization:
Statistics.com
Location:
Online
Length:
8 weeks (120 hours)
Dates Offered:
Credit Recommendation & Competencies
Level Credits (SH) Subject
Graduate 3 regression analysis
Description

Objective:

The course objective is to explain how to derive multiple linear regression models, how to use software to implement them, and what assumptions underlie the models. You will also learn how to test whether your data meets those assumptions, what can be done when those assumptions are not met, and strategies to build and understand useful models.

Learning Outcomes:

  • calculate a simple linear regression model
  • Assess the model with standard error, R-squared, and slope
  • Review and check model assumptions
  • Extend the model to multiple linear regression
  • Assess parameter estimates globally, in subsets, and individually test model assumptions
  • Transform predictors and response variables to improve model fit
  • Deal with qualitative predictors
  • Handle interactions among predictors
  • Identify influential points
  • Deal with autocorrelation, multi-collinearity, and missing data
  • exercise appropriate caution with respect to extrapolation.
  • understand simple and multiple linear regression
  • Understand how to test whether the data meet those assumptions and what can be done when those assumptions are not met
  • develop strategies for building and understanding useful models

General Topics:

  • Foundations and Simple Linear Regression
  • Multiple Linear Regression
  • Model Building I
  • Model Building II
Instruction & Assessment

Instructional Strategies:

  • Classroom Exercise
  • Coaching/Mentoring
  • Computer Based Training
  • Discussion
  • Practical Exercises
  • Project-based Instruction

Methods of Assessment:

  • Other
  • Quizzes
  • Project

Minimum Passing Score:

80%
Supplemental Materials