Part 1 – Section D.1. Forecasting analysis

[Hameed]

CMA1.D1.a. demonstrate an understanding of a simple regression equation and the measures associated with it

CMA1.D1.b. define a multiple regression equation

CMA1.D1.c. identify the assumptions of simple and multiple regression analyses

CMA1.D1.d. calculate the result of a simple regression equation as applied to a specific situation

CMA1.D1.e. demonstrate an understanding of learning curve analyses

CMA1.D1.f. calculate the results under a cumulative average-time learning model and under an incremental unit-time learning model

CMA1.D1.g. demonstrate an understanding of exponential smoothing and calculate a forecast using this method

CMA1.D1.h. demonstrate an understanding of time series analyses, including objectives and patterns, i.e., trend, cyclical, seasonal, and irregular

CMA1.D1.i. list the benefits and shortcomings of regression analysis, learning curve analysis, and time series analysis