25. Regression Analysis Flashcards
How does regression analysis in cost forecasting work?
Regression analysis is a statistical tool used to highlight patterns in past cost data. Managers can use insights gathered from the analysis of past data to forecast future costs.
What is the difference between simple regression analysis and multiple regression analysis?
Simple regression analysis (sometimes called single linear regression analysis) can be used to explore two sets of data to see if there is a relationship between them. One set of data is the activity, or independent variable, and the other is the dependent variable.
While simple regression analysis uses only one activity to predict costs, multiple regression analysis can use many activities to help managers understand and forecast costs.
What is the Multiple R in regression analysis?
The Multiple R statistic is the simple correlation between two or more sets of data (volume and costs, for example).
What is the difference between R Square and Adjusted R Square in regression analysis?
The R Square statistic indicates how much of the change in one or more sets of data explains the variance (change) in the other.
The Adjusted R Square statistic is R Square adjusted for the size of the sample data set. The Adjusted R Square statistic is a more appropriate measure to use when explaining variance in cost data.
What is the Standard Error in regression analysis?
A Standard Error signifies that there is approximately a 68% chance (assuming the data has a normal distribution) the estimated cost will be within the original estimate plus or minus the Standard Error. Doubling the Standard Error provides approximately a 95% chance that the estimated cost is actually within range of the original estimate.
