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Video of Regression Analysis for Estimating Costs. Cost Accounting Course. CPA Exam BAR. CMA Exam in Costs Accounting course by Farhat Lectures. The # 1 CPA & Accounting Courses channel, video No. 39 free certified online
How do you use regression analysis to estimate costs? In this cost accounting lesson for CPA BAR and CMA candidates, Professor Farhat explains regression analysis as a cost estimation method — contrasting it with the high-low method, fitting a cost line, and interpreting spreadsheet output such as multiple R, R-square, the intercept and slope coefficients (fixed and variable costs), and t-stats and p-values. Great for cost and managerial accounting students.
Try it free at farhatlectures.com — interactive exercises, lectures, simulations, cases, multiple choice, and AI tools for CPA, CMA, EA and students.
Video Timeline & Key Concepts:
0:00 — Introduction
0:48 — Regression vs the high-low method
2:56 — Interpreting regression output
9:48 — Multiple R, R-square, coefficients, t-stat and p-value
11:20 — Multiple regression with additional predictors
14:06 — Potential pitfalls: outliers and data validity
Frequently Asked Questions:
What is regression analysis in cost estimation?
Regression analysis is a statistical method that estimates the relationship between costs and one or more activity drivers. It fits a cost line to all available data points, producing an estimate of fixed costs and variable cost per unit of activity.
How is regression better than the high-low method?
The high-low method uses only the highest and lowest activity points, so it can be distorted by outliers. Regression uses all the data points to find the best fit line, generally producing a more accurate and reliable cost estimate.
What do R-square and multiple R measure?
Multiple R measures the strength of the relationship between the variables, while R-square represents the proportion of the variability in cost that is explained by the activity drivers. Higher values indicate the model explains more of the cost behavior.
How do you read the intercept and slope coefficients?
In a cost regression, the intercept estimates fixed costs and the slope coefficient estimates the variable cost per unit of the activity driver. Together they form the cost equation used to predict total cost at different activity levels.
What do the t-stat and p-value tell you?
The t-statistic and p-value indicate whether a predictor is statistically significant. A significant result suggests the relationship is unlikely to be due to chance, which supports including that driver in the cost model.
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