Ch16 Analysis - Linear Programming and Regression Analysis

Question 1

Cost functions

Answer 1

Cause and effect
- level of activity aka. level of cost driver
- identify a variable that causes a change in total cost
- economic plausibility - can be reapplied to similar situation for cost/revenue trend analysis

Question 2

Estimating a cost function

Answer 2

Step 1: choose the dependent variable (Y-cost)
Step 2: identify the independent variable(X-cost drivers)
Step 3: collect data for both
(time-series data - ideal
cross-sectional data - different entity at same time
Step 4: plot the data
Step 5: Estimate the cost function
- high-low method (simple but flawed by reflective of extremes)
- regression analysis (preferred)
Step 6: use regression analysis function in excel to provide a summary output
Step 7: analyze the results based on economic plausibility, goodness of fit, and stas significance

Question 3

Regression analysis - establish cost functions
aka. line of best fit

Answer 3

to predict and forecast, in budeting, planning, financial analysis and other techniques

Methods:
1. Linear regression
2. ordinary least squares

To analyze:
1. economic plausibility - relationship logical sense
2. Goodness of fit (r2)
3. Significance F (<0.05 is acceptable)
4. p-value

Question 4

Goodness of fit

Answer 4

Professional judgement