Forecasting Techniques Flashcards
In describing the regression equation used for cost prediction, Y = a + bx, which of the following is correct?
A. Y is the total revenue.
B. a is the variable rate.
C. a and b are valid for all levels of activity.
D. a is the total fixed cost.
D. a is the total fixed cost.
The constant, a in a regression equation to calculate cost depicts the total fixed cost.
Dough Distributors has decided to increase its daily muffin purchases by 100 boxes. A box of muffins costs $2 and sells for $3 through regular stores. Any boxes not sold through regular stores are sold through Dough’s thrift store for $1. Dough assigns the following probabilities to selling additional boxes:
Additional sales Probability 60 .6 100 .4 What is the expected value of Dough's decision to buy 100 additional boxes of muffins? A. $28. B. $40. C. $52. D. $68.
C. $52.
Income or net cash inflow is expected to increase:
$52 = .6[60($3-$2) + 40($1-$2)] + .4[100($3-$2)].
The .6[ ] term reflects the expected sales of 60 units at regular price less their cost, and 40 at the reduced price less their cost. The .4[ ] term reflects the expected sales all at regular prices less their cost.
The regression analysis results for ABC Co. are shown as y = 90x + 45. The standard error (Sb) is 30 and the coefficient of determination (r2 ) is 0.81. The budget calls for the production of 100 units. What is ABC's estimate of total costs? A. $3,090. B. $4,590. C. $9,030. D. $9,045.
D. $9,045.
Total cost (y) is expressed as $90 of variable cost per unit + $45 of fixed cost. Given that x represents units, we solve for y = $90(100) + $45 = $9,045.
Box Co. uses regression analysis to estimate the functional relationship between an independent variable (cost driver) and overhead cost.
Assume that the following equation is being used:
y = A + Bx.
What is the symbol for the independent variable? A. y B. x C. Bx D. A
B. x
The independent variable (x) is the one that is believed to have a causal effect on cost, the dependent variable (y). The variable is called “independent” because its level is first set in order to determine the effect on cost. For example, x might be output level. The firm is interested in determining the effect of different outputs (set first) on cost (determined second). Cost is “dependent” on the independent variable output.
The coefficient of determination, r squared, in a multiple regression equation is what?
Percentage of variation in the dependent variable explained by the variation in the independent variables.
The definition of r squared reflects the overall model’s explanatory power of the independent variables in predicting the dependent variable.
A management accountant performs a linear regression of maintenance cost vs. production using a computer spreadsheet. The regression output shows an “intercept” value of $322,897. How should the accountant interpret this information?
A. Y has a value of $322,897 when x equals zero. B. x has a value of $322,897 when Y equals zero. C. The residual error of the regression is $322,897. D. Maintenance cost has an average value of $322,897.
A. Y has a value of $322,897 when x equals zero.
The regression equation has the format: Y = A + Bx, where Y is the dependent variable, A is point where the regression line intercepts the Y access, B is the slope of the line, and x is the independent variable. The Y intercept occurs when x equals zero.
Under frost-free conditions, Cal Cultivators expects its strawberry crop to have a $60,000 market value.
An unprotected crop subject to frost has an expected market value of $40,000.
If Cal protects the strawberries against frost, then the market value of the crop is still expected to be $60,000 under frost-free conditions and $90,000 if there is a frost.
What must be the probability of a frost for Cal to be indifferent to spending $10,000 for frost protection? A. .167. B. .200. C. .250. D. .333.
B. .200.
Correct!
There are two states of nature that can affect the firm’s earnings: frost and no frost. There are also two actions under consideration: provide frost protection for $10,000, or do not. The expected income under each action will depend on the probability of frost. Let p = the probability of frost. Expected net income if frost protection is provided = $90,000(p) + $60,000(1-p) - $10,000. Expected net income if frost protection is not provided = $40,000(p) + $60,000(1-p). The firm is indifferent between the two actions when the expected net income is the same for both. Setting the two expressions equal to each other and solving for p determines at what probability of frost the two actions provide the same income.
$90,000(p) + $60,000(1-p) - $10,000 = $40,000(p) + $60,000(1-p)
$50,000(p) = $10,000
p = .20
When the probability of frost exceeds .20, the expected income from providing frost protection exceeds that of not providing frost protection. This can be verified by entering a probability higher than .20 into both income expressions and determining the income. This is the expected result. As the probability of frost increases, the expected benefits of providing frost protection also increase.
The opposite is true for probabilities lower than .20.
In using regression analysis, which measure indicates the extent to which a change in the independent variable explains a change in the dependent variable? A. p-value. B. r-squared. C. Standard error. D. t-statistic.
B. r-squared.
The coefficient of determination, identified as R2 (R-squared), indicates the degree to which the behavior of the independent variable(s) predicts or explains the dependent variable.
