Forcasting Flashcards

1
Q

Regression analysis

A

The process of deriving the linear equation that describes the relationship between two variables.

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2
Q

Simple regression equation

A

algebraic formula for a straight line

y: a+bx
y: the dependent variable
a: the y intercept
b: the slope of the regression line
x: the independent variable

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3
Q

Regression analysis is particularly valuable for:

A

Budgeting and cost accounting purposes

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4
Q

Simple regression is used when:

A

Exactly one independent variable is involved

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5
Q

Multiple regression is used:

A

When there is more than one independent variable

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6
Q

High-Low Method

A

Used to generate a regression line by basing the equation on only the highest and lowest of a series of observations

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7
Q

A major criticism of the high-low method is:

A

That the high and low points may be abnormalities not representative of normal events.

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8
Q

What is Correlation?

A

The strength of the linear (straight-line) relationship between two variables, expressed mathematically in terms of the coefficient of correlation (r).

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9
Q

What is the range of the coefficient of correlation?

A

Ranges from 1 (perfect direct relationship) to -1 (perfect inverse relationship)

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10
Q

What is the coefficient of determination?

A

A measure of how good the fite between the independent and dependent variables is
Mathematically, it is the proportion of the total variation in the dependent variable that is accounted for by the independent variable.

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11
Q

What is Standard Error?

A

Measures how well the linear equation represents the data.
The vertical distance between the data points in a scatter diagram and the regression line.
The closer the data points are to the regression line, the lower the standard error.

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12
Q

Learning Curve

A

A reflection of the increased rate at which people perform tasks as they gain experience.

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13
Q

Expected Value

A

A means of associating a dollar amount with each of the possible outcomes of a probability distribution.
The outcome yielding the highest expected value (which may or may not be the most likely one) is the optimal alternative.

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14
Q

how to calculate the expected value of an event

A

Multiply the probability of each outcome by its payoff and summing the products.
Calculation is often called a payoff table.

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