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Managerial Economics > Week 2 > Flashcards

Week 2 Flashcards

1
Q

What are parameters?

A

The coefficients in an equation that determine the exact mathematical relation among the variable.

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2
Q

Parameter Estimation

A

The process of finding estimates of the numerical values of the parameters of an equation.

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3
Q

Regression Analysis

A

A statistical technique for estimating the parameters for an equation and testing for statistical significance.

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4
Q

Dependent Variable

A

A variable whose variation is to be explained.

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5
Q

Explanatory (independent) Variables

A

Variables that are thought to cause the dependent variable to take on different values.

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6
Q

Intercept Parameter (A) -

A

Gives the value of Y where the regression line crosses the Y-Axis.

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7
Q

Slope Parameter

A

Gives the change in Y associated with a one-unit change in X

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8
Q

Random Error Term

A

Unobservable term added to a regression model to capture the effects of all of the minor, unpredictable factors that affect Y but cannot reasonably be included as explanatory variables.

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9
Q

What is a regression line?

A

A line that shows the average or expected value of Y for each level of X

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10
Q

Time Series

A

A data set in which the data for the dependent and explanatory variables are collected over time for a single firm.

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11
Q

Cross-Sectional Data

A

A data set in which the data for the dependent and explanatory variables are collected from many different firms or industrials at a given point in time.

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12
Q

Scatter Diagram

A

A graph of the data points in a sample

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13
Q

What is Y = a + bx with hats over the Y, A, and B called?

A

Sample Regression Line.

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14
Q

What is the residual?

A

True value - predicted value in a regression. (Yi - Yi^)

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15
Q

What is the method of least squares?

A

minimizes the sum of the squared distances from each sample data point to the sample regression line.

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16
Q

What are Estimators?

A

Estimators are the formulas by which the estimates of parameters are computed.

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17
Q

What is statistical significance?

A

When there is sufficient evidence from the sample to indicate that the true value of the coefficient is not zero.

18
Q

What is hypothesis testing?

A

A statistical technique for making a probabilistic statement about the true value of a parameter.

19
Q

What are unbiased estimators?

A

The estimators a^ and b^ do not generally equal the true values of a and b.

20
Q

What is the T Value Formula?

A

B^
___
S b^

21
Q

How do you calculate S^?

A

It is the standard error of b^, and you calculate it by looking at the standard error column in the regression.

22
Q

What are degrees of freedom?

A

The number of observations in the sample minus the number of parameters being estimated by the regression analysis.

23
Q

What is the Level of Significance?

A

The probability of finding a parameter estimate to be statistically different from zero when, in fact, it is zero.

24
Q

What is a type 1 error?

A

When a parameter estimate is found to be statistically-significant when it is not.

25
Q

What is level of confidence?

A

Is the probability of correctly failing to reject the true hypothesis that b=0.

26
Q

What is the formula for level of confidence?

A

1-level of significance = level of confidence.

27
Q

What is the maximum allowable level of significance?

A

10%

28
Q

What is a t-Test?

A

A statistical test used to test the hypothesis that the true value of a parameter is equal to zero.

29
Q

What is N in a regression?

A

Number of observations.

30
Q

What is K in a regression?

A

The number of predictor terms.

31
Q

What is a P-Value?

A

A measure that gives you the exact level of significance for a test statistic.

32
Q

What is R Square? (Coefficient of Determination)

A

R2 measures the fraction of the total variation in the dependent variable (Y) that is explained by the regression equation (or explained by the variation in X).

33
Q

What is F statistic?

A

Used to test the significance of the overall regression equation.

34
Q

What is multiple regression?

A

Regression models that use more than one explanatory variables to explain the variation in the dependent variable.

35
Q

What is a quadratic regression model?

A

A nonlinear regression model.

36
Q

Least squares / standard error = ?

A

Degrees of freedom

37
Q

What are the three types of functions?

A

Demand, production, and cost.

38
Q

What is the formula to determine the total cost of producing various levels of output?

A

C = a + bQ + cQ2 + dQ3

39
Q

The objective of regression analysis is to find what?

A

A perfect fit for a scatter diagram.

40
Q

What is the true regression line?

A

The population

41
Q

The ____________ line is the line that best fits the data collected.

A

Sample

Managerial Economics (5 decks)

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