QM Test 2

Excel and virtually all other statistical packages report the p-value ____________________________________.

for a two-tailed test that assesses whether the regression coefficient differs from zero

The managers of a brokerage firm are interested in finding out if the number of new clients a broker brings into the firm affects the sales generated by the broker. They sample 12 brokers and determine the number of new clients they have enrolled in the last year (X) and their sales amounts in thousands of dollars (Y). The resulting regression equation is Y^ = 1.1 + 17.7x What is the predicted amount of sales (in $1,000s) for a person who brings 25 new clients into the firm? Include 1 decimal place with your answer.

$443.6

In a simple regression analysis based on 30 observations it is found that SSE=2540 and SST=13,870. Calculate R2. Round your answer to 3 decimal places.

.817

Dummy variables take on the values of _________ and are used to model the effects of different levels of qualitative variables.

0 or 1

A time series is

a set of sequential observations of a variable over time.

Suppose that we have a qualitative variable Month with categories: January, February, etc. How many dummy variables are needed to describe Month?

11

The accompanying table shows the regression results when estimating Y= β0 + β1X + ε. Coefficients Standard Error t-stat p-value Intercept 0.083 3.56 0.02 0.9822 x 1.417 0.63 ? 0.0745 Which of the following is the value of the test statistic when testing H0: β1=0?

2.25

What is the name of the variable that is used to predict another variable?

Explanatory

In a simple regression analysis, the Y-intercept (b0) represents the:

predicted value of Y when X = 0.

In the simple linear regression model, the y-intercept represents the:

predicted value of y when x = 0

A candy bar manufacturer is interested in trying to estimate how sales are influenced by the price of their product. To do this, the company randomly chooses 6 small cities and offers the candy bar at different prices. Using candy bar sales as the dependent variable, the company built a simple linear regression on the data. The resulting equation is: Where P is the price of the candy bar in dollars. What are the expected sales when the price of the candy bar is $2.00?

$49

Consider the model Y = β0 + β1X + β2D + ε, where X is a quantitative variable and D is a dummy variable. When D = 1, the predicted value of Y is computed as:

(b0 + b2) + b1X

You wish to include marital status in a multiple regression model. The categories you want to include are: Single, Married, Divorced, and Other. How many dummy variables do you need?

3

Use these data for Questions 5 and 6. Conduct a regression analysis in Excel using the following data: X Y 12 40 23 50 40 59 33 58 18 45 What is the value of b0? Include 1 decimal place in your answer. What is the value of b1? Include 2 decimal places in your answer.

32.5 .71

In a simple regression analysis based on 30 observations it is found that SSE=2540 and SST=13,870. What is the value of se, the standard error of the estimate? Round your answer to 2 decimal places.

9.52

Given the augmented Phillips model: Y=B0+B1X1+B2X2+E, where Y=Actual rate of inflation, X1=Unemployment rate, and X2=Anticipated inflation rate. The response variable(s) in this model is/are:

Actual inflation rate

A time series with observed long-term upward movements in its values is said to have _________________.

An increasing trend component

In a moving average method, when a new observation becomes available, the new average is computed by including the new observation and ________ .

Dropping the oldest observation

T/F: A drawback to exponential smoothing is that it gives equal weight to all recent observations equally.

False

T/F: Quantitative forecasting procedures are based on the judgement of the forecaster, who uses prior experience and expertise to make forecasts.

False

T/F: The moving average method is one of the most complex smoothing techniques used for processing time series.

False

Consider the following simple linear regression model: Y= β0 + β1X + ε When determining whether X significantly influences Y, the null hypothesis takes the form _____________.

H0: β1 = 0

A regression analysis was conducted using 3 explanatory (X) variables. The null hypothesis for the overall F test is:

H0: β1 = β2 = β3 = 0

What is the name of the variable that is predicted by another variable?

Response

A trend is an example of what kind of pattern?

Systematic

Seasonality is an example of what kind of pattern?

Systematic

The optimal value of the speed of decline in the exponential smoothing procedure is determined by:

Trial and Error

T/F: A Moving Average is a noncausal model of forecasting.

True

The presence of random error causes what kind of pattern?

Unsystematic

A time series with observed long-term downward movements in its values is said to have

a decreasing trend component

Which of the following is an example of a time series? a) The number of daily visitors to the Niagara Falls during the month of April. b) The current average prices of regular gasoline in different states of the U.S. c) The recorded exam scores of students in a class. d) The sales prices of single family homes sold last month in Florida.

a) The number of daily visitors to the Niagara Falls during the month of April

A professor of industrial relations believes that an individual's wage rate at a factory (Y) depends on his performance rating (X1) and the number of economics courses the employee successfully completed in college (X2). A random sample of 6 workers was used to generate the following model: Y^ = 16.93 + 1.05X1 + 0.62X2 What is the interpretation of B2? a) An increase in in performance rating of 1.0 will increase the predicted wage by $1.05. b) Successfully completing one more economics course will increase the predicted wage by $0.62. c) The starting wage rate at the factory is $16.93.

b) Successfully completing one more economics course will increase the predicted wage by $0.62

Simple linear regression analysis differs from multiple regression analysis in that: a) goodness-of-fit measures cannot be calculated with simple linear regression b) simple linear regression uses only one explanatory variable c) the coefficient of determination is always higher in simple linear regression d) the coefficient of correlation is meaningless in simple linear regression

b) simple linear regression uses only one explanatory variable

A regression analysis was used for predicting the selling price of a home (in thousands of dollars) using lot size, home size, and whether or not the home has a pool. The presence of a pool was modeled with a dummy variable that has a value of 1 if the home has a pool and a value of 0 if the home does not have a pool. The value of the coefficient of the pool dummy variable is 23.5. What is the interpretation of this coefficient? Pay attention to the units! a) On average, a home with a pool will sell for $23.50 more than a home without a pool. b) On average, a home with a pool will sell for $23.50 less than a home without a pool. c) On average, a home with a pool will sell for $23,500 more than a home without a pool. d) On average, a home with a pool will sell for $23,500 less than a home without a pool.

c) On average, a home with a pool will sell for $23,500 more than a home without a pool

Which of the following is an example of a time series? a) The balances of all checking accounts at Wells Fargo Bank. b) The heights of players on the Orlando Magic basketball team. c) The monthly sales of Ford F-150 pickup trucks. d) The current average prices of regular gasoline in different states of the U.S.

c) The monthly sales of Ford F-150 pickup trucks

In the simple linear regression model, the slope represents the:

change in y per unit change in x

Generally speaking, if two variables are unrelated (as one increases, the other showsnot pattern), the correlation coefficient will be:

close to zero

Which of the following variables is not qualitative? Group of answer choices Student's status (freshman, sophomore, etc.) Gender of a person Religious affiliation Number of dependents claimed on a tax return

d) Number of dependents on a tax return

When a value of Y is calculated using the regression equation, it is called: a) y-hat b) the estimated value c) the predicted value d) all of the above

d) all of the above

For the model Y= β0 + β1X + β2D + ε, which test is used for testing the significance of the dummy variable D?

t test

The residual is defined as the difference between:

the actual value of y and the estimated value of y.

The slope (b1) represents:

the estimated average change in Y per unit change in X.

Adjusted R2 takes into account

the number of X variables and the sample size.

Adjusted R2 takes into account:

the number of predictor (X) variables and the sample size.

A correlation coefficient r = −0.85 could indicate a:

very strong negative linear relationship