Unformatted text preview: mple exponential smoothing and
determined the following: S0 = 19, S1 = 18.6, S2 = 19.08, S3 = 19.064, S4 = 19.851 and S5 =
19.481. Calculate the Mean Absolute Deviation (MAD).
A. 3.671
B. 8.215
C. 2.161
D. 1.643 AACSB: Analytic
Bloom's: Application
Difficulty: Medium
Learning Objective: 6
Topic: Exponential Smoothing 11621 Chapter 01  An Introduction to Business Statistics 98. Consider the following data and calculate S1 using simple exponential smoothing and =
0.3. A. 19.14
B. 19.00
C. 18.40
D. 18.55 AACSB: Analytic
Bloom's: Application
Difficulty: Medium
Learning Objective: 5
Topic: Exponential Smoothing 11622 Chapter 01  An Introduction to Business Statistics 99. Consider the following data and calculate S2 using simple exponential smoothing and α =
0.3. A. 18.40
B. 19.18
C. 19.00
D. 19.60 AACSB: Analytic
Bloom's: Application
Difficulty: Medium
Learning Objective: 5
Topic: Exponential Smoothing 11623 Chapter 01  An Introduction to Business Statistics 100. Consider the following data and calculations. Calculate the estimated value of b1 and b0
and state the linear trend regression prediction equation. A. 2.5 + 1.43t
B. 2.86 + 2.5t
C. 1.43 + 2.5t
D. 4.00 + 1.43t AACSB: Analytic
Bloom's: Application
Difficulty: Hard
Learning Objective: 2
Topic: Time series regression 11624 Chapter 01  An Introduction to Business Statistics 101. The linear trend equation for the following data is What is the predicted value of the fund in the period t = 1?
A. 11.43
B. 3.93
C. 8.22
D. 2.50 AACSB: Analytic
Bloom's: Application
Difficulty: Medium
Learning Objective: 2
Topic: Time series regression 11625 Chapter 01  An Introduction to Business Statistics 102. The linear trend equation for the following data is What is the predicted value of the fund in the period 7?
A. 12.51
B. 48.93
C. 18.93
D. 29.67 AACSB: Analytic
Bloom's: Application
Difficulty: Medium
Learning Objective: 2
Topic: Time series regression 11626 Chapter 01  An Introduction to Business Statistics 103. The linear trend equation for the following data is Find the residual value (error) for period 7.
A. 6.49
B. 29.93
C. 0.07
D. 10.67 AACSB: Analytic
Bloom's: Application
Difficulty: Medium
Learning Objective: 2
Topic: Time series regression 11627 Chapter 01  An Introduction to Business Statistics 104. Consider the regression equation = 6.04 + 0.10(t) and the data below. Compute the predicted value of sales for period 8.
A. 48.42
B. 14.04
C. 6.75
D. 6.84 AACSB: Analytic
Bloom's: Application
Difficulty: Easy
Learning Objective: 2
Topic: Time series regression 11628 Chapter 01  An Introduction to Business Statistics 105. Consider the regression equation = 6.04 + 0.10(t) and the data below. Compute the residual (error term) for period 8.
A. 1.25
B. 1.16
C. 0.35
D. 0.26 AACSB: Analytic
Bloom's: Application
Difficulty: Medium
Learning Objective: 2
Topic: Time series regression 11629 Chapter 01  An Introduction to Business Statistics
Essay Questions 106. Consider the following set of quarterly sales data given in thousands of dollars. Write an appropriate dummy variable model that incorporates a linear trend and constant
seasonal variation.
y (t) = B0 + B1t + BQ1(Q1) + BQ2(Q2) + BQ3(Q3) + Et
There are (4  1) = 3 binary seasonal variables (Q1, Q2, and Q3).
Qi is a binary (0, 1) variable defined as:
Qi = 1, if the time series data is associated with quarter i.
Qi = 0, if the time series data is not associated with quarter i.
y (t) = B0 + B1t + BQ1(Q1) + BQ2(Q2) + BQ3(Q3) + Et AACSB: Analytic
Bloom's: Comprehension
Difficulty: Hard
Learning Objective: 2
Topic: Time series regression 11630 Chapter 01  An Introduction to Business Statistics 107. Consider the following set of quarterly sales data given in thousands of dollars. The following dummy variable model that incorporates a linear trend and constant seasonal
variation was used: y (t) = B0 + B1t + BQ1(Q1) + BQ2(Q2) + BQ3(Q3) + Et
In this model there are 3 binary seasonal variables (Q1, Q2, and Q3).
Where
Qi is a binary (0, 1) variable defined as:
Qi = 1, if the time series data is associated with quarter i;
Qi = 0, if the time series data is not associated with quarter i.
The results associated with this data and model are given in the following MINITAB
computer output.
The regression equation is
Sales = 2442 + 6.2 Time  693 Q1  1499 Q2 + 153 Q3 Provide a managerial interpretation of the regression coefficients for the variable "Q1"
(quarter 1), "Q2" (quarter 2) and "Q3" (quarter 3).
Excluding trend, estimated sales in quarter 1 (winter) is $693,000 less than the estimated sales
in quarter 4 (fall).
Excluding trend, estimated sales in quarter 2 (spring) is $1,499,000 less than the estimated
sales in quarter 4 (fall).
Excluding trend, estimated sales in quarter 3 (summer) is $153,000 more than the estimated
sales in quarter 4 (fall). 11631 Chapter 01  An Introduction to Business Statistics
AACSB: Analytic
Bloom's: Evaluation
Difficulty: Hard
Learning Objective: 2
Topi...
View
Full Document
 Winter '14
 Frequency, Frequency distribution, Histogram, AACSB, Statistical charts and diagrams

Click to edit the document details