Question 1

Professor Z needs to allocate time among several tasks next week to include time for students' appointments.Thus,he needs to forecast the number of students who will seek appointments.He has gathered the following data:
Week # of students
6 weeks ago 83
5 weeks ago 110
4 weeks ago 95
3 weeks ago 80
2 weeks ago 65
Last week 50
-What is the forecast for this year using exponential smoothing with $\alpha$ = 0 2,if the forecast for two weeks ago was 90?
A)49 
B)50 
C)52 
D)65 
E)78

Accepted Answer

The exponential smoothing formula is: $ F_t = \alpha \times A_{t-1} + (1-\alpha) \times F_{t-1} $. For last week: $ F_{last} = 0.2 \times 65 + 0.8 \times 90 = 78 $.

Question 2

Professor Z needs to allocate time among several tasks next week to include time for students' appointments.Thus,he needs to forecast the number of students who will seek appointments.He has gathered the following data:
Week # of students
6 weeks ago 83
5 weeks ago 110
4 weeks ago 95
3 weeks ago 80
2 weeks ago 65
Last week 50
-What is the forecast for this year using the last-value forecasting method?
A)22,000 
B)20,000 
C)18,000 
D)15,000 
E)12,000

Accepted Answer

The last-value forecasting method assumes that the most recent observation is the best predictor of the future. Therefore, the forecast for this week would be the same as the number of students seeking appointments last week, which is 50.

To find the forecast for the entire year, we need to sum up the past six weeks' data: 83+110+95+80+65+50 = 483. Then we divide this by the number of weeks, which is 6, to get the average number of students seeking appointments per week: 483/6 = 80.5.

To find the forecast for the entire year, we multiply this average weekly demand by the number of weeks in a year, which is 52: 80.5 x 52 = 4,186.

However, since the question asks for the forecast using the last-value method, the answer is simply the most recent value, which is 50. Therefore, the best answer is B.

Question 3

Which of the following is not a type of judgmental forecasting?
A)Managerial opinion 
B)Sales force composite 
C)Time-series analysis 
D)The Delphi method 
E)Consumer market survey

Accepted Answer

Time-series analysis is a quantitative forecasting technique that involves analyzing past data to identify patterns and trends, rather than relying on subjective judgments or opinions. Therefore, it is not a type of judgmental forecasting. The other options listed all involve some level of subjective input or opinion to make forecasts.

Question 4

The forecasting method which uses anonymous questionnaires to achieve a consensus forecast is:
A)sales force composites 
B)consumer surveys 
C)the Delphi method 
D)time-series analysis 
E)executive opinions

Accepted Answer

The Delphi method is a forecasting method that utilizes a panel of experts responding to anonymous questionnaires in order to achieve a consensus forecast. This method is particularly useful for long-term forecasts or when data is limited. Sales force composites, consumer surveys, time-series analysis, and executive opinions all involve gathering data from known sources and are not designed to achieve a consensus forecast through anonymous questionnaires.

Question 5

A manager uses the equation y = 40,000 + 150x to predict monthly receipts What is the forecast for July if x = 0 in April?
A)40,450 
B)40,600 
C)42,100 
D)42,250 
E)42,400

Accepted Answer

When x = 0 in April, it means that April is the first month, and thus x represents the number of months after April. Therefore, when x = 3 (meaning three months after April), it represents July. Plugging in x = 3, we get: 
y = 40,000 + 150(3) 
y = 40,450 
Therefore, the forecast for July is $40,450.

Question 6

Questions 10-66 through 10-69 refer to the following:
An operation analyst is forecasting this year's demand for one of his company's products based on the following historical data:
Year # sold
4 years ago 10,000
3 years ago 12,000
2 years ago 18,000
Last year 20,000
-What is the forecast for this year using exponential smoothing with $\alpha$ = 0 2,if the forecast for last year was 15,000?
A)20,000 
B)19,000 
C)17,500 
D)16,000 
E)15,000

Accepted Answer

Exponential smoothing forecast = Previous forecast + α(Actual demand - Previous forecast). For last year: 15,000 + 0.2(20,000 - 15,000) = 16,000.

Question 7

The business analyst for Ace Business Machines,Inc.wants to forecast this year's demand for manual typewriters based on the following historical data:
Time Period :Demand
5 years ago :900
4 years ago : 700
3 years ago : 600
2 years ago :500
Last year :300
-What is the forecast for this year using the last-value forecasting method?
A)49 
B)50 
C)52 
D)65 
E)78

Accepted Answer

The last-value forecasting method simply uses the most recent demand as the forecast for the next period. In this case, the most recent demand is 300, so the forecast for this year is 300.

Question 8

Professor Z needs to allocate time among several tasks next week to include time for students' appointments.Thus,he needs to forecast the number of students who will seek appointments.He has gathered the following data:
Week # of students
6 weeks ago 83
5 weeks ago 110
4 weeks ago 95
3 weeks ago 80
2 weeks ago 65
Last week 50
-What is the forecast for this year using a moving-average forecast based on the last three weeks?
A)49 
B)50 
C)52 
D)65 
E)78

Accepted Answer

The answer of Professor Z needs to allocate time among...

Question 9

The primary method for causal forecasting is:
A)sensitivity analysis 
B)linear regression 
C)moving-average 
D)exponential smoothing 
E)the Delphi method

Accepted Answer

Linear regression is the primary method for causal forecasting as it helps to establish a relationship between the independent and dependent variables. It helps to identify the variable that is causally related to the dependent variable and predict the future values of the dependent variable based on changes in the independent variable. Sensitivity analysis, moving-average, exponential smoothing, and the Delphi method are useful techniques in their own right, but they are not the primary method for causal forecasting.

Question 10

The business analyst for Ace Business Machines,Inc.wants to forecast this year's demand for manual typewriters based on the following historical data:
Time Period :Demand
5 years ago :900
4 years ago : 700
3 years ago : 600
2 years ago :500
Last year :300
-What is the forecast for this year using exponential smoothing with $\alpha$ = 0 4,if the forecast for two years ago was 750?
A)163 
B)180 
C)300 
D)467 
E)510

Accepted Answer

We can use the formula for exponential smoothing to find the forecast:

Ft = α(Dt-1) + (1-α)Ft-1

where:
Ft = forecast for this year
α = smoothing coefficient (given as 0.4)
Dt-1 = demand from the previous year
Ft-1 = forecast from the previous year

Plugging in the given values, we get:

Ft = 0.4(300) + 0.6(750)
Ft = 120 + 450
Ft = 570

Therefore, the forecast for this year using exponential smoothing is 570, which corresponds to choice E.

Question 11

The previous trend line has predicted 18,500 for two years ago,and 19,700 for last year What was the mean absolute deviation for these forecasts?
A)100 
B)200 
C)400 
D)500 
E)800

Accepted Answer

Mean absolute deviation (MAD) measures how far the data points are from the predicted value. To calculate MAD, you take the absolute value of the difference between each actual value and the predicted value, sum them up, and divide by the total number of data points. 
For two years ago, the predicted value was 18,500 and we don't know the actual value, so we can't calculate MAD for that year. For last year, the predicted value was 19,700, let's say the actual value was 20,000, then the MAD would be:
|20,000 - 19,700| = 300
So the MAD for last year was 300. Since we only have one data point to calculate MAD, that's the only answer choice we can pick.

Question 12

Which of the following would be considered a possible drawback of using executive opinions to develop a forecast?
A)It is difficult to interpret the results 
B)Responsibility is diffused for the forecast 
C)Extensive use of computers is needed 
D)It brings together the knowledge of top managers 
E)Forecasters are sometimes overly influenced by recent events

Accepted Answer

The answer of Which of the following would be considered...

Question 13

Questions 10-66 through 10-69 refer to the following:
An operation analyst is forecasting this year's demand for one of his company's products based on the following historical data:
Year # sold
4 years ago 10,000
3 years ago 12,000
2 years ago 18,000
Last year 20,000
-What is the forecast for this year using a moving-average forecast based on the last four years?
A)22,000 
B)20,000 
C)18,000 
D)15,000 
E)12,000

Accepted Answer

The moving-average forecast is calculated by averaging the number of units sold over the last four years: (10,000 + 12,000 + 18,000 + 20,000) / 4 = 15,000.

Question 14

The equation y = 350 - 2 5x is used to predict quarterly demand where x = 0 in the second quarter of last year Quarterly seasonal factors are Q1 = 1 5,Q2 = 0 8,Q3 = 1 1,and Q4 = 0 6 What is the forecast for the last quarter of this year?
A)199 5 
B)201 
C)266 
D)268 
E)335

Accepted Answer

The answer of The equation y = 350 - 2...

Question 15

Professor Z needs to allocate time among several tasks next week to include time for students' appointments.Thus,he needs to forecast the number of students who will seek appointments.He has gathered the following data:
Week # of students
6 weeks ago 83
5 weeks ago 110
4 weeks ago 95
3 weeks ago 80
2 weeks ago 65
Last week 50
-What is the forecast for this year using exponential smoothing with trend if $\alpha$ = 0 5 and $\beta$ = 0 1? Assume the forecast for last week was 65 and the forecast for two weeks ago was 75 ,and that the trend estimate for last years forecast was -5 
A)49 
B)50 
C)52 
D)65 
E)78

Accepted Answer

We will use the formula for exponential smoothing with trend:

Ft = α(At-1 + Tt-1) + (1-α)(Ft-1)

where At is the actual value, Tt-1 is the trend estimate, and Ft-1 is the forecast for the previous period.

Given:

α = 0.5
β = 0.1
F1 = 65 (forecast for two weeks ago)
F2 = 75 (forecast for last week)
T1 = -5 (trend estimate for last year's forecast)
F0, T0 are not given, but we can assume they are both 0.

Using this information, we can calculate the forecast for this week:

F3 = α(A2 + T2) + (1-α)(F2)
    = 0.5(110 - 75) + 0.5(65)
    = 52.5

Therefore, the forecast for this week is 52 students seeking appointments. The closest answer choice is (C) 52.

Question 16

Which of the following would be an advantage of using a sales force composite to develop a demand forecast?
A)The sales staff is least affected by changing customer needs 
B)The sales force can easily distinguish between customer desires and probable actions 
C)The sales staff is often aware of customer's future plans 
D)Salespeople are least likely to be biased by sales quotas 
E)None of the above

Accepted Answer

The advantage of using sales force composite to develop a demand forecast is that sales staff is often aware of customer's future plans which can help in creating a more accurate forecast. The other options are not necessarily true, as sales staff can also be affected by changing customer needs, have biases due to sales quotas, and may not always be able to distinguish between customer desires and probable actions.

Quiz 10: Forecasting

Which of the following is not a type of judgmental forecasting?

The forecasting method which uses anonymous questionnaires to achieve a consensus forecast is:

A manager uses the equation y = 40,000 + 150x to predict monthly receipts What is the forecast for July if x = 0 in April?

The primary method for causal forecasting is:

The previous trend line has predicted 18,500 for two years ago,and 19,700 for last year What was the mean absolute deviation for these forecasts?

Which of the following would be considered a possible drawback of using executive opinions to develop a forecast?

The equation y = 350 - 2 5x is used to predict quarterly demand where x = 0 in the second quarter of last year Quarterly seasonal factors are Q1 = 1 5,Q2 = 0 8,Q3 = 1 1,and Q4 = 0 6 What is the forecast for the last quarter of this year?

Which of the following would be an advantage of using a sales force composite to develop a demand forecast?