PDF- Chapter 3, PHAK Chapter 3, -Title 305 - NEBRASKA REAL ESTATE COMMISSION Chapter 3 - Chapter-3


Chapter- 3 (FORECASTING) 1

What are some of the consequences of poor forecasts

What advantages as a forecasting tool does exponential smoothing have over moving averages

What factors enter into the choice of a value for the smoothing constant in exponential smoothing

Contrast the terms ‘sales’ and ‘demand’

Contrast the reactive and proactive approaches to forecasting

Give several examples of types of organizations or situations in which each type is used

Which type of forecasting approach,

Choose the type of forecasting technique (survey,


or associative) that would be most appropriate a) b) c) d)

for predicting Demand for Mother’s Day greeting cards

Popularity of a new television series

Demand for vacations on the moon

The impact of a price increase of 10 percent would have on sales of

e) Demand for toothpaste in a particular supermarket

Explain the trade-off between responsiveness and stability in a forecasting system that uses time series data

A commercial bakery has recorded sales (in dozens) for three products,

as shown below: Day 1 2 3 4 5 6 7 8 9 10 11

Blueberry Muffins 30 34 32 34 35 30 34 36 29 31 35

Cinnamon Buns 18 17 19 19 22 23 23 25 24 26 27

Cupcakes 45 26 27 23 22 48 29 20 14 18 47

a) Predict orders for the following day for each of the products using an appropriate naive method

(Hint: Plot each data set) b) What should the use of sales data instead of demand imply

National Scan,

sells radio frequency inventory tags


sale for a seven-month period were as follows: Month Feb

May Jun

Sales (000 units) 19 18 15 20 18 22 20

Forecast September sales volume using each of the following: I

A five-month moving average II

Exponential smoothing with a smoothing constant equal to

assuming a march forecast of 19(000)

The naïve approach A weighted average using

Which method seems least appropriate

? (Hint: Refer to your plot from part a

What does use of the term sales rather than demand presume

An electrical contractor’s records during the last five weeks

indicate the number of job requests: Week:


Predict the number of requests for week 6 using each of these methods: a

Naive b

A four-period moving average

Exponential smoothing with α =

Use 20 for week 2 forecast

A tourist center is open on weekends (Friday,



The owner-manager hopes to improve scheduling of part-time employees by determining seasonal relatives for each of these days

Data on recent traffic at the center have been tabulated and are shown in the following table:

Friday Saturday Sunday

WEEK 3 152 260 171

Use naïve and simple average technique to predict sales transactions for the following week

Obtain estimates of daily relatives for the number of customers

at a restaurant for the evening meal,

(Hint: Use a seven-day moving average

Number Served 80 75 78 95 130 136 40 82 77 80

Day 15 16 17 18 19 20 21 22 23 24

Number Served 84 78 83 96 135 140 44 87 82 88