Question 1

Which of the following statements is TRUE?

Accepted Answer

A)  Residual variation cannot be determined for time series data 
B)  Residual variation may only be calculated for time series data when more than 10 data points exist 
C)  Residual variation is usually insignificant and so calculating it has little value in practice 
D)  Residual variation can be calculated when trend values and seasonal variation are known 
A)  Residual variation cannot be determined for time series data 
B)  Residual variation may only be calculated for time series data when more than 10 data points exist 
C)  Residual variation is usually insignificant and so calculating it has little value in practice 
D)  Residual variation can be calculated when trend values and seasonal variation are known D

Question 2

Which of the following options BEST describes seasonal variation?

Accepted Answer

A)  The influence of short-term cyclic variation 
B)  The influence of long-term cyclic variation 
C)  The influence of a long-term upwards trend in the data 
D)  The influence of a long-term downwards trend in the data 
A)  The influence of short-term cyclic variation 
B)  The influence of long-term cyclic variation 
C)  The influence of a long-term upwards trend in the data 
D)  The influence of a long-term downwards trend in the data A

Question 3

In which of the following situations would seasonal variation be LEAST important?

Accepted Answer

A)  Predicting the sale of beachwear during a year 
B)  Predicting the demand for gas over the course of a year 
C)  Predicting demand for ski holidays in the European Alps 
D)  Predicting changes to the Hong Kong Stock Exchange index 
A)  Predicting the sale of beachwear during a year 
B)  Predicting the demand for gas over the course of a year 
C)  Predicting demand for ski holidays in the European Alps 
D)  Predicting changes to the Hong Kong Stock Exchange index D

Question 4

Which of the following statements concerning forecasting is NOT true?

Accepted Answer

A)  In some cases, simple estimation of likely future trends is sufficient 
B)  Structured forecasts, using statistics, can be relied upon to be accurate 
C)  Forecasting allows us to estimate future performance based on historical trends 
D)  Before making a large investment, structured forecasting may be necessary 
A)  In some cases, simple estimation of likely future trends is sufficient 
B)  Structured forecasts, using statistics, can be relied upon to be accurate 
C)  Forecasting allows us to estimate future performance based on historical trends 
D)  Before making a large investment, structured forecasting may be necessary

Question 5

The range of trend factors for data indicating the sales of French wine (in millions of litres) are 2.4 to 3.8 - there are 6 trend values. Assuming a value of S of 0.65, estimate the next value in the sequence (2 decimal places).

Accepted Answer

A)  2.29 
B)  2.59 
C)  3.52 
D)  3.98 
A)  2.29 
B)  2.59 
C)  3.52 
D)  3.98

Question 6

Which option BEST describes the purpose of seasonally adjusting time series data?

Accepted Answer

A)  Adjusting data to give a picture of data 'as if seasons had not existed' 
B)  Adjusting data so that the seasonal variation is constant 
C)  Adjusting data so that the seasonal variation is reduced by half 
D)  Adjusting data to show the impact of seasonal differences 
A)  Adjusting data to give a picture of data 'as if seasons had not existed' 
B)  Adjusting data so that the seasonal variation is constant 
C)  Adjusting data so that the seasonal variation is reduced by half 
D)  Adjusting data to show the impact of seasonal differences

Question 7

Using the additive model for time series forecasting, estimate the the value of y when t = 5.2 (year 5 quarter 2). In year 1, quarter 1 the value of t is 20 (with an upward trend of 5 per quarter). s = +23 for quarter 2.

Accepted Answer

A)  113 
B)  118 
C)  123 
D)  128 
A)  113 
B)  118 
C)  123 
D)  128

Question 8

Which value of s indicates that seasonal variation for the given time period deflates the trend by 6?

Accepted Answer

A)  +6 
B)  -6 
C)  +0.6 
D)  -0.6 
A)  +6 
B)  -6 
C)  +0.6 
D)  -0.6

Question 9

In the multiplicative model, seasonal adjustment is made by dividing the value of y by S. Which of the following options is the correct formula for S?

Accepted Answer

A)  S = 1 - (y-t)/t 
B)  S = 1 + (y+t)/t 
C)  S = 1+ (y-t)/t 
A)  S = 1 - (y-t)/t 
B)  S = 1 + (y+t)/t 
C)  S = 1+ (y-t)/t

Question 10

In which of the following situations will the forecast be MOST accurate?

Accepted Answer

A)  When the residual factor is large 
B)  When the residual factor is small 
C)  When the residual factor equals the seasonal factor 
D)  When the residual factor is equal to the mean of the time series data 
A)  When the residual factor is large 
B)  When the residual factor is small 
C)  When the residual factor equals the seasonal factor 
D)  When the residual factor is equal to the mean of the time series data

Exam 17: Seasonal Variation and Forecasting

Which of the following statements is TRUE?

Which of the following options BEST describes seasonal variation?

In which of the following situations would seasonal variation be LEAST important?

Which of the following statements concerning forecasting is NOT true?

The range of trend factors for data indicating the sales of French wine (in millions of litres) are 2.4 to 3.8 - there are 6 trend values. Assuming a value of S of 0.65, estimate the next value in the sequence (2 decimal places).

Which option BEST describes the purpose of seasonally adjusting time series data?

Using the additive model for time series forecasting, estimate the the value of y when t = 5.2 (year 5 quarter 2). In year 1, quarter 1 the value of t is 20 (with an upward trend of 5 per quarter). s = +23 for quarter 2.

Which value of s indicates that seasonal variation for the given time period deflates the trend by 6?

In the multiplicative model, seasonal adjustment is made by dividing the value of y by S. Which of the following options is the correct formula for S?

In which of the following situations will the forecast be MOST accurate?

Introduction to Business Mathematics and Statistics

Sampling and Data Collection

Data and Their Accuracy

Frequency Distributions and Charts

General Charts and Graphs

Arithmetic Mean

Median

Mode and Other Measures of Location

Measures of Dispersion and Skewness

Standard Deviation

Quantiles and the Quartile Deviation

Linear Functions and Graphs

Regression Techniques

Correlation Techniques

Time Series Model

Time Series Trend

Index Relatives

Composite Index Numbers

Special Published Indices

Interest and Depreciation

Present Value and Investment Appraisal

Annuities

Functions and Graphs

Linear Equations

Quadratic and Cubic Equations

Differentiation and Integration

Cost, Revenue and Profit Functions

Set Theory and Enumeration

Introduction to Probability

Conditional Probability and Expectation

Combinations and Permutations

Binomial and Poisson Distributions

Normal Distribution

Linear Inequalities

Matrices

Inventory Control

Network Planning and Analysis

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