Maestra

CHAPTER

15

Time Series Analysis
and Forecasting
CONTENTS
STATISTICS IN PRACTICE:
NEVADA OCCUPATIONAL
HEALTH CLINIC
15.1 TIME SERIES PATTERNS
Horizontal Pattern
Trend Pattern
Seasonal Pattern
Trend and Seasonal Pattern
Cyclical Pattern
Using Excel’s Chart Tools
to Construct a Time
Series Plot
Selecting a Forecasting Method
15.2 FORECAST ACCURACY
15.3 MOVING AVERAGES
ANDEXPONENTIAL
SMOOTHING
Moving Averages
Using Excel’s Moving
Average Tool
Weighted Moving Averages
Exponential Smoothing
Using Excel’s Exponential
Smoothing Tool

15.4 TREND PROJECTION
Linear Trend Regression
Using Excel’s Regression Tool
to Compute a Linear
Trend Equation
Nonlinear Trend Regression
Using Excel’s Regression Tool
to Compute a Quadratic
Trend Equation
Using Excel’sChart Tools for
Trend Projection
15.5 SEASONALITY AND TREND
Seasonality Without Trend
Seasonality and Trend
Models Based on Monthly Data
15.6 TIME SERIES
DECOMPOSITION
Calculating the Seasonal Indexes
Deseasonalizing the Time Series
Using the Deseasonalized Time
Series to Identify Trend
Seasonal Adjustments
Models Based on Monthly Data
Cyclical Component

© 2012 Cengage Learning. AllRights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.

15-2

STATISTICS

Chapter 15

Time Series Analysis and Forecasting

in PRACTICE

NEVADA OCCUPATIONAL HEALTH CLINIC*
Nevada Occupational Health Clinic is a privately owned
medical clinic in Sparks, Nevada. The clinic specializes
in industrial medicine.Operating at the same site for
more than 20 years, the clinic had been in a rapid growth
phase. Monthly billings increased from $57,000 to more
than $300,000 in 26 months, when the main clinic building burned to the ground.
The clinic’s insurance policy covered physical property and equipment as well as loss of income due to the
interruption of regular business operations. Settling the
propertyinsurance claim was a relatively straightforward
matter of determining the value of the physical property
and equipment lost during the fire. However, determining
the value of the income lost during the seven months that
it took to rebuild the clinic was a complicated matter
involving negotiations between the business owners and the
insurance company. No preestablished rules could helpcalculate “what would have happened” to the clinic’s
billings if the fire had not occurred. To estimate the lost income, the clinic used a forecasting method to project the
growth in business that would have been realized during
the seven-month lost-business period. The actual history of
billings prior to the fire provided the basis for a forecasting
model with linear trend and seasonal componentsas
*The authors are indebted to Bard Betz, Director of Operations, and
Curtis Brauer, Executive Administrative Assistant, Nevada Occupational
Health Clinic, for providing this Statistics in Practice.

A forecast is simply a
prediction of what will
happen in the future.
Managers must learn to
accept that regardless of
the technique used, they
will not be able to develop
perfectforecasts.

© Bob Pardue–Medical Lifestyle/Alamy.

SPARKS, NEVADA

A physician checks a patient’s blood pressure at
the Nevada Occupational Health Clinic.
discussed in this chapter. This forecasting model enabled
the clinic to establish an accurate estimate of the loss,
which was eventually accepted by the insurance company.

The purpose of this chapter is to provide an introduction to timeseries analysis and forecasting. Suppose we are asked to provide quarterly forecasts of sales for one of our company’s products over the coming one-year period. Production schedules, raw material
purchasing, inventory policies, and sales quotas will all be affected by the quarterly forecasts we provide. Consequently, poor forecasts may result in poor planning and increased
costs for the company....