Presentation is loading. Please wait.

Presentation is loading. Please wait.

Quantitative Decision Making 7 th ed By Lapin and Whisler.

Published byBrook Ray Modified over 8 years ago

Similar presentations

Presentation on theme: "Quantitative Decision Making 7 th ed By Lapin and Whisler."— Presentation transcript:

1 Quantitative Decision Making 7 th ed By Lapin and Whisler

2  Y t = T t ·C t ·S t ·I t  T t : The trend component  C t : The cyclic component  S t : The seasonal component  I t : The irregular component

3 1. Isolate trend and cyclical elements together. 2. Four-quarter moving averages

4 1. Add up the first four values in a time series, then divide by four. 2. Repeat this computation, but the initial quarter is dropped and the fifth is added. 3. Continue this process until you run out of new quarters.

5 YearQuarterDataFour Quarter Moving Average 1175 260 =(75+60+54+59)/4 = 62 354 =(60+54+59+86)/4 = 64.75 459 =(54+59+86+65)/4 = 66 2186 =(59+86+65+63)/4 = 68.25 265 =(86+65+63+80)/4 = 73.5 363 480

6 YearQuarterDataFour Quarter Moving Average/ Centered Moving Average 1175 260 =(75+60+54+59)/4 = 62 354=(62+64.75)/2 = 63.375 =(60+54+59+86)/4 = 64.75 459=(64.75+66)/2 = 65.375 =(54+59+86+65)/4 = 66 2186=(66+68.25)/2 = 67.125 =(59+86+65+63)/4 = 68.25 265=(68.25+73.5)/2 = 70.875 =(86+65+63+80)/4 = 73.5 363 480

7 YearQuarterData Four Quarter Moving Average/ Centered Moving Average Original as percentage of moving average 1175 260 =(75+60+54+59)/4 = 62 354=(62+64.75)/2 = 63.375=(54/63.375) x 100 =85.21 =(60+54+59+86)/4 = 64.75 459=(64.75+66)/2 = 65.375=(59/65.375) x 100 = 90.25 =(54+59+86+65)/4 = 66 2186=(66+68.25)/2 = 67.125=(86/67.125) x 100 = 128.12 =(59+86+65+63)/4 = 68.25 265=(68.25+73.5)/2 = 70.875=(65/70.875) x 100 = 91.71 =(86+65+63+80)/4 = 73.5 363 480

8 Calculating Seasonal Indices YearQuarter 1234 1-------85.2190.25 2128.1291.7185.13106.14 3117.4592.7585.13104.29 4117.9992.03--- Median117.9992.0385.13104.29 Sum of Medians: 399.44 Seasonal Index = Median x (400/399.44) Seasonal Indices 118.1692.1685.25104.44

9 YearQuarterDataFour Quarter Moving Average/ Centered Moving Average Original as percentage of moving average Seasonal Indices 1175 118.16 260 92.16 =(75+60+54+59)/4 = 62 354=(62+64.75)/2 = 63.375=(54/63.375) x 100 =85.21 85.25 =(60+54+59+86)/4 = 64.75 459=(64.75+66)/2 = 65.375=(59/65.375) x 100 = 90.25 104.44 =(54+59+86+65)/4 = 66 2186=(66+68.25)/2 = 67.125=(86/67.125) x 100 = 128.12 118.16 =(59+86+65+63)/4 = 68.25 265=(68.25+73.5)/2 = 70.875=(65/70.875) x 100 = 91.71 92.16 =(86+65+63+80)/4 = 73.5 363 85.25 480 104.44

Download ppt "Quantitative Decision Making 7 th ed By Lapin and Whisler."

Similar presentations

Mean, Median, Mode, and Range. Mean Mean: Average 1)First, order the numbers from least to greatest. 2)Next, add the numbers in the data set. 3)Then,

Mean, Median, Mode, and Range. Mean Mean: Average 1)First, order the numbers from least to greatest. 2)Next, add the numbers in the data set. 3)Then,
Exercise 7.5 (p. 343) Consider the hotel occupancy data in Table 6.4 of Chapter 6 (p. 297)

Exercise 7.5 (p. 343) Consider the hotel occupancy data in Table 6.4 of Chapter 6 (p. 297)
19- 1 Chapter Nineteen McGraw-Hill/Irwin © 2005 The McGraw-Hill Companies, Inc., All Rights Reserved.

19- 1 Chapter Nineteen McGraw-Hill/Irwin © 2005 The McGraw-Hill Companies, Inc., All Rights Reserved.
Ka-fu Wong © 2003 Chap 19- 1 Dr. Ka-fu Wong ECON1003 Analysis of Economic Data.

Ka-fu Wong © 2003 Chap Dr. Ka-fu Wong ECON1003 Analysis of Economic Data.
Chapter 5 Time Series Analysis

Chapter 5 Time Series Analysis
Using a Centered Moving Average to Extract the Seasonal Component of a Time Series If we are forecasting with say, quarterly time series data, a 4-period.

Using a Centered Moving Average to Extract the Seasonal Component of a Time Series If we are forecasting with say, quarterly time series data, a 4-period.
1 Pertemuan 23 Deret Berkala, Peramalan, dan Angka Indeks-1 Matakuliah: A0064 / Statistik Ekonomi Tahun: 2005 Versi: 1/1.

1 Pertemuan 23 Deret Berkala, Peramalan, dan Angka Indeks-1 Matakuliah: A0064 / Statistik Ekonomi Tahun: 2005 Versi: 1/1.
Section 7.2: Exponential Smoothing Quantitative Decision Making 7 th ed By Lapin and Whisler.

Section 7.2: Exponential Smoothing Quantitative Decision Making 7 th ed By Lapin and Whisler.
Part II – TIME SERIES ANALYSIS C2 Simple Time Series Methods & Moving Averages © Angel A. Juan & Carles Serrat - UPC 2007/2008.

Part II – TIME SERIES ANALYSIS C2 Simple Time Series Methods & Moving Averages © Angel A. Juan & Carles Serrat - UPC 2007/2008.
Mean and Median Math .

Mean and Median Math .
X-12 ARIMA Eurostat, Luxembourg Seasonal Adjustment.

X-12 ARIMA Eurostat, Luxembourg Seasonal Adjustment.
Time series Decomposition Additive Model Farideh Dehkordi-Vakil.

Time series Decomposition Additive Model Farideh Dehkordi-Vakil.
McGraw-Hill/Irwin Copyright © 2010 by The McGraw-Hill Companies, Inc. All rights reserved. Time Series and Forecasting Chapter 16.

McGraw-Hill/Irwin Copyright © 2010 by The McGraw-Hill Companies, Inc. All rights reserved. Time Series and Forecasting Chapter 16.
Time Series and Forecasting

Time Series and Forecasting
CHAPTER 18 Models for Time Series and Forecasting

CHAPTER 18 Models for Time Series and Forecasting
Think about it... Do you know what mean, median, mode, and range are?

Think about it... Do you know what mean, median, mode, and range are?
Measures of Central Tendancy Lesson 6.05 Vocabulary Review Sum – the answer to an addition problem. Addend – the numbers you added together to get the.

Measures of Central Tendancy Lesson 6.05 Vocabulary Review Sum – the answer to an addition problem. Addend – the numbers you added together to get the.
1 1 Slide © 2009 South-Western, a part of Cengage Learning Chapter 6 Forecasting n Quantitative Approaches to Forecasting n Components of a Time Series.

1 1 Slide © 2009 South-Western, a part of Cengage Learning Chapter 6 Forecasting n Quantitative Approaches to Forecasting n Components of a Time Series.
Slides by John Loucks St. Edward’s University.

Slides by John Loucks St. Edward’s University.
Time-Series Analysis and Forecasting – Part IV To read at home.

Time-Series Analysis and Forecasting – Part IV To read at home.

Similar presentations

Ads by Google