Books & Videos

Table of Contents

Chapter: Introduction


04m 37s

Chapter: Lesson 1 Simple Exponential Smoothing: A Review

Learning Objectives

01m 0s

1.1 Prepare data for exponential smoothing

04m 6s

1.2 Carry out a simple exponential smoothing analysis

16m 29s

1.3 Quantify the accuracy of forecasts

15m 51s

Chapter: Lesson 2 Smoothing and Its Notation

Learning Objectives

01m 20s

2.1 Optimize forecasts using Excel's Solver add-in

12m 17s

2.2 Interpret smoothing analyses presented in various sources

13m 15s

2.3 Resolve apparent discrepancies in smoothing equations

13m 39s

Chapter: Lesson 3 Characteristics of Trend in a Time Series

Learning Objectives

01m 55s

3.1 Understand why simple exponential smoothing works poorly with a trended series

13m 13s

3.2 Interpret a correlation coefficient in terms of standard scores

13m 6s

3.3 Understand how autocorrelation helps to characterize baselines

13m 0s

Chapter: Lesson 4 Diagnosing Trend with Least Squares

Learning Objectives

01m 23s

4.1 Use LINEST() and TREND() functions to support smoothing forecasts

17m 20s

4.2 Understand the limitations of regression forecasts

14m 43s

4.3 Evaluate a forecasting model by analyzing residuals

10m 57s

Chapter: Lesson 5 Diagnosing Trend: The Autocorrelation Function and the Concept of Lags

Learning Objectives

01m 49s

5.1 Distinguish the methods of the ACF from those of the Pearson correlation

11m 30s

5.2 Use the ACF add-in to create and interpret ACF correlograms

10m 15s

5.3 Interpret correlograms to help evaluate borderline cases

05m 0s

Chapter: Lesson 6 Differencing

Learning Objectives

01m 10s

6.1 Detrend a baseline using first differences

07m 19s

6.2 Forecast the baseline's first differences

07m 51s

6.3 Reintegrate the forecast differences into the baseline

04m 50s

Chapter: Lesson 7 The Forecast Equation for Trend

Learning Objectives

01m 21s

7.1 Use Holt's double exponential smoothing method to forecast trended time series

09m 51s

7.2 Use either the smoothing or the error correction formulas to forecast from a trended baseline

13m 14s

7.3 Use defined names and relative references to derive self-documenting formulas

24m 21s

Chapter: Lesson 8 Initializing Values

Learning Objectives

01m 20s

8.1 Employ standard methods to initialize forecast values

09m 43s

8.2 Backcast via smoothing to Period 0 in a stationary baseline

10m 20s

8.3 Backcast via smoothing to Period 0 in a trended baseline

07m 44s

Chapter: Summary


02m 37s