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Data Quality for Analytics Using SAS by Gerhard Svolba

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Chapter 21: Consequences of Data Quantity and Data Completeness in Time Series Forecasting

21.1 Introduction

21.2 Effect of the Length of the Available Time History

General

Simulation procedure

Graph results

Interpretation

Results in numbers

Business case calculation

21.3 Optimal Length of the Available Time History

General

Results

Interpretation

21.4 Conclusion

General

Data relevancy

Self-assessment of time series data

21.1 Introduction

This chapter examines the influence of the length of the available data history of a time series on the quality of the forecast for future periods. The results of simulation studies that are presented in this chapter address the importance of long time histories to performing good time series forecasting.

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