Chapter 9, Problem 8PA

a

Summary Introduction

Interpretation:the given data is to be represented graphically along with its interpretation.

Concept Introduction:

Time series forecasting models use the previous data. The various methods are moving average, exponential smoothening method. A time series method can compute the forecast more precisely if only two period data is given whereas it is not possible to do so in regression technique.

b

Summary Introduction

Interpretation:Best numbers of weeks are to be calculated based on MSE.

Concept Introduction:

MSE(Mean Square Error) is the most common way to measure the forecast accuracy. Forecasting error is the difference between Actual data and Forecasted data.

c

Summary Introduction

Interpretation:Best single exponential smoothening model to forecast data is to be determined.

Concept Introduction:

Exponential smoothening is a moving average approach that applies exponentially decreasing weights to each demand.