Explanation of time series analysis for demand forecasting

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Reference no: EM132202347

1. What is an essential feature of a company being a separate legal entity?

a. The company’s obligations and property are separate from those of its participants

b. The company is attached to another business or individual with respect to accountability

c. The company is not separate from the people that run the company and own it

d. The company's obligations and property are its own and those of its participants

2. In a multiple regression model, by calculating the p-value of each variable we can assess the significance of the:

A) dependent variable

B) entire problem only if you take the square root and divide by 5

C) the mean

D) independent variables

E) slope

3. What is not true about the explanation of time series analysis for demand forecasting? (The answer can be one or more)

1) Time series analysis is based on the assumption that the past pattern of demand, which is a dependent variable, will continue in the future.

2) The former demand method is a technique to forecast demand for the next period with the latest demand, and can be used effectively when the demand is stable.

3) The moving average method is a useful technique when only random variation is largely applied. The latest n period data can be arithmetically averaged or weighted averaged to forecast the demand for the next period.

4) Trend analysis can predict future demand by finding a straight trend line that minimizes the sum of the errors between the past demand and trend forecasts, if there is a noticeable increase or decrease in the past data.

5) The exponential smoothing method can analyze trends and seasonal variations, but even if the smoothing constant is reduced, the weight of recent demand data can not be imposed less than the weight of past demand data.

Reference no: EM132202347

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