Questions from Business Statistics

Q: a. Name the four basic components of a monthly or quarterly

a. Name the four basic components of a monthly or quarterly time series, from the trend-seasonal approach. b. Carefully distinguish the cyclic and the irregular components.

Q: a. How is the moving average different from the original series

a. How is the moving average different from the original series? b. For trend-seasonal analysis, why do we use exactly 1 year of data at a time in the moving average? c. Which components remain in the...

Q: a. How do you compute the ratio-to-moving

a. How do you compute the ratio-to-moving-average? Which components does it represent? b. What do you do to the ratio-to-moving-average to produce a seasonal index? Why does this work? c. What does a...

Q: Consider annual salary as the Y variable and age as the X

Consider annual salary as the Y variable and age as the X variable. a. Draw a scatterplot and describe the relationship. b. Find the correlation coefficient. What does it tell you? Is it appropriate,...

Q: a. How is a linear trend estimated in trend-seasonal

a. How is a linear trend estimated in trend-seasonal analysis? b. What kind of forecast does the linear trend represent? c. What do you do to produce a forecast from the linear trend? d. Which compone...

Q: a. How is the flexibility of the Box-Jenkins ARIMA

a. How is the flexibility of the Box-Jenkins ARIMA process approach helpful in time-series analysis? b. What is parsimony? c. How does the forecast relate to the actual future behavior of the estimate...

Q: a. Define the random noise process in terms of the relationship

a. Define the random noise process in terms of the relationship between successive observations. b. Comment on the following: If it is a random noise process, then special time-series methods are not...

Q: a. Define a first-order autoregressive process in terms of

a. Define a first-order autoregressive process in terms of the relationship between successive observations. b. What are the X and Y variables in the regression model to predict the next observation i...

Q: Explain in what sense the analysis of variance involves actually analyzing variance

Explain in what sense the analysis of variance involves actually analyzing variance—in particular, what variances are analyzed and why?

Q: a. What kind of data set should be analyzed using the

a. What kind of data set should be analyzed using the one-way analysis of variance? b. Why should not you use the unpaired t test instead of the one-way analysis of variance?