1. This problem requires conceptualization.

1. If a collection of paired data includes at least three pairs of values, what do you know about the linear correlation coefficient if s _e = 0?
2. If a collection of paired data is such that the total explained variation is 0, what do you know about the slope of the regression line?

1. Use the given time series values and seasonal indexes to find the seasonally adjusted values.
   1. (3) For the second quarter of a year, a company’s revenues total $856,750. The seasonal index for the second quarter is 1.183 .
   2. (12) For one year, the quarterly net earnings for a company are $82,600. $105,200, $96,700, and $93,800. The corresponding seasonal indexes are 0.873, 1.112, 1.022, and 0.992.
2. Use the given trend equation and the seasonal indexes to forecast values for the indicated time periods.

3. (3) The coded time period of x = 15 corresponds to the seasonal index of 1.050, and the trend equation is T = 12.6 + 2.57x. Forecast the value of the time series corresponding to the time period represented by x = 15.

4. (12) The coded time periods of x = 15, 16, 17, and 18 correspond to the seasonal indexes of 1.050, 0.885, 0.955, and 1.110, respectively. The trend equation is T = -34.7 + 6.22x. Forecast the values of the time series corresponding to the time periods represented by the given values of x.

IV. Isolate the irregular component of the given time series multiplicative model.

9. (1) It is known that the S x I value of new housing starts in the third quarter of the first year of tracking is 1.174. The seasonal index is 1.149. Find I, rounded to the nearest thousandth. (Show your solution.)

Price: $8.64

Solution: The downloadable solution consists of 4 pages, 464 words.
Deliverable: Word Document