In order to take advantage of the burgeoning public interest in sustainability, Klorax has developed a nonsynthetic line of natural cleaning products called GreenClean. One of the first sustainable products Klorax introduced was a natural cold-water detergent. The company has now gathered several years’ worth of sales data for this product in order to develop various forecast models. The company’s marketing department believes that sales increase when there are several major environmental (i.e., “green”) episodes in the national media, such as a government energy report, an increase in gasoline or energy prices, an oil spill, a pollution episode, a company getting positive press for undertaking a major green project, and so on. Therefore, the marketing department wants to develop a linear regression forecasting model that relates the number of green episodes reported monthly in the national media to monthly sales of the detergent. The marketing department had several staff members go through various media sources for the past 2 years and count the number of major national green episodes reported on, which with monthly sales, is shown in the following table:

Month Sales Green Episodes Month Sales Green Episodes 1 34,175 3 13 55,732 7 2 28,366 2 14 26,004 4 3 41,819 4 15 49,188 5 4 27,666 1 16 40,005 2 5 31,299 1 17 38,912 2 6 37,456 4 18 31,777 1 7 52,444 5 19 30,367 0 8 46,712 3 20 34,566 1 9 37,222 2 21 29,078 1 10 44,981 2 22 45,876 3 11 40,006 2 23 48,556 4 12 47,321 4 24 51,022 6 Develop a linear regression model and determine the sales forecast if three green episodes are reported in the media next month. Discuss the value and usefulness of this type of relational forecast for Klorax.

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