The manager of Sarah€™s Ice Cream store needs an accurate forecast of the demand for ice cream. The store orders ice cream from a distributor a week ahead, and if too little is ordered the store loses business. If it orders too much, it must be thrown away. The manager believes that a major determinant of ice cream sales is temperature; that is, the hotter it is, the more ice cream people buy. Using an almanac, the manager has determined the average daytime temperature for 10 weeks selected at random and then, from store records, has determined the ice cream consumption for the same 10 weeks. The data are summarized as follows:

a. Develop a linear regression model for this data and fore-cast the ice cream consumption if the average weekly day-time temperature is expected to be 27°C.
b. Determine the strength of the linear relationship between temperature and ice cream consumption using correlation.

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Temperature (°C) Week (Litres Sold) 24 95 19 90 28 125 4 32 150 25 85 27 115 7 29 110 33 145 32 130 10 18 100