Create prediction interval for daily sales regression line


An ice cream vendor would like to predict daily sales of ice cream cones based on the temperature outdoors. Data for a random sample of 8 days are provided in the table below.

Temperature (OC) Daily Sales {Litres)

(x) (y)

6 135
8 50
12 125
16 100
18 200
22 150
28 250
28 175

The regression line with "daily sales" as the dependent variable and "temperature" as the independent variable has been calculated as:
yhat = 55.217 + 5.38597x

You may use the following sums of squares and cross products for the questions below.

Σx=138 Σy=1185

SSxx=495.5 SSyy=26446.875 SSxy=2668.75

a) Using the regression line and sums of squares and cross products provided above, construct a 90% prediction interval for daily sales when the outside temperature is 24 degrees Celsius.

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Basic Statistics: Create prediction interval for daily sales regression line
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