Final answer:
To fit a simple linear regression model to the sales data, you would need to find the equation of the line of best fit, which is represented by ŷ = a + bx. Using the given equation ŷ = 101.32 + 2.48x, you can plug in the values of x (day) to predict the sales on a particular day.
Step-by-step explanation:
A simple linear regression model can be used to predict the sales data. In order to fit a simple linear regression model, you would need to have a set of data with two variables: the independent variable (x) and the dependent variable (y). In this case, the independent variable would be the day and the dependent variable would be the sales.
To fit the model, you would need to find the equation of the line of best fit, which is represented by the equation ŷ = a + bx. Here, ŷ represents the predicted sales, a represents the y-intercept, and b represents the slope of the line.
Using the given equation ŷ = 101.32 + 2.48x, you can plug in the values of x (day) to predict the sales on a particular day. For example, on day 60, you would plug in x=60 and solve for ŷ to predict the sales. Similarly, on day 90, you would plug in x=90 to predict the sales.