STAT 101 Module 4 Case – It seems logical that restaurant chains

Case DescriptionIt seems logical that restaurant chains with more units (restaurants) would have greater sales. Thisassumption is mitigated, however, by several possibilities: some units may be more profitable thanothers, some unites may be larger, some unites may serve more meals, some units may serve moreexpesinve meals, and so on. The data shown here were published by Technomic.SalesNumber ofChain($Units (1000)billions)McDonald’s17.112.4Buger King7.97.5Taco Bell4.86.8Pizza Hut4.78.7Wendy’s4.64.6KFC45.1Subway2.911.2DairyQueen2.75.1Hardee’s2.72.9Open up Excel and enter the data into your spreadsheet. The table below illustrates how the first 2 data records should look like, after this step is completed.Create a Scatter plot in Excel with restaurant chains sales on the Y-axis and number of units on the X-axis.To determine the measure of correlation between restaurant chains sales and number of units, Select the Data tab. Click on Data Analysis to open up a pull down menu then choose Correlation.Highlight the input range for the data in the two columns (B1 C10).Check the labels box.Click on the output radio button, and choose cell E1 for the output range. Finish it off by clicking OK.To develop a regression model to predict the restaurant chains sales by the number of units,Select Regression from the Data Analysis pulldown menu.In the Regression dialog box, input the location of the y values in Input Y Range. Input the location of the x values in Input X Range.Select Labels and select Confidence Level, keeping the 95% default.Select K1 as the location for the output.Select Residuals, Standardized Residuals, Residual Plots, and Line Fit Plots. Also select Normal Probability Plots.