DATA analytics Visual Presentation on Firm performance for the Food industry.
Due is 20 May 21 at 10:00 AM (100 pts)
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This is continuation of your previous the Food industry. You can use your data that are used in your project. Do not worry if you drop all observations that do not have XRD.
Here you need your previous regression result of COGS and SALE, a ratio of COGS to SALE, and the trend graph from the project. When you answer to questions 1-8 and 1-9 clearly note these numbers on your Excel sheet.
Make data to a table format and conduct analyses.
1-1 Create two graphs. One is the time trend graph for sales and IB (X is year). and the other is a scatter graph of Operating income (IB as Y variable) versus Sale (X Variable) for each firm. You should observe any outliers, and examine if a liner line will fit well or not.
1-2 Conduct a simple regression analysis (use the same DATA used in the proejct) and examine whether the estimated slope coefficient and R square are reasonable given the Scatter graphs.
1-3 Using VLOOUP and pick up the value of ROS from the Pivot table and include the value underneath of the estimated coefficient on Sales.
1-4 Compare the estimated slope coefficient and the value of ROS. What kind of conclusion can be drawn from this comparison? Comment on.
1-5 Create two tables. One table for COGS and SALE that includes the estimated slope coefficient, P-value, the average ratio of COGS to SALE. The other Table for IB and SALE that includes the estimated slope coefficient, P-value, the average ROS. Include the number of observations for the COGS and SALE table. For the ratios you use VLOOKUP to pick the value from the pivot table. For P-value you can use VLOOKUP to pick up value from your regression analysis.
1-6 Create one more column in both tables. The title of this column is ESTVC for the COGS and SALE table and ESTVI for the IB and COGS table. Use “if statement” and include the value in the column. The if statement states that if the P-value is smaller than 0.025 then include the value of the regression coefficient otherwise include the value of the ratio.
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