Predictive Modeling Exercise
Predictive modeling is the use of predictors that have been determined to influence future outcomes in order to create a statistical model. There is no one form of predictive modeling. It can be simple – using a linear equation – or more complex using sophisticated software.
Predictive analytics involves using information from historical data to identify patterns in order to determine possibilities for the future. Regression and trend analyses are both examples of predictive analytics.
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Predictive Modeling Exercise
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- Watch What is predictive analytics data mining
- Watch Predictive Data Analytics in UNDER 5 Minutes.
- Watch AI for Marketing and Growth #1 – Predictive Analytics in Marketing.
- Watch Learn 5 of the Hottest Analytics Techniques in Just 12 Minutes.
- Watch Use the TREND Function to Predict Sales Growth.
- Read & View ExcelFunctions.net.
- Assume that for a given company, net profit will increase when sales increase. In this scenario, the linear relationship exists between sales (the independent variable) and net profit (the dependent variable).
- Develop a trend and linear regression analysis for a public company of your choice.
- Research and collect 10 years of Sales and Net Profit Data.
- Forecast the sales for the next 2 years using the Sales Data and the Years.
i. The TREND function link above (not the Forecast function) - Then, use the Trend function for the next 2 years, using the Profit Data and the Sales Data, with the Forecasted Sales from (b) above. You can predict the Profit (be sure to hit Control, Shift, Enter) to calculate.
- This link uses the TREND function to predict outcome of two strings of numbers which the user believes has a correlation. Using this same method, you can use the old Profit and the Sales Data, along with your newly forecasted Sales data to predict what the Net Profit will be in the next two years.
- With the new table of numbers for Profit, Sales and Years, you can produce a linear graph.
- Sample of how to create Linear graph after data for graph is completed.
