You are a business analyst at a private-equity investment organization. You are exploring potential new investment opportunities for your organization. One of the sectors your organization is looking to invest in is sustainable green-energy businesses. The chief investment officer (CIO) has handed you a historical data set on sustainable organizations. The CIO informs you that five new organizations in the sector are looking for investors. You must analyze the historical data to assess whether investing in one of these organizations would be a good decision.
A linear regression model provides ratio values as output. Using the Historical Green Energy Data Set, you will build and apply a linear regression model to predict the profit value for the five new organizations. If an organization’s predicted profit value is a negative ratio value, you may not recommend the organization as an investment opportunity. Similarly, if an organization’s predicted profit is a positive ratio value, you may recommend it as an investment opportunity.
Write a report with your analysis and recommendations about the investment potential of the five new organizations. Specifically, you must address the following rubric criteria:
Data Requirements: Using the given historical data set, identify the information you will need to create the predictive model.
Determine the dependent and independent variables.
Explain the relationship between the dependent and independent variables.
Linear Regression Model: Use the given historical data to build a linear regression equation.
Create a linear regression equation for multiple independent variables.
Strength of the Model: Use the results of the linear regression to assess the strength of the model.
Discuss the summary output, including multiple R, R square, adjusted R square, and sample error.
What do these results tell you about the variables and the data?
How will these results help you predict the investment potential of an organization?
Strength of the Independent Variables: Evaluate the strength of the independent variables to find out which variables have the most impact.
Discuss the degrees of freedom (df), sum of squares (ss), and mean square (MS).
What do these tell you about the historical data and the role of the different independent variables?
Discuss how the model’s coefficients can be used to select the optimal independent variables for the model.
Actual versus Predicted Model: Compare the predicted variable values with the actual variable values.
Explain whether this model is potentially useful for predicting an organization’s profitability.
Show the residual output from the model, and discuss how far the predicted variables are from the actual results.
Recommendation: Provide a recommendation based on the results of the predictive model.
Apply the model to the data from the five new organizations to determine if any of the organizations are profitable for investors.
Provide a recommendation for each of the five organizations.
