The following dataset is an IBM Watson Customer Lifetime Value dataset obtained from Kaggle. It contains a sample of an internal database from an insurance company. The dataset contains detailed customer profile data, service (policy) customers purchased, vehicle information, claim information, and whether customers responded to a recent promotion. The additional information/attachment/tables/figures that is related to the question -are to be retrieved from: https://www.kaggle.com/pankajjsh06/ibm-watson-marketing-customer-value-data (please retrieve data from this link as the file cannot be uploaded here - it will take you directly to the download).

Use the data set for this assignment. Note - For sav files - Launch SPSS.

For this data analysis activity, the insurance company is analyzing the total claim amount to understand how customer profiles affect their claim behavior. The company wants to study whether income, number of policies, types of policies, coverage of policy, gender and marital status would affect the customer's total claim amount.

For each nominal/ordinal scaled variable, you should independently decideone group as baseline group and create the dummy variables for the other groups defined by this nominal/ordinal scaled variable.

Next, use SPSS to conduct necessary analysis.

• Summarize the analysis results.
• Based on your analysis results, how would you make recommendations to the management?
• Are there any other factors you would like to add to your analysis? Why?
• Paste the screenshots of the SPSS outputs for linear regression.

Variable Creation Label Coverage_1 Coverage=Bas ic Coverage_2 Coverage=Exte nded Coverage_3 Coverage=Pre mium Regression Variables Entered/Removed" Variables Variables Model Entered Removed Method Extended Enter Marital Status, Income, Basic" a. Dependent Variable: Total Claim Amount b. All requested variables entered. Model Summary Adjusted R Std. Error of the Model R R Square Square Estimate 470 221 220 256.50274295 a. Predictors: (Constant), Extended, Marital Status, Income, Basic ANOVA" Sum of Model Squares df Mean Square F Sig. Regression 170106344.32 4 42526586.081 646.363 000 Residual 600630296.06 9129 65793.657 Total 770736640.38 9133 a. Dependent Variable: Total Claim Amount b. Predictors: (Constant), Extended, Marital Status, Income, Basic Coefficients" Standardized Unstandardized Coefficients Coefficients Model B Std. Error Beta + Sig (Constant) 880.141 12.010 73.283 000 Income -.003 000 -.324 -34.096 <.001 marital status basic>