Do the odds of churning increase or decrease when the customer has a two-year contract as compared to month-to-month (reference level)? What about a one-year contract? Show the calculation of the odds for both.

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Do the odds of churning increase or decrease when the customer has a two-year contract as compared to month-to-month (reference level)? What about a one-year contract? Show the calculation of the odds for both.

### Logistic Regression Learner Node: Coefficients and Statistics Table

The table presented is an output from a Logistic Regression model, detailing the coefficients associated with various predictor variables. Here's a breakdown of the table:

#### Table Columns:

1. **Row ID**: Identifies the specific row number for reference.
2. **S**: Indicates whether the variable is selected for the model (Yes/No).
3. **Logit**: Probability measure or log-odds associated with the variable.
4. **Variable**: The name of the variable or feature used in the Logistic Regression model.
5. **D**: Significance denoted by a characteristic. This column is not filled in the image.
6. **Coeff.**: The coefficient value that represents the impact of the predictor on the dependent variable in the model.

#### Key Variables and Coefficients:

- **Gender**:
  - Male: Coefficient = 0.004
- **Demographics**:
  - Senior Citizen: Coefficient = 0.31
- **Services**:
  - Phone service: Coefficient = 0.083
  - Multiple lines (Yes): Coefficient = 0.267; (No): Coefficient = -0.285
  - Internet service (Fiber optic): Coefficient = 0.685; (No): Coefficient = -0.214
- **Features**:
  - OnlineSecurity: Coefficient = -0.234
  - OnlineBackup: Coefficient = 0.099
  - DeviceProtection: Coefficient = 0.042
  - TechSupport: Coefficient = -0.416
- **Streaming Features**:
  - StreamingTV (Yes): Coefficient = 0.504
  - StreamingMovies (Yes): Coefficient = 0.556
- **Contracts and Payments**:
  - Contract (One year): Coefficient = -0.649; (Two year): Coefficient = -1.259
  - PaperlessBilling: Coefficient = 0.393
  - Payment Method (Mailed check): Coefficient = 0.331; (Bank transfer automatic): Coefficient = -0.501
- **Charges**:
  - Monthly Charges: Coefficient = 0.033
  - Total Charges: Coefficient = 0.000
- **Constant**: Coefficient = -3.383

###
Transcribed Image Text:### Logistic Regression Learner Node: Coefficients and Statistics Table The table presented is an output from a Logistic Regression model, detailing the coefficients associated with various predictor variables. Here's a breakdown of the table: #### Table Columns: 1. **Row ID**: Identifies the specific row number for reference. 2. **S**: Indicates whether the variable is selected for the model (Yes/No). 3. **Logit**: Probability measure or log-odds associated with the variable. 4. **Variable**: The name of the variable or feature used in the Logistic Regression model. 5. **D**: Significance denoted by a characteristic. This column is not filled in the image. 6. **Coeff.**: The coefficient value that represents the impact of the predictor on the dependent variable in the model. #### Key Variables and Coefficients: - **Gender**: - Male: Coefficient = 0.004 - **Demographics**: - Senior Citizen: Coefficient = 0.31 - **Services**: - Phone service: Coefficient = 0.083 - Multiple lines (Yes): Coefficient = 0.267; (No): Coefficient = -0.285 - Internet service (Fiber optic): Coefficient = 0.685; (No): Coefficient = -0.214 - **Features**: - OnlineSecurity: Coefficient = -0.234 - OnlineBackup: Coefficient = 0.099 - DeviceProtection: Coefficient = 0.042 - TechSupport: Coefficient = -0.416 - **Streaming Features**: - StreamingTV (Yes): Coefficient = 0.504 - StreamingMovies (Yes): Coefficient = 0.556 - **Contracts and Payments**: - Contract (One year): Coefficient = -0.649; (Two year): Coefficient = -1.259 - PaperlessBilling: Coefficient = 0.393 - Payment Method (Mailed check): Coefficient = 0.331; (Bank transfer automatic): Coefficient = -0.501 - **Charges**: - Monthly Charges: Coefficient = 0.033 - Total Charges: Coefficient = 0.000 - **Constant**: Coefficient = -3.383 ###
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