A national homebuilder builds single-family homes and condominium-style townhouses. The accompanying dataset provides information on the selling price, lot cost, and type of home for closings during one month. Complete parts a through c. A Click the icon to view the house sales data. - X House sales data a. Develop a multiple regression model for sales price as a function of lot cost and type of home without any interaction term. Create a dummy variable named "Townhouse", where it is equal to 1 when Type = "Townhouse" and 0 otherwise. Determine the coefficients of the regression equation. Туре Townhouse Single Family $138,530 Townhouse Single Family Townhouse Townhouse Sales Price = 108726 +( 3.68 ) • Lot Cost + ( – 75063 ) • Townhouse (Round the constant and coefficient of Townhouse to the nearest integer as needed. Round all other values to two decimal places as needed.) Sales Price $114,740 Lot Cost $21,700 $26,550 $149,905 $172,000 $183,916 $189,390 b. Determine if an interaction exists between lot cost and type of home and find the best model. Use a = 0.1 as the level of significance. First determine whether an interaction exists. Select the correct choice below and, if necessary. fillin te answer box to complete your choice. © A. An interaction exists because the p-value of the variable Lot Cost · Townhouse is . which is less than a. $25,550 $26,200 $46,025 $28,000 $36,000 $46,025 $46,025 $40.299 $37,500 Single Family $191,120 Townhouse Townhouse Single Family Single Family $216,205 Townhouse Single Family $257,000 Single Family Single Family Single Family Single Family Single Family Single Family Single Family Single Family Single Family Single Family Single Family Single Family Single Family Single Family Single Family Single Family Single Family $494,820 (Type an integer or a decimal rounded to three decimal places as needed.) O B. An interaction exists because the p-value of the variable Townhouse i $198,898 $205,076 $207,821 s. which is greater than a. (Type an integer or a decimal rounded to three decimal places as needed.) $252,800 $74,400 $44,198 $44,344 $42,099 $46,000 $45,650 $58,000 $60,000 $46,850 OC. An interaction exists because the p-value of the variable Lot Cost is which is greater than a. (Type an integer or a decimal rounded to three decimal places as needed.) O D. No interaction exists because the p-value is less than a for all of the independent variables $270,000 $270,500 $273,105 $279,720 $296,990 $303,500 $309,487 $314,898 $321,602 $326,412 $339,374 $339,380 $340,065 $356,117 $361,949 $434,426 $41,768 $83,300 $63,523 $71,449 $50,150 $55,850 $57 219 $51,591 $58,422 $85,122 Print Done

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# Educational Content: Analyzing House Sales Data

## Overview

A national homebuilder constructs single-family homes and condominium-style townhouses. This exercise utilizes a dataset providing details on selling price, lot cost, and home type for houses sold in one month. The task involves creating a multiple regression model.

### Step-by-Step Analysis

**a. Developing a Regression Model**

- **Objective**: Build a regression model where sales price is a function of lot cost and home type.
- **Dummy Variable**: Create "Townhouse," set to 1 for townhouses and 0 otherwise.
- **Regression Equation**:
  \[
  \text{Sales Price} = 108726 + (3.68) \cdot \text{Lot Cost} + (-75063) \cdot \text{Townhouse}
  \]
  (Note: The constant and coefficient for Townhouse are rounded to the nearest integer; other values to two decimal places.)

**b. Interaction Between Lot Cost and Home Type**

- **Objective**: Determine if an interaction affects the model. Use \(\alpha = 0.1\) as the significance threshold.
- **Interaction Existence**:
  - **A**: Interaction exists if p-value for "Lot Cost - Townhouse" is \(\_\_\_\), less than \(\alpha\).
  - **B**: Interaction exists if p-value for "Townhouse" is \(\_\_\_\), greater than \(\alpha\).
  - **C**: Interaction exists if p-value for "Lot Cost" is \(\_\_\_\), greater than \(\alpha\).
  - **D**: No interaction if p-values are ≥ \(\alpha\).

### House Sales Data

A dataset containing rows with the following columns:

- **Type**: Identifies if the property is "Single Family" or "Townhouse."
- **Sales Price**: The selling price in dollars.
- **Lot Cost**: The cost of the lot as an integer value.

#### Example Entries

- Type: "Single Family" | Sales Price: $114,740 | Lot Cost: $21,700
- Type: "Townhouse" | Sales Price: $149,905 | Lot Cost: $25,550
- Type: "Single Family" | Sales Price: $192,062 | Lot Cost: $26,000
- Type: "Townhouse"
Transcribed Image Text:# Educational Content: Analyzing House Sales Data ## Overview A national homebuilder constructs single-family homes and condominium-style townhouses. This exercise utilizes a dataset providing details on selling price, lot cost, and home type for houses sold in one month. The task involves creating a multiple regression model. ### Step-by-Step Analysis **a. Developing a Regression Model** - **Objective**: Build a regression model where sales price is a function of lot cost and home type. - **Dummy Variable**: Create "Townhouse," set to 1 for townhouses and 0 otherwise. - **Regression Equation**: \[ \text{Sales Price} = 108726 + (3.68) \cdot \text{Lot Cost} + (-75063) \cdot \text{Townhouse} \] (Note: The constant and coefficient for Townhouse are rounded to the nearest integer; other values to two decimal places.) **b. Interaction Between Lot Cost and Home Type** - **Objective**: Determine if an interaction affects the model. Use \(\alpha = 0.1\) as the significance threshold. - **Interaction Existence**: - **A**: Interaction exists if p-value for "Lot Cost - Townhouse" is \(\_\_\_\), less than \(\alpha\). - **B**: Interaction exists if p-value for "Townhouse" is \(\_\_\_\), greater than \(\alpha\). - **C**: Interaction exists if p-value for "Lot Cost" is \(\_\_\_\), greater than \(\alpha\). - **D**: No interaction if p-values are ≥ \(\alpha\). ### House Sales Data A dataset containing rows with the following columns: - **Type**: Identifies if the property is "Single Family" or "Townhouse." - **Sales Price**: The selling price in dollars. - **Lot Cost**: The cost of the lot as an integer value. #### Example Entries - Type: "Single Family" | Sales Price: $114,740 | Lot Cost: $21,700 - Type: "Townhouse" | Sales Price: $149,905 | Lot Cost: $25,550 - Type: "Single Family" | Sales Price: $192,062 | Lot Cost: $26,000 - Type: "Townhouse"
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