A realty group would like to develop a regression model to help it set weekly rental rates (y) for beach properties during the summer season. The independent variables for this model are the number of bedrooms a property has (x,), its age in years (x2), and the number of blocks away from the ocean the property is (x3). Use the data provided to complete parts a through e below. E Click the icon to view the data for randomly selected rental properties. a) Construct a regression model using all three independent variables. ŷ = (D + (O×, + (O*2 + (Dx3 (Round the constant term to the nearest integer. Round the coefficients of x,, X2, and x3 to one decimal place as needed.)

A realty group would like to develop a regression model to help it set weekly rental rates (y) for beach properties during the summer season. The independent variables for this model are the number of bedrooms a property has (x,), its age in years (x2), and the number of blocks away from the ocean the property is (x3). Use the data provided to complete parts a through e below. E Click the icon to view the data for randomly selected rental properties. a) Construct a regression model using all three independent variables. ŷ = (D + (O×, + (O*2 + (Dx3 (Round the constant term to the nearest integer. Round the coefficients of x,, X2, and x3 to one decimal place as needed.)

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Concept explainers

Correlation

Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.

Linear Correlation

A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.

Regression Analysis

Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.

Question

Data for rental properties
Rental ($) | Bedrooms
Age
Blocks O
875
2
12
1175
3
12
3
1500
7
1.5
1900
4
20
2
2300
12
2.5
3200
10
1.5
5000
5
1.5
2250
5
3
1.5
2700
3
4
2.5
3000
4
2.5
4000
4
11
1
5000
3
6500
5
11
1
8000
13
1
1300
2
15
3
2000
4
9.
2.5
2800
4
6.
2
3400
4
6.
1
4000
4
10
1.5
4500
12
2
5400
14
8000
13
1.5
12,000
4
0.5

A realty group would like to develop a regression model to help it set weekly rental rates (y) for beach properties during the summer season. The independent variables for this model are the number of bedrooms a property has (x1), its age in
years (x2), and the number of blocks away from the ocean the property is (x3). Use the data provided to complete parts a through e below.
Click the icon to view the data for randomly selected rental properties.
a) Construct a regression model using all three independent variables.
OX1 + (OX2 + (O X3
y =
(Round the constant term to the nearest integer. Round the coefficients of x1, X2, and x3 to one decimal place as needed.)

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