You are trying to produce an app to replace realtors and reap their commissions (typically 5 to 6% of theproperty selling price). Your first mission is to produce a tool that helps prospective house buyers estimatethe potential selling price of their houses, and you're working on making a regression model to serve as theengine behind the tool. You'd like to make the model as simple as possible, so you are wondering how wellyou can predict the selling price of a house from just the size of the living area (ignoring garage, etc).In RStudio, run the following code to install and/or library the package "openintro".1. install.packages("openintro") # don't do this again if you already did this!2. library(openintro)3. amesDelete the install line of code if you are in an RMD file so that it doesn't install every time you knit. Thelast line of code will access the dataset of that name.The table ames' gives information about house prices in the fun college town of Ames, lowa. Use the dataset to make a model to predict the price of a house in Ames, lowa in dollars (price") from the area of livingspace of a house in square feet ("area").a. Make a scatterplot of "price" (y-axis) vs "area" (xx-axis). Which plot is the scatterplot?Graph A Graph B Graph C Graph DGraphGraphOA$4845-с5000-3000-✔BOH: B111.694HA: 111.6944000-Db. Does the relationship appear roughly linear?2900-1300No, all the points do not fall on a straight line.No, there are gaps in the graph along the x-axis.Yes, there is no obvious curvature in the graphYes, all the points fall on a straight line.c. Do the data provide strong evidence that the price of a house in Ames, lowa in dollars and the areaof living space of a house in square feet are associated! State the null and alternative hypotheses,report the p-value, and state your conclusion.1. The hypotheses are:ⒸH₂:₁0H₁:024+05d. Interpret R.Ho: 111.694H₁:111.694Ho: ₁0HA: 0II. The result of this hypothesis test is:11. The p-value for the test is (round to three decimal places if that value is 0 then enter 0.):About 49.95% of the variation in the area of living space of a house in square feet isexplained by the least squares line.Ha:B₁0HA:B₁0ⒸH₁:0HA: >0the area of living space of a house in square feet is not predictive of the price of a housein Ames, lowa in dollars.the area of living space of a house in square feet is predictive of the price of a house inAmes, lowa in dollars.About 49.95% of the variation in the price of a house in Ames, lowa in dollars isexplained by the least squares line.The total unexplained variation in the model.The total amount of variation in the model.O the amount of variation in the price of a house in Ames, lowa in dollars that is explained bythe least squares line.e. What is the equation of the regression line?Oarea - 111.694 price + 13289.634area - 13289.634 price + 111.694Oprice 13289.634 area + 111.694Oprice 111.694 area+ 13289.634The amount of variation in the area of living space of a house in square feet that is explainedby the least squares line.f. Interpret the slope in the context of the model. For each [Select an answer increase inSelect an answerSelect an answer✔Select an answerSelect an answerg. Interpret the y-intercept in the context of the model or explain why it should not be interpretedOwhen the the area of living space of a house in square feet of a house is 0 the expected valueof the price of a house in Ames, lowa in dollars is 13289.634.Owhen the the price of a house in Ames, lowa in dollars of a house is 0 the expected value ofthe area of living space of a house in square feet is 111.694.On It does not make sense to interpret the y-intercept for this model because no house in thedata had a the area of living space of a house in square feet anywhere close to 0.When the the price of a house in Ames, lowa in dollars of a house is 0 the expected value ofthe area of living space of a house in square feet is 13289.634.

> install.packages("openintro") Installing package into…

Answered: tryin produce app replace realtor…

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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Flying twice as farA flight from Los Angeles to ABQ is about 2 hours but is 670.2 miles.A flight from San Jose to Chicago is 4 hours but is 1859.0 miles.Can anyone explain why the travel time from San Jose to Chicago is notlonger and closer to 5.75 hours?If the distance increase by 2, shouldnt the time increase by a factorof 2 as well?1. Write a linear model for this question. Takeoff and landing will take a fixed amount of time. Actualtravel in the air will take time proportional to the distance traveled. Think about which of thevariables (time and distance) is the independent variable, and identify the slope and intercept withtheir units.2. Use the data in the quotation to estimate the two constants in your linear model.
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