2.Jack is wondering whether or not the rent( in hundreds) of an apartment negativelydepends on the vacancy rate (in percentage points) of the city where the apartment located. Jackcollects the data of 30 cities in the U.S. The summary statistics are listed as the following:a.f.VariableRentVacancy ratee.Obs3030RentVacancyrateAnd the correlation coefficient matrix is:RentMean17.2011.331.0000VacancyRateStd. Dev.3.355.96-0.54 1.0000Please find the estimated simple linear regression.b.Please find the sum of square of errors(SSE).c. Do you find evidences that an increase in the vacancy rate of a city reduces the rent of thecity?MinMax10.83 24.9220d. Interpret your estimated slope coefficient.Is the rent of a city is correlated to its vacancy rate?Estimate with 95% confidence the rent of apartments for a city with the vacancy rate of 11and 15. Which confidence interval is wider?

In this question, we need to perform a simple linear regression analysis. This involves estimating…

Answered: 2. Jack is wondering whether or not the…

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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Jim and Larry run a soup stand. The data below represents the sales of soup that they had on 8 randomly selected days, along with the high temperature on that day. a) Create a scatter diagram for this data set and comment on whether there is a positive or negative relationship between these variables.b) Calculate the correlation coefficient between temperature and sales.c) Does a linear relationship exist between these variables? Explain to me why or why not this is the case.d) Using excel, calculate the least squares regression equation for this data set. e) Using your equation, predict the soup sales on a day where the temperature is 29 degrees.f) Interpret the slope of this equation.g) Can we use this data set and regression equation to predict the sales on a day when the average temperature is 102 degrees? Why or why not?h) What is the R-squared for this equation? How do you interpret that R-squared?
Susan, a personal trainer, was interested in whether or not there was a linear relationship between the number of visits her clients made to the gym each week and the average amount of time her clients exercised per visit. She took the following data. Client 1 2 3 4 5 6 Number of visits per week 1 3 4 2 3 5 Average time spent exercising per visit (hours) 2 1.5 1 2 2 0.30 Is the correlation coefficient significant? Group of answer choices No Yes Perhaps Insufficient Information to make a decision
If the linear association between two numerical variables is studied and the correlation coefficient is 0.32, it can be concluded that:a. The relationship between the variables is inverse and weak. b. The percentage of variability observed in the data that is explained by the error is 89.76%. c. The percentage of observed variability in the data that is explained by the model is 32%. d. None is correct Please explain clearly, thank you
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A local store kept track of the number of advertisements it placed in local newspapers and the number of stereo systems it sold each week. Week 1 2 3 4 5 6 7 8 Advertisements, x 7 5 4 2 8 5 5 3 Stereos Sold, y 23 15 12 8 2 7 9 6 a) Create a scatter plot for the data showing Advertisements Vs. Stereos Sold. b) Determine the value of r, the correlation coefficient for the set of data and classify the type of correlation. c) What does this correlation coefficient suggest about the effectiveness of the advertisements? Explain
2. A study was conducted to determine the relationship between a person’s monthly income in Omani Rials and the number of meals that person eats away from home per month. The data are shown below.
After gathering data about the number of starfish and measuring the pollution in areas of the ocean you find a negative linear correlation between pollution levels and number of starfish. What can you conclude based on this information? a. There is a confounding variable that is affecting both pollution and starfish. b. As pollution rises the number of starfish falls c. That pollution is causing starfish to die, leading to the negative correlation d. That pollution is supporting starfish, leading to the negative correlation
There appears to be a problem with one of your contact methods. Please check your SettingS Enter the following table into your calculator or the Desmos Grapher and create the scatterplot. X 2 60 33 2,100 36 2,860 49 14,440 65 10,560 79 567,860 79 570,560 97 2,238,200 95 3,674,760 98 5282120 1. Is there a correlation for the data? If so, is it strong or weak? 2. What shape of function does the scatterplot show? 3. Use your calculator or the Desmos Grapher to find the equation for the line/curve of best fit. Now, use the equation editor to give the equation for the line/curve of best fit. 4. Determine if this equation is a good predictor of the data, using the appropriate number as proof/reasoning.
The following table shows the approximate number of wireless telephone subscriptions in recent years.

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