A team from UNHABITAT took a random sample of 230 households in a city tobetter understand how the size of a house (measured in metres) is related to thenumber of people living in that house. They performed a regression analysis on thedata and found that regression model had an R² = 18.3%. What is the correlationbetween the size of a house and the number of people living in that house?0.6670.1830.0330.9040.428

given data n = 230R2 = 18.3% = 0.183correlation between variables = ?

Answered: A team from UNHABITAT took a random…

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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Please also explain why you determined whether or not the results are statistically significant. A student finds a correlation of r = .04 between the number of units the students in his research methods class are taking and the students’ level of stress.
A sociologist is studying the relationship between income and farm production in California’s Central Valley. She has data for each county, showing the average income and total farm production (in dollars) for that county. The correlation is 0.43. Does this give a fair estimate of the strength of the association between income and farm production? Explain why.
The systolic blood pressure of individuals is thought to be related to both age and weight. Let the systolic blood pressure, age, and weight be represented by the variables x1, x2, and x3, respectively. Suppose that Minitab was used to generate the following descriptive statistics, correlations, and regression analysis for a random sample of 15 individuals. Relative to its mean, which variable has the greatest spread of data values?
Researchers found a correlation coefficient of r = .50 on personality measures for identical twins. A reporter interpreted this to mean that "the environment orchestrated one-half of their personality differences." Do you agree with the interpretation? Explain.
A professor obtains SAT scores and freshman grade point averages (GPAs) for a group of n = 15 college students. The SAT scores have a mean of M = 580 with SS = 22,400, and the GPAs have a mean of 3.10 with SS = 1.26, and SP = 84. Find the regression equation for predicting GPA from SAT scores. What percentage of the variance in GPAs is accounted for by the regression equation? (Compute the correlation r, then find r^2.) Does the regression equation account for a significant portion of the variance in GPA? Use α = .05 to evaluate the F-ratio.
Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Find the regression equation, letting the right arm blood pressure be the predictor (x) variable. Find the best predicted systolic blood pressure in the left arm given that the systolic blood pressure in the right arm is 9090 mm Hg. Use a significance level of 0.05 Right Arm 100 99 91 79 79 Left Arm 176 171 141 145 143 LOADING... Click the icon to view the critical values of the Pearson correlation coefficient r The regression equation is ModifyingAbove y with caretyequals=31.931.9plus+1.41.4x. (Round to one decimal place as needed.) Given that the systolic blood pressure in the right arm is 90mm Hg, the best predicted systolic blood pressure in the left arm is ???? mm Hg. (Round to one decimal place as needed.)
Find the correlation coefficient between the “modules studied in the last semester and number of hours spend on reading the books” from your collected data.
A football coach is looking for a way to identify players that are "under weight". The coach decides to get data for each player's height (x, in inches) and weight (y, in pounds), then does a linear regression. The results are: 58+3.7x, r = 0.86 and the standard error is Se = 10.4. Since there is a strong linear correlation the coach, who also majored in Statistics, decides to identify all "outliers" in the data. Obviously, any player whose weight is above the regression line is not "under weight". So the only outliers the coach is interested in are those that are below the regression line. What is the lowest weight possible for a 75 inch player to not be considered "under weight"? Do not round. Submit Question ctor GSearch or type URL & % 24 6 7
Two regression lines of a sample are X+6 Y=6 and 3X+2Y=0. Find the correlation coefficient.
Use the summary statistics to calculate the regression line for this data. Explain each coefficient. What is the total amount of weight would you expect a weightlifter with a body weight of 84kg to lift? At the 5% significance level, is there evidence that the body weight of the athlete is a useful predictor for the total amount an athlete can lift? Assume the assumptions can be verified.
The mean height of Americanwomen in their twenties is about 64.3 inches, and the standard deviation is about 3.9 inches. The mean height of menthe same age is about 69.9 inches, with standard deviationabout 3.1 inches. Suppose that the correlation between theheights of husbands and wives is about r 0.5.(a) What are the slope and intercept of the regressionline of the husband’s height on the wife’s height in youngcouples?(b) Draw a graph of this regression line for heights of wivesbetween 56 and 72 inches. Predict the height of the husbandof a woman who is 67 inches tall, and plot the wife’s heightand predicted husband’s height on your graph.(c) You don’t expect this prediction for a single couple to bevery accurate. Why not?
A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y).The results of the regression were:y=ax+b a=-1.38 b=39.555 r2=0.693889 r=-0.833 Assume the correlation is significant, and use this to predict the number of situps a person who watches 7 hours of TV can do (to one decimal place)

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