A housing developer in a certain subdivision wants to determine if the number of family members andthe number of bedrooms are linearly related. A sample of 10 families in a certain subdivision revealedthe following observations.Number of Family Members (X) 31 3 74 52563Number of Bedrooms (Y)1 2 3 4 2 1 5 4 6 2Determine the strength of the relationship of variable x and y by finding the value of correlationcoefficient and coefficient of determination. Then, Interpret the results.

Given that : X Y X \cdot YX⋅Y X^2X2 Y^2Y2 3 1 3 9 1 2 2 4 4 4 5 3 15 25 9 6 4…

Answered: A housing developer in a certain…

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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Police sometimes measure shoe prints at crime scenes so that they can learn something about criminals. Listed below are shoe print lengths, foot lengths, and heights of males. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value of r. Determine whether there is sufficient evidence to support a claim of linear correlation between the two variables. Based on these results, does it appear that police can use a shoe print length to estimate the height of a male? Use a significance level of α=0.01. Shoe Print (cm) 29.0 29.0 31.2 31.7 27.1 Foot Length (cm) 26.3 24.9 28.0 26.0 25.7 Height (cm) 177.5 173.1 181.1 181.6 176.9
6. Police sometimes measure shoe prints at crime scenes so that they can learn something about criminals. Listed below are shoe print lengths, foot lengths, and heights of males. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value of r. Determine whether there is sufficient evidence to support a claim of linear correlation between the two variables. Based on these results, does it appear that police can use a shoe print length to estimate the height of a male? Use a significance level of = 0.05. 29.6 29.6 32.1 32.4 28.1 Shoe Print (cm) Foot Length (cm) Height (cm) 24.7 24.6 26.8 25.6 25.0 175.8 173.2 182.6 177.3 171.3 The test statistic is t = (Round to two decimal places as needed.) The P-value is (Round to three decimal places as needed.) Because the P-value of the linear correlation coefficient is (3)- the significance level, there (4) heights of males. sufficient evidence to support the claim that there is a linear correlation…
Police sometimes measure shoe prints at crime scenes so that they can learn something about criminals. Listed below are shoe print lengths, foot lengths, and heights of males. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value of r. Determine whether there is sufficient evidence to support a claim of linear correlation between the two variables. Based on these results, does it appear that police can use a shoe print length to estimate the height of a male? Use a significance level of a=0.05. Shoe Print (cm) 28.8 28.8. 32.1 32.6 Foot Length (cm) Height (cm) 25.2 181.7 24.9 173.5 27.5 27.6 27.5 25.9 186 169.1 171 Construct a scatterplot. Choose the correct graph below. OA. 200- 2 160+ Shoe Print (cm) 35 The linear correlation coefficient is r= (Round to three decimal places as needed.) B. 200- 160- 25 Shoe Print (cm) ○ C. 200- G 35 160+ 25 Shoe Print (cm) 35 OD. Q 200- Height (cm) G 160- 25 35 Shoe Print (cm)
The store manager of a business that sells jackets is curious if the weather temperature (in degrees Celsius) per day is related to the daily sales (in pesos) earned by the store. He took some random samples and recorded the temperatures and sales for the selected days, which can be found in the next slide. Calculate the correlation coefficient and interpret the result.
A survey was taken in 2018 that asked people about their saving habits. Researchers wanted to know if people who saved more also spent less. The scatterplot below shows their results when comparing two variables: the amount people reported that they put into savings each month, and the amount they reported that they spent on clothes. The researchers found the correlation coefficient for this data to be -0.239. Which of the following is true about these variables? a. There is no relationship between savings and money spent on clothes each month.b. There is a weak, positive linear relationship between savings and money spent on clothes each month.c. There is a perfect, negative linear relationship between savings and money spent on clothes each month.d. There is a weak, negative linear relationship between savings and money spent on clothes each month.
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
The following table shows the weekly sales, test scores & achievement ratings of 5 salespersons working for a local car dealership: Salesperson Weekly Sales (Y) Sales Aptitude Test Score (x1) Mechanical Achievement (x2) Walters 11 10 6 Sullivan 5 4 2 Obmer 8 1 4 Smith 12 7 5 Jones 4 3 1 Brown 6 5 3 Black 7 2 2 Calculate the multiple correlation coefficient.. Select one: a. 0.925 b. 0.952 c. 0.295 d. 0.592
A random sample of 7 countries gave the following figures for X = annual per capita income and Y = urbanization rate (percentage of people living in urban area): Country X (US dollars) Y (%) 1 3500 20 2 2700 24 3 2100 16 4 2400 19 5 3000 26 6 2000 19 7 1900 17 Calculate the correlation coefficient for the sample. Explain the results At the 5% significant level, test whether per capita income and urbanization rate are unrelated.
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
For a data set of weights (pounds) and highway fuel consumption amounts (mpg) of twelve types of automobile, the linear correlation coefficient is found and the P-value is 0.022. Write a statement that interprets the P-value and includes a conclusion about linear correlation. The P-value indicates that the probability of a linear correlation coefficient that is at least as extreme is %, which is so there sufficient evidence to conclude that there is a linear correlation between weight and highway fuel consumption in automobiles. (Type an integer or a decimal. Do not round.)
A study of bone density on 5 random women at a hospital produced the following results. Age 41 45 49 69 73Bone Density 360 350 345 335 330 Step 3 of 3: Calculate the coefficient of determination, r2. Round your answer to three decimal places.
The table below includes data from taxi rides. The distances are in miles, the times are in minutes, the fares are in dollars, and the tips are in dollars. Is there sufficient evidence to conclude that there is a linear correlation between the time of the ride and the tip amount? Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value of r. Determine whether there is sufficient evidence to support a claim of linear correlation between the two variables. Use a significance level of a = 0.01. Does it appear that riders base their tips on the time of the ride? Click here for information on the taxi rides. Construct a scatterplot. Choose the correct graph below. O A. Tip Amount ($) 25- Q 0 35 G Ride time (minutes) Determine the linear correlation coefficient. The linear correlation coefficient is r= (Round to three decimal places as needed.) Tip Amount ($) B. 25- 0- 0 35 G Ride time (minutes) Taxi data ip Amount (S C. 25- 0- 35 Ride time…

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