Calculate the correlation between the two variables. Describe the linear relationship between these two variables. Classmate's survey data:How many of your neighbors' cars are red?0,0,0,0,0,0,1,1,1,1,1,1,2,2,2,2,2,3,5,7,70My survey data:How much money is spent on gas per month?0,0,40,65,75,85,100,100,100,100,100,100,120,140,144,150,150,180,200,200,200 X0000001111112222235770y0040657585100100100100100100120140144150150180200200200

Answered: Calculate the correlation between 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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What does linear mean
Input 'X' Family Median Percentiles OutPut 'Y' Percent Of Children Attending College 100 94 1 25 Find The Linear equation using the above data.
Hi, I am stuck on this question, could you please help
The correlation for the data is r=1 and a=0.05 should regression analysis be done Find the equation of the regression line y = a+bx A= B= Find y when x=40
The regression equation of two variables are 3Y-2X 10 = 0 and 2Y-X-500. Find coefficient of correlation.
Pls help ASAP
Sometimes we have data that can be paired together, such as height and weight of an individual. When two variables are measured and paired together, we have what we call paired data. When we have paired data, we can plot the results using a scatterplot. This will give us a visual to determine if there is a relationship between the variables of interest. For two variable relationships, we can often report the data as ordered pairs in (x, y) format. Our x-variable in this case is known as the explanatory variable, and the y-variable is known as the response variable. We use values of x to predict y. If there appears to be a linear relationship between the two variables, we can create a least squares regression line. This is a line that “best” fits the dataset we have. The result will be a linear equation and we can use this equation to predict future values. For simple linear regression (ordered pairs with only two variables), the general form of a regression line follows:�̂=β0+β1�,…
Complete parts (a) through (h) for the data below. x 20 30 40 50 60 D 50 y 80 75 71 64 (a) By hand, draw a scatter diagram treating x as the explanatory variable and y as the response variable. Choose the correct scatter diagram below. O A. _^) 70 10+ 10 (b) Find the equation of the line containing the points (30,75) and (60,50). y=x+ (Type integers or simplified fractions.) (c) Graph the line found in part (b) on the scatter diagram. Choose the correct graph below. OA. A 70 10+ N A) N. 70+ 10+ 0 (d) By hand, determine the least-squares regression line. II X+ (Round to three decimal places as needed.) (e) Graph the least-squares regression line on the scatter diagram. Choose the correct graph below. OA. IN 100 1. Q Q X Q Q G 100 Q (f) Compute the sum of the squared residuals for the line found in part (b). (Round to three decimal places as needed.) (g) Compute the sum of the squared residuals for the least-squares regression line found in part (d). (Round to three decimal places as…
The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 40 inches. Is the result close to the actual weight of 352 pounds? Use a significance level of 0.05. Chest size (inches) *Weight (pounds) 44 54 328 528 41 55 39 51 418 580 296 503 Click the icon to view the critical values of the Pearson correlation coefficient r. - What is the regression equation? x (Round to one decimal place as needed.)
A regression analysis was performed to determine if there is a relationship between hours ofTV watched per day r) and number of sit ups a person can do (y). The results of the regression were: у-ах+b a=-0.827 b=35.329 r2=0.540225 r=-0.735 Use this to predict the number of sit ups a person who watches 13.5 hours of TV can do, and please round your answer to a whole number.
A chemistry experiment is performed measuring the solubility of potassium chloride (KCl) in water at different temperatures. The goal was to determine if there is a linear relationship between the temperature of the water and how much KCl can dissolve, measured as grams per 100 milliliter (g/100mL). After the experiments were performed, the following data was collected with temperature being the independent x-variable and solubility being the dependent y-variable: Temperature (°C) x Solubility (g/100mL) y 10 31 20 33 30 37 40 41 50 42 Based on the data given for temperature and solubility of KCl and without doing any math yet, which of the following do you predict would best describe the relationship between these variables? A positive linear relationship (r close to 1) A positive linear relationship (r close to -1) A negative linear relationship (r close to 1) A negative linear relationship (r close to -1)…
A hydrologist is interested in studying the influence of rainfall on runoff in a drainage basin. Rainfall and runoff are measured during 20 rainfall events. Model the relationship. What are the variables and the type of measurement for these variables? slope (numerical) and itercept (numerical) dependent variable (nominal) and independent vatiable (nominal) Rainfall (total mm) and Runoff (liters/36 hours) geographic location (lat/long), area of watershed (hectares), and substrate type (rock/soil/vegitation) rainfall (numerical) and runoff (numerical)

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