The following calculator screenshots show the scatterplot and the correlation coefficient between the number of days absent and the final grade for a sampleof college students in a general education statistics course at a large community college.LinRegTTesty=a+bx8#0 and P#0tb=-2.827272727s=3.067320418r2=.8975572812r=-.9473949974The relationship between "days absent" and "final grade" can be described asO A strong negative linear relationshipDeO A weak negative relationshipA strong positive linear relationshipO A moderate positive linear relationshipIS

From the diagram, we can see that as the number of days absent increases, their grades are…

Answered: The following calculator screenshots…

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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A pediatrician wants to determine the relation that may exist between a child's height and head circumference. She randomly selects 8 children, measures their height and head circumference, and obtains the data shown in the table. The pediatrician wants to use height to predict head circumference. Compute the linear correlation coefficient between the height and head circumference of a child. Height Head Circumference (inches) (inches) 27.5 25 (Round to three decimal places as needed.) 17.3 17.1 26 25.25 27.25 26.75 25.75 27 25 17.2 17 17.6 17.4 17.2 17.3 Enter your answer in the answer box and then click Check Answer. All parts showing Clear All Check Answer Type here to search TOUG Panasonic CF-54 CDSS-4852 TERMO TOGA O O O O D () Scre Loc PrtSc Num Lock F10 F11 F12 F7 F8 F9 SysRq F5 F6 F3 F4 A 8 F1 F2 Esc & 7 0 8 B 90 5 A2 24 近 %#3
Suppose a car's city miles per gallon rating can be determined by the car's weight. The means and standard deviations of these variables and the correlation coefficient between them are reported in the following table: What proportion of the variability in cars' miles per gallon ratings is explained by the least squares line with weight?
The trend of thinner beauty pageant winners has generated charges that the contest encourages unhealthy diet habits among young women. Listed below are body mass indexes (BMI) for beauty pageant winners from two different time periods. Find the coefficient of variation for each of the two sets of data, then compare the variation. The coefficient of variation for the BMI's of beauty pageant winners from the 1920s and 1930s is %
For a sample of eight bears, researchers measured the distances around the bears' chests and weighed the bears. Minitab was used to find that the value of the linear correlation coefficient is r = 0.862. Using a = 0.05, determine if there is a linear correlation between chest size and weight. What proportion of the variation in weight can be explained by the linear relationship between weight and chest size? Click here to view a table of critical values for the correlation coefficient. a. Is there a linear correlation between chest size and weight? O A. No, because the absolute value of r exceeds the critical value of 0.707. O B. Yes, because r falls between the critical values of -0.707 and 0.707. O C. Yes, because the absolute value of r exceeds the critical value of 0.707. O D. The answer cannot be determined from the given information. b. What proportion of the variation in weight can be explained by the linear relationship between weight and chest size? (Round to three decimal…
The mass of a 45.750g piece of copper is measured three times on two different balances with the following results: 1 45.747 1 45.76 2 45.745 2 45.77 3 45.748 3 45.74 Calculate the standard devation for each set of meaurements on each balance. Show work
The maximum weights (in kilograms) for which one repetition of a half-squat can be performed and the jump heights (in centimeters) for 12 international soccer players are given in the accompanying table. The correlation coefficient, rounded to three decimal places, is r=0.692. At a =0.05, is there enough evidence to conclude that there is a significant linear correlation between the variables? E Click the icon to view the soccer player data. Determine the null and alternative hypotheses. Ho: p o Maximum Weights and Jump Heights Ha: p o Maximum Jump height, y Determine the critical value(s). weight, x 190 60 to = (Round to three decimal places as needed. Use a comma to separate answers as needed.) 185 56 155 55 Determine the standardized test statistic. 180 59 175 55 t= (Round to three decimal places as needed.) 170 65 What is the conclusion? 150 52 160 52 Ho. There V enough evidence at the 5% level of significance to conclude that there is a significant linear correlation between the…
The accompanying technology output was obtained by using the paired data consisting of foot lengths (cm) and heights (cm) of a sample of 40 people. Along with the paired sample data, the technology was also given a foot length of 23.5 cm to be used for predicting height. The technology found that there is a linear correlation between height and foot length. If someone has a foot length of 23.5 cm, what is the single value that is the best predicted height for that person? The single value that is the best predicted height is _____cm. The regression equation is Height=50.8+3.20 Foot Length Predictor Coef SE Coef T P Constant 50.82 11.65 4.36 0.000 Foot Length 3.1982 0.4903 6.52 0.000 S=5.50372 R-Sq=71.7% R-Sq(adj)=71.0% Predicted Values for New Observations New Obs Fit SE Fit 95% CI 95% PI 1 125.978 1.744 (121.356, 130.600) (114.681, 137.275) Values of Predictors…
determine whether suicide and homicide rates in metropolitan areas around the country are correlated. a sample of 10 metropolitan areas with their rates (number per 100,000), of suicide and homicide. computed the correlation coefficient of 0.70.
A university would like to describe the relationship between the GPA and the starting monthly salary of a graduate who earned a business degree from the university. The accompanying table shows the monthly starting salaries for eight graduates of the business school along with their corresponding GPAS. Determine the sample correlation coefficient between the starting salary and the GPA of a business graduate of the university. Click the icon to view the salary and GPA data. Starting salary and GPA data (Round to three decimal places as needed.) Starting Salary GPA Starting Salary GPA 2,500 3.1 3,100 3.7 2,800 3.4 2,900 3.9 2,300 2.6 2,000 2.5 2,600 3.5 2,400 3.2 4o5
For a data set of chest sizes (distance around chest in inches) and weights (pounds) of seven anesthetized bears that were measured, the linear correlation coefficient is r=0.147. Use the table available below to find the critical values of r. Based on a comparison of the linear correlation coefficient r and the critical values, what do you conclude about a linear correlation? LOADING... Click the icon to view the table of critical values of r. The critical values are nothing. (Type integers or decimals. Do not round. Use a comma to separate answers as needed.) Since the correlation coefficient r is ▼ between the critical values in the right tail above the positive critical value in the left tail below the negative critical value , there ▼ is not is sufficient evidence to support the claim of a linear correlation.
Fifty-four wild bears were anesthetized, and then their weights and chest sizes were measured and listed in a data set. Results are shown in the accompanying display. Is there sufficient evidence to support Correlation Results the claim that there is a linear correlation between the weights of bears and their chest sizes? When measuring an anesthetized bear, is it easier to measure chest size than weight? If so, does it appear that Correlation coeff, r: 0.959614 a measured chest size can be used to predict the weight? Use a significance level of = 0.05. Critical r: +0.2680855 P-value (two tailed): 0.000 Но: Р H1:P (Type integers or decimals. Do not round.) Identify the correlation coefficient, r. (Round to three decimal places as needed.) Identify the critical value(s). (Round to three decimal places as needed.) O A. There is one critical value at r= . B. There are two critical values at r= ± Is there sufficient evidence to support the claim that there is a linear correlation between…
The accompanying technology output was obtained by using the paired data consisting of foot lengths (cm) and heights (cm) of a sample of 40 people. Along with the paired sample data, the technology was also given a foot length of 17.8 cm to be used for predicting height. The technology found that there is a linear correlation between height and foot length. If someone has a foot length of 17.8 cm, what is the single value that is the best predicted height for that person? Click the icon to view the technology output. The single value that is the best predicted height is (Round to the nearest whole number as needed.) cm. Technology Output The regression equation is Height = 53.3+4.25 Foot Length Predictor Constant Coef SE Coef 53.28 11.44 Foot Length 4.2537 0.4699 S = 5.50739 R-Sq=72.3% R-Sq (adj) = 71.6% T 4.66 9.05 Predicted Values for New Observations New Obs 1 Fit SE Fit 128.996 1.733 (124.309, 133.683) 95% CI Foot New Obs Length 1 17.8 0.000 0.000 Values of Predictors for New…

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