3. The above data lists a random sample of paired data: Waist size in cm to Body MassIndex in Weight to height in KG per Meter-Squared (BMI).a. Do a scatterplot of the data and indicate below whether based on the scatterplotyou think there is by circling one of the following.positive linear correlationnegative linear correlationno linear correlationb. What is the correlation coefficient rr=c. What is the P-valueP-value =d. At the 0.05 significance level do you conclude that there is (circle your conclusion)positive linear correlation between waist size and body mass index (BMI)negative linear correlation between waist size and body mass index (BMI)no linear correlation between waist size and body mass index (BMI)e. Regardless of your answer to d., give the "a" and "b" of the regression equation, andthe give the regression equationi. a =ii. b =iii. y = a + bxf. Use the regression equation from part e. to estimate the BMI (y value) for an adultwith a waist size of 100 cm.y = WAIST BMI120.4 33.3107.8 28.0120.3 45.497.2 28.495.1 25.9112.0 31.178.0 20.1103.5 32.789.7 25.8112.0 36.595.0 25.8115.3 34.5118.8 37.492.6 26.175.5 19.3101.8 29.992.5 27.4100.8 31.482.8 21.092.9 28.5120.4 30.8107.8 31.2120.3 33.697.2 26.795.1 24.5112.0 21.678.0 27.4103.5 29.389.7 24.6112.0 29.178.8 23.265.8 19.4114.4 38.978.0 21.0106.8 33.3112.4 31.894.8 27.390.6 21.695.2 27.171.5 20.0

Given data: Waist BMI 120.4 33.3 107.8 28 120.3 45.4 97.2 28.4 95.1 25.9 112 31.1…

Answered: 3. The above data lists a random sample…

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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Suppose the correlation coefficient r = 0.09 for a data set Find: a. The coefficient of determination r (round to 3 decimal places) b. The percentage of explained variation = % (round to 1 decimal place) c. The percentage of unexplained variation = % (round to 1 decimal place)
Listed below are paired data consisting of amounts spent on advertising (in millions of dollars) and the profits (in millions of dollars). Determine if there is significant linear correlation between advertising cost and profit. Use a significance level of 0.10 and round all values to 4 decimal places. Advertising Cost Profit 3 22 4 20 5 21 26 7 24 8 27 9 25 10 27 11 28 Ho: ρ 0 На: р 0 Find the Linear Correlation Coefficient r = Find the p-value p-value =
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=0.707. At & = 0.05, is there enough evidence to conclude that there is a significant linear correlation between the variables? Click the icon to view the soccer player data. Determine the null and alternative hypotheses. Ho:p = 0 Ha:p # 0 Determine the critical value(s). to = (Round to three decimal places as needed. Use a comma to separate answers as needed.)
Listed below are paired data consisting of amounts spent on advertising (in millions of dollars) and the profits (in millions of dollars). Determine if there is significant linear correlation between advertising cost and profit . Use a significance level of 0.10 and round all values to 4 decimal places. Advertising Cost Profit 3 23 4 23 5 22 6 26 7 25 8 25 9 25 10 30 11 31 12 31 Ho: ρ = 0Ha: ρ ≠ 0 Find the Linear Correlation Coefficient r = Find the p-value p-value =
A population data set produced the following information. N = 250. Ex = 9870, E y = 1452, E xy = 84,890 E = 485,590, and E = 135,115. Find the linear correlation coefficient p. Round your answer to three decimal places. p = i
nalysis Name: Date: Score: Section Exercise 10.3 1. SJS Company has been selling to retail customers in the Metro Manila area. They advertise extensively on radio, print ads, and in the internet. The owner would like to review the relationship between the amount spent on advertising expense (in P000s) and sales (in P000s). Below is information on advertising expense and sales for the last 9 months. Month Jan Advertising Expense 10 Sales Revenue Feb Mar Apr May June July Aug Sept 8 12 11 13 190 215 190 210 235 208 15 14 13 16 170 175 250 Find the coefficient of correlation. Determine at the 0.10 significance level whether the correlation in the population is greater than zero. Step 1: State the hypotheses. Ho: Hi: Step 2: The level of significance and critical region. a= Step 3: Complete the table and compute for the value of r and t. and tcritical = Month x x 22 x2 xy Jan Feb Mar Apr May Jun Jul Aug Sept Σχ= Σy= ΣΥ Σαν = Σx=- tcomputed= r = Step 4: Decision rule. Step 5: Conclusion.…
You wish to determine if there is a linear correlation between the age of a driver and the number of driver deaths. The following table represents the age of a driver and the number of driver deaths per 100,000. Use a significance level of 0.01 and round all values to 4 decimal places. Driver Age Number of Driver Deaths per 100,000 65 27 34 27 76 24 55 34 71 21 49 24 34 36 27 19 Ho: ρ = 0Ha: ρ ≠ 0 Find the Linear Correlation Coefficient r = Find the p-value p-value = The p-value is Less than (or equal to) αα Greater than αα The p-value leads to a decision to Reject Ho Accept Ho Do Not Reject Ho The conclusion is There is a significant positive linear correlation between driver age and number of driver deaths. There is a significant linear correlation between driver age and number of driver deaths. There is a significant negative linear correlation between driver age and number of driver deaths. There is insufficient evidence to make a…
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…
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The data shown below consists of the price (in dollars) of 7 events at a local venue and the number of people who attended. Determine if there is significant negative linear correlation between ticket price and number of attendees. Use a significance level of 0.05 and round all values to 4 decimal places. Ticket Price Attendence 6. 109 10 114 14 139 18 142 22 139 26 132 30 154 Но: = 0 На: р Find the Linear Correlation Coefficient r = Find the p-value p-value = %3D The p-value is Less than (or equal to) a Greater than a The p-value leads to a decision to Reject Ho Аcсept Ho Do Not Reject Ho The conclusion is There is a significant linear correlation between ticket price and attendance. There is a significant negative linear correlation between ticket price and attendance. There is a significant positive linear correlation between ticket price and attendance. There is insufficient evidence to make a conclusion about the linear correlation between ticket price and attendance.
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