Determine whether the following bivariate data are correlated or not. If they are correlated, tell the direction of theassociation. Evaluate whether the correlation is most likely strong or week.a. Annual income of the family and floor area of the residence house.b. Age and price of a car.c. Gross national product ad level of technology of a country.d. Age and reaction time of persons over 18 years of age.e. Yearly income and number of years of schooling of company owners.

Given that We have to find the direction of association positive or negative.... a. Annual…

Answered: Determine whether the following…

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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You might expect the correlation between the horsepower of new cars and their gas mileages in miles per gallon to be: Group of answer choices A substantial negative correlation A substantial positive correlation A small correlation
Is there a linear relationship between educational attainment and annual salary? a. Draw the scatterplot for the variables. b. Describe the relationship, if any, shown by the scatterplot. c. Calculate r, the correlation coefficient. How does the correlation coefficient compare to the relationship you saw in the scatterplot? Number of Years 7 9 6 7 11 12 11 3 3 7 9 1 Salary (in Dollars) $48,897 $62,866 $54,585 $56,611 $53,541 $53,541 $47,027 $47,970 $46,668 $48,029 $46,735 $45,000 Is there a linear correlation between a mathematics instructor’s years of experience and his or her annual salary? a. Draw the scatterplot for the variables. b. Describe the relationship, if any, shown by the scatterplot. c. Calculate r, the correlation coefficient. How does the correlation coefficient compare to the relationship you saw in the scatterplot?
For the following pairs of variables, indicate whether you would expect a positive correlation, a negative correlation, or close to 0 correlation. Maximum daily temperature and cooling costs Interest rates and number of loans Incomes of husbands and wives in dual career families Height and IQ Height and shoe size Score on the Math SAT and Verbal SAT scores Time spent on video games and college GPA Use of fertilizer and yield of crops
Answer quickly please. Need answer ASAP. Choose one letter only. No need for long explanation. 1. A characteristic of interest for the elements is called: A. a sample B. a data set C. a variable D. an observation 2. What does the correlation coefficient (r) measure in a correlation analysis? A. The strength and direction of a linear relationship between two variables. B. The causal relationship between two variables. C. The difference between the means of the two groups. D. The variability of a single variable. 3. You work as an analyst for a retail company, and you are interested in understanding how advertising spending (independent variable) affects monthly retail sales (dependent variable). In a simple linear regression equation, what does the regression slope coefficient (B1) represent in this scenario? A. The average monthly retail sales for all companies B. The change in average monthly retail sales is associated with a one-unit increase in advertising spending. C. The…
Use the data values in the table below to calculate the correlation between the variables x and y. Submit the link through Canvas to either a photo of your work on paper or a link to a google sheet. y 5 2.86 4.48 7 3 8. 3.92 3.34 10 0.96 11 2.38 12 2.8 Give your answer to three decimal places. Submit Question 6.
Use the data set below to answer the following questions where weight is your independent variable and MPG is your dependent variable: 4. Give a predicted value of yˆfor a value of the explanatory variable which is not an actual observation in your data set. 6. What is the correlation coefficient, r? Interpret r.
Identify the type of correlation in the following scatter plot. e Skip step McCully, Aliyah 9. 24AMCCully21C
use the sample data to construct a scatterplot. Use the first variable for the x-axis. Based on the scatterplot, what do you conclude about a linear correlation? FORECAST AND ACTUAL TEMPERATURES The table lists actual high temperatures and the high temperatures that were previously forecasted for these same days. The table includes data for ten different days near the author’s home. What does the result suggest about the accuracy of five-day predicted high temperatures?
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 linear correlation between ticket price and number of attendees. Use a significance level of 0.01 and round all values to 4 decimal places. Ticket Price 6 10 14 18 22 26 30 r= Ho: p= 0 Ha: p=0 Find the Linear Correlation Coefficient Find the p-value p-value= Attendence 151 146 146 145 The p-value is 138 137 137 O Less than (or equal to) a O Greater than a The p-value leads to a decision to Accept Ho Reject Ho Do Not Reject Ho The conclusion is There is insufficient evidence to make a conclusion about the 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 a significant linear correlation between ticket price and attendance.
2. Step 3.2 Instructions: Please answer these a.b.c questions. Dont use excel. Please explain well by your knowledge.
Let x be the average number of employees in a group health insurance plan, and let y be the average administrative cost as a percentage of claims.
Police sometimes measure shoe prints at crime scenes so that they can learn something about criminals. Listed below are shoe print 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. Use a significance level of a = 0.01. Click to view the data on shoe print lengths and heights. Construct a scatterplot. Choose the correct graf Shoe Print Lengths versus Heights of Males O B. OD. 210- 200- 190- 180- 170- 160- 20 24 28 32 36 40 Shoe Print Length (cm) 210 200 190 180 170 160 2101 200- Shoe Print 190- Length (cm) Height (cm) 176.0 180- 170- 160- 20 24 28 32 36 40 31.4 28.9 181.2 31.5 194.5 Shoe Print Length (cm) 32.3 172.9 30.4 174.0 The linear correlation coefficient is r= 32.9 190.5 (Round to three decimal places as needed.) 31.0 176.6 30.8 170.0 30.5 171.9 32.3 175.5 30.5 200.1 32.6 199.3…

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