1. If someone owns an electric car it is represented by a one and if they don’t it is represented by a zero. If someone owns an electric car and their yearly salary in pounds for four people are (0,80000), (0, 17000), (0, 37000) and (1, 58000) calculate the correlation coefficient. 2. How might we interpret this result?

1. If someone owns an electric car it is represented by a one and if they don’t it is represented by a zero. If someone owns an electric car and their yearly salary in pounds for four people are (0,80000), (0, 17000), (0, 37000) and (1, 58000) calculate the correlation coefficient. 2. How might we interpret this result?

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

For each pair of quantities, decide if the correlation coefficient would be close to 1, close to -1, or not be close to 1 or -1. Part: 0/4 Part 1 of 4 (a) The number of hours a student spends studying and the score on that student's exam. The correlation coefficient would be close to 1 Part: 1/4 Part 2 of 4 Part: 2/4 X (b) The number of hours a student spends studying and the number of letters in that student's name. The correlation coefficient would be close to -1 Part 3 of 4 X Ś X Ś (c) The number of hours an overweight person spends exercising and that person's weight. The correlation coefficient would be close to 1 5
For each pair of quantities, decide if the correlation coefficient would be close to 1, close to -1, or not be dose to 1 or-1, Part: 0/4 Part 1 of 4 (a) The number of years of education completed and age of the car that person drives. The correlation coefficient would (Choose one) be dose to 1 be dose to -1 not be close to 1 or -1
Select the most appropriate response. If the correlation between a person’s age and annual income is 0.60, then the coefficient of determination tells us that: 36% of the variation in a person’s annual income can be explained by the predictor variable age. 36% of a person’s annual income can be explained by their age 60% of the variation in a person’s annual income can be explained by the predictor variable age 60% of a person’s annual income can be explained by their age
Suppose a friend of yours computes a correlation coefficient of +1.10 and comes to you for advice as to how to interpret it. What would you tell your friend?
Give an example of two variables that you would expect to have a correlation close to or equal to -1. Give an example of two variables that you would expect to have a correlation close to or equal to 0. Remember that survey question you wrote? Take the class responses to your survey as data related to the one variable of your question. Now, take the list of responses from the survey question that one of your classmates wrote. Write down both lists of data. (If one sample size happens to be different from the other, cut the larger sample size down to that of the smaller sample size.) Calculate the correlation between the two variables. Describe the linear relationship between these two variables. (data for number 3) How many cars have you had so far in your lifetime? 0,1,1,1,2,2,2,2,3,3,3,3,4,4,5,6,6,7,10. How many days per week do you exercise? 0,0,0,1,2,3,3,3,3,4,4,4,4,5,5,5,5,6,6,6
Consider the bivariate data set with n = 7 observations X -4 1 -6 9. -8 -4 -4 Y 20 60 -10 99 -3 16 18 where a linear relationship between X and Y is investigated. The equation relating Y to X is formulated by Y = Bo + B1X + e and is called the simple linear regression equation. Use your calculator to answer the following questions. Give the values of the least squares estimates Bo Round your answer to the nearest integer. Round your answer to 3 decimal places.
Suppose data are collected concerning the weight of a person in pounds and the number of calories burned in 30 minutes of walking on a treadmill at 3.5 miles per hour. How would the value of the correlation coefficient, r, change if all of the weights were converted to kilograms?
A negative correlation means that decreases in the X variable tend to be accompanied by decreases in the Y variable. T or F
A professor believed that there is a correlation between people’s weights and number of times they eat out. He recorded a group of students’ weights (measured in lbs.) and the number of times they ate out last week. The r value was 0.90. We can tell that the correlation between students’ weights (measured in kilogram) and the number of times they ate out last week is: Bigger than 0.9 0.90 Smaller than 0.9 We cannot tell ( don't hand writing solution)
4. Put the r-values in order from the weakest to strongest correlation. r = -0.90 r = 0.050 r = 0.80 r = -0.72 r= 0.45 r= -0.88 r = 0.97
Dr. Erie, a researcher at the Moore County Botany Institute, reported the following correlations. The correlation between pH level of soil and tomato weight is r₁ = -0.4. The correlation between hours of sunlight and tomato weight is r2 = 0.1. According to this information, which of the following statements are true? Select all that apply. Larger tomatoes result from more daily hours of sunlight. Larger tomatoes result from higher soil pH level. Tomato size is related more strongly to hours of sunlight than to soil pH level. None of these are true.
A teacher collected information from a class of 25 students about the time, in hours, they spent studying the previous week and the time, in hours, they spent on the Internet the previous week. The value of the correlation coefficient between hours spent studying and hours spent on the Internet was −0.72. If the teacher changes the units of each variable from hours to minutes, what will be the value of the correlation coefficient between minutes studying and minutes spent on the Internet?