One may wonder if people of similar heights tend to marry each other. For this purpose, you collect asample of newly married couples. Let X be the height of the husband in centimeters and Y the heightof the wife in centimeters. Consider the following statements:1. If every man married a woman exactly 5 centimeters shorter than him, the correlation coefficientwould be equal to -1.2. Neither the covariance nor the correlation coefficient would change if the heights weremeasured in inches rather than in centimeters.Both statements are trueOnly statement 2. is trueBoth statements are falseOnly statement 1. is true

Here given One may wonder if people of similar heights tend to marry each other. For this purpose,…

Answered: One may wonder if people of similar…

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

1. In your own words, what does it mean to have a linear correlation (Give an example of one that is NOT in the book, online or given in class.) 2. In your own words, what does it mean to have a non-linear correlation? (Give an example of one that is NOT in the book, online or given in class.) 3. Describe the error: Given: The linear correlation coefficient between scores on a math test and scores on a test of athletic ability is negative and close to zero. Conclusion: People who score high on the math test tend to score lower on the test of athletic ability.
For each of a number of cities across Canada, the number of people with Cantonese as a mother tongue and the number of people with Mandarin as a mother tongue were rocorded. A scatterplot of the data is shown in the figure below. The correlation between the number of Cantonese speakers in a city aud the number of Mandarin speakers is 0.980. Do you think this correlation is a reasonable summary of the relationship? Why, or why not? (a) If the two largest cities (Toronto and Vancouver) were removed, the correlation would be even higher. (b) No, because there are outliers and/or influential points. (c) Yes, because the relationship is more or less linear. (d) No, because the relationship is clearly curved. (e) Yes, because there are no influential points.
Suppose a researcher is interested in examining the relationship between a person 's age and whether he or she likes the taste of cilantro. She collects a sample of n- 10 people and asks them whether they like the taste of cilantro. The following table summarizes the results. Does not like Cilantro Does like Cilantro 18 years old 2 18+ years old 3 The researcher wants to calculate the correlation between a person 's age and whether he or she likes the taste of cilantro. To do so, you (the researcher) must first create a table of the data by converting each variable to a numerical value. Assign a 0 to "< 18 years old" and 1 to "18+ years old." Then assign O to "does not like the taste of cilantro" and a 1 to " likes the taste of cilantro." Complete the top two rows of the your (the researcher's) data. Age (0 is <18; 1 is 18+) Likes the taste of Cilantro (0 is no; 1 is yes) a) ob) 1 a) Ob) 1 a) ob) 1 a) Ob) 1 1 1 1 1 1 1 1 The phi-coefficient is a) -0.09 b) -0.16 c) -0.20 d) 0.80
Dr. Wright, a researcher at the Young County Botany Institute, reported the following correlations. The correlation between pH level of soil and tomato weight is r₁ = 0.8. The correlation between hours of sunlight and tomato weight is r2 = 0.7. 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 lower soil pH level. ✔Tomato size is related more strongly to hours of sunlight than to soil pH level. None of these are true.
2. Consider the following examples; would you expect the correlation coefficient to be close to 1, -1, or 0 (10 points): The amount of time a dog is walked, and the number of hours the dog sleeps at night Outdoor temperature and snowfall. The length of time someone wears braces and their SAT scores. 3. The following graph represents the amount of time that someone studies for their final exam, and their final examination grade (HINT) (20 points). Student 1 Student 2 Student 3 Student 4 Student 5 Student 6 Hours Studied 4 7 11 8 10 8 Final Exam Grade 55% 72% 88% 93% 91% 84% Graph the following students as ordered pairs. Let the x-axis represent the hours studied, and the y-axis represent the students’ final exam grade. Circle the value that best represents the estimate of r: (circle one) -0.99, -0.62, -0.30, 0, 0.30, 0.75, 0.85, 0.99
A survey was taken in 2018 that asked people about their saving habits. Researchers wanted to know if people who saved more also spent less. The scatterplot below shows their results when comparing two variables: the amount people reported that they put into savings each month, and the amount they reported that they spent on clothes. The researchers found the correlation coefficient for this data to be -0.239. Which of the following is true about these variables? a. There is no relationship between savings and money spent on clothes each month.b. There is a weak, positive linear relationship between savings and money spent on clothes each month.c. There is a perfect, negative linear relationship between savings and money spent on clothes each month.d. There is a weak, negative linear relationship between savings and money spent on clothes each month.
The following statement contains an error. Choose the statement that best explains the error. "The correlation between shoe size and height is 0.87 inches" A. Correlation requires that both of the variables be categorical B. When stating the correlation coefficient, one must state whether it is a positive or negative relationship C. This statement does not tell us whether or not shoe size is correlated with height D. When reporting correlation, one does not report units because correlation has no units E. There is no error in this statement
a. Calculate the sample covariance.X Y-3 -913 95 12b. Calculate the sample correlation.c. Describe in words the information given to us by the sample covariance and by the sample correlation.Explain how the correlation gives us more precise information.d. Explain why the covariance is not a good measure of the strength of the linear relationship between the twovariables.e. Sketch a scatterplot of a bivariate dataset with a correlation of 0.9f. Sketch a scatterplot of a bivariate dataset with a correlation of -0.3.
8.
Which of the following correlation coefficients indicate the strongest relationship between two variables? A .20 B .87 C .80 D -.95
e. Compute the covariance and correlation coefficient r between the right tire pressure. f. How do you know the relationship between pressure in the left and right tires is positive. g. What value would a correlation coefficient (r) be close to if there was no (linear) relationship between the 2 tire pressures?
A nutritionist collects data from 25 popular breakfast cereals. For each cereal, the number of calories per serving is plotted on the x-axis against the number of milligrams of sodium on the y-axis. The value of r for the resulting scatterplot is 0.83. How would the value of the correlation coefficient, r, change if sodium was plotted on the x-axis and calories plotted on the y-axis? The value ofr would increase. The value of r would not change. The value of r would change to -0.83. The value ofr could increase or decrease, depending of the strength of the new relationship.

SEE MORE QUESTIONS

Recommended textbooks for you

MATLAB: An Introduction with Applications

Statistics

ISBN:

9781119256830

Author:

Amos Gilat

Publisher:

John Wiley & Sons Inc

Probability and Statistics for Engineering and th…

Statistics

ISBN:

9781305251809

Author:

Jay L. Devore

Publisher:

Cengage Learning

Statistics for The Behavioral Sciences (MindTap C…

Statistics

ISBN:

9781305504912

Author:

Frederick J Gravetter, Larry B. Wallnau

Publisher:

Cengage Learning

MATLAB: An Introduction with Applications

Statistics

ISBN:

9781119256830

Author:

Amos Gilat

Publisher:

John Wiley & Sons Inc

Probability and Statistics for Engineering and th…

Statistics

ISBN:

9781305251809

Author:

Jay L. Devore

Publisher:

Cengage Learning

Statistics for The Behavioral Sciences (MindTap C…

Statistics

ISBN:

9781305504912

Author:

Frederick J Gravetter, Larry B. Wallnau

Publisher:

Cengage Learning

Elementary Statistics: Picturing the World (7th E…

Statistics

ISBN:

9780134683416

Author:

Ron Larson, Betsy Farber

Publisher:

PEARSON

The Basic Practice of Statistics

Statistics

ISBN:

9781319042578

Author:

David S. Moore, William I. Notz, Michael A. Fligner

Publisher:

W. H. Freeman

Introduction to the Practice of Statistics

Statistics

ISBN:

9781319013387

Author:

David S. Moore, George P. McCabe, Bruce A. Craig

Publisher:

W. H. Freeman

SEE MORE TEXTBOOKS