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

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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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For a data set of weights (pounds) and highway fuel consumption amounts (mpg) of twelve types of automobile, the linear correlation coefficient is found and the P-value is 0.009. Write a statement that interprets the P-value and includes a conclusion about linear correlation.
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.
The data below are the ages and systolic blood pressures (measured in millimeters of mercury) of 9 randomly selected adults. What is the best predicted value for y given x = 60? Assume that the variables x and y have a significant correlation. Age, x Pressure, y A. 152 B. 148 C. 150 D. 146 38 41 116 120 45 48 51 53 57 123 131 142 145 148 61 65 150 152
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
Click this Video for Finding Correlation Coefficient by Using Formula. Yessica thought that there was a correlation between the amount of time students slept the evening before their final exam and their final exam grade. She took an SRS of 5 students in her class and recorded the sleep time the evening before their final exam, and their final exam score. Let the sleep time the evening before the final exam represents the explanatory variable, and the final exam score be the response variable. Below is a sample data set. x (hour) 8 9 3 9 1 2 3 4 5 Calculate the sample correlation coefficient (r) to three decimal places. r= 9 Why would we expect the correlation coefficient to be positive? As the sleep time increases, exam score increases As the sleep time increases, exam score decreases As the sleep time decreases, exam score increases There is no change in exam score to sleep time C E y (score) 91 94 51 100 90 C A
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 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.
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 of r would increase. The value of r would not change. The value of r would change to –0.83. The value of r could increase or decrease, depending of the strength of the new relationship.
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?
Please provide answers for the empty boxes. The following data are the morning and evening high tide levels for Charleston, SC from January 1-14,2017. The information for the PM high tide for January 4 is missing. Create a scatter plot. Find the regression line and use it to estimate the PM high tide for January 4. Then find the correlation coefficient. (NOTE: The first column identifies the day. This data will not be used in the scatter plot.)
Assume that you have paired values consisting of heights (in inches) and weights (in lb) from 40 randomly selected men. The linear correlation coefficient r is 0.506. Find the value of the coefficient of determination. What practical information does the coefficient of determination provide? Choose the correct answer below. O A. The coefficient of determination is 0.256. 25.6% of the variation is explained by the linear correlation, and 74.4% is explained by other factors. O B. The coefficient of determination is 0.744. 25.6% of the variation is explained by the linear correlation, and 74.4% is explained by other factors. O C. The coefficient of determination is 0.744. 74.4% of the variation is explained by the linear correlation, and 25.6% is explained by other factors. O D. The coefficient of determination is 0.256. 74.4% of the variation is explained by the linear correlation, and 25.6% is explained by other factors.

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