To investigate the influence of distracted driving, 13volunteers were asked to participate in a studyHow would the correlation change if the stoppingdistances were recorded in meters, rather than feet?involving a driving simulator. The participants drove ata safe speed but were told to stop the car at a randommoment during the simulation. The scatterplot showsthe reaction time and the simulated car's stoppingdistance (in feet) for each volunteer. The value of r forO The value of the correlation coefficient would notchange.O Since the points would be more spread out, thevalue of the correlation coefficient would decrease.the scatterplot is 0.935.O Since the number of meters would be less than thenumber of feet, the value of the correlationcoefficient would increase.Driving Reaction TimesO Since the number of meters would be less than the80number of feet, the value of the correlationcoefficient would decrease.60Mark this and returnSave and ExitSubmitNext65°F CrDELLF3F4F5F6F7F8F9F10F11PrtScrF12HorInsert%23&8.8.EY{DF GHJKবoping Distance (Feet)

The value of r for the given scatterplot is 0.935

Answered: How would the correlation change if the…

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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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?
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 correlation between midterm and final grades for 300 students is 0.620. If 5 points are added to each midterm grade, the new r will be: a. 0.124 b. 0.57 c. 0.62 d. 0.744
A researcher gathered a sample of participants who volunteered for a studying of phobias. She measured anxiety level of participants as they viewed photos of spiders and again when they viewed puppies. Which statistical test is appropriate for this study and why?
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.
A random sample of college students was surveyed about how they spend their time each week. The scatterplot below displays the relationship between the number of hours each student typically works per week at a part- or full-time job and the number of hours of television each student typically watches per week. The correlation between these variables is r = –0.63, and the equation we would use to predict hours spent watching TV based on hours spent working is as follows: Predicted hours spent watching TV = 17.21 – 0.23(hours spent working) Since we are using hours spent working to help us predict hours spent watching TV, we’d call hours spent working a(n) __________________ variable and hours spent watching TV a(n) __________________ variable. The correlation coefficient, along with what we see in the scatterplot, tells us that the relationship between the variables has a direction that is _________________ and a strength that is ______________________. According to the…
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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 0.594. 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 0.353. 64.7% of the variation is explained by the linear correlation, and 35.3% is explained by other factors. O B. The coefficient of determination is 0.647. 35.3% of the variation is explained by the linear correlation, and 64.7% is explained by other factors. O C. The coefficient of determination is 0.647. 64.7% of the variation is explained by the linear correlation, and 35.3% is explained by other factors. O D. The coefficient of determination is 0.353. 35.3% of the variation is explained by the linear correlation, and 64.7% is explained by other factors.
A company wishes to know whether advertising expenditure is related to sales volume. Using the past two years of data for these two variables, they determined the correlation coefficient is +0.93. This indicates 23 Multiple Choice 1 Dints awarded Scored a strong indirect relationship between advertising expenditure and sales volume. References a weak indirect relationship between advertising expenditure and sales volume. a strong direct relationship between advertising expenditure and sales volume. a weak direct relationship between advertising expenditure and sales volume.
The accompanying technology output was obtained by using the paired data consisting of foot lengths (cm) and heights (cm) of a sample of 40 people. Along with the paired sample data, the technology was also given a foot length of 17.8 cm to be used for predicting height. The technology found that there is a linear correlation between height and foot length. If someone has a foot length of 17.8 cm, what is the single value that is the best predicted height for that person? Click the icon to view the technology output. The single value that is the best predicted height is (Round to the nearest whole number as needed.) cm. Technology Output The regression equation is Height = 53.3+4.25 Foot Length Predictor Constant Coef SE Coef 53.28 11.44 Foot Length 4.2537 0.4699 S = 5.50739 R-Sq=72.3% R-Sq (adj) = 71.6% T 4.66 9.05 Predicted Values for New Observations New Obs 1 Fit SE Fit 128.996 1.733 (124.309, 133.683) 95% CI Foot New Obs Length 1 17.8 0.000 0.000 Values of Predictors for New…
Compute and interpret the coefficient of multiple correlation. Number 4 answer is missing.
Below shows the linear relationship between first year college GPA and high school GPA For both variables the GPA ranges from 0 to 4 in this sample. However, for the high schools sampled in this region, the true range of GPA is 0 to 5, how might this affect the correlation between these two variables?

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