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 betweenhours 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 following information is given: The correlation between the "pH level of the soil" and "weight…

Answered: Dr. Wright, a researcher at the Young…

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 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.
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
If we find that there is a linear correlation between the concentration of carbon dioxide in our atmosphere and the global temperature, does that indicate that changes in the concentration of carbon dioxide cause changes in the global temperature? Choose the correct answer below. O A. No. The presence of a linear correlation between two variables does not imply that one of the variables is the cause of the other variable. O B. Yes. The presence of a linear correlation between two variables implies that one of the variables is the cause of the other variable.
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
The weights (in pounds) of 6 vehicles and the variability of their braking distances (in feet) when stopping on a dry surface are shown in the table. Can you conclude that there is a significant linear correlation between vehicle weight and variability in braking distance on a dry surface? Use a = 0.01. Weight, x Variability in braking distance, y 5960 5320 6500 5100 5850 4800 D 1.72 1.93 1.88 1.61 1.66 1.50 E Click here to view a table of critical values for Student's t-distribution. Setup the hypothesis for the test. Họip = 0 H:p # 0 Identify the critical value(s). Select the correct choice below and fill in any answer boxes within your choice. (Round to three decimal places as needed.) O A. The critical value is O B. The critical values are – to = and to =
Suppose the correlation between height and weight for adults is +0.80. What proportion of the variability in weight can be explained by the relationship with height? A. 20% B. 36% C. 64% D. 80%
A researcher measures GPA and height for a group of high school students. What kind of correlation is likely to be obtained for these two variables?
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…
Which of the following correlation coefficients indicate the strongest relationship between two variables? A .20 B .87 C .80 D -.95
Which of the following values represents the weakest correlation between two variables? о г= -0.17 г= 0.07 K r=0.45 r=-0.62 r = 0.81 00000
If when measuring two quantitative variables on an individual, we find that increases in the first variable x correspond to decreases in the second variable y, we say that A. there is a positive association between the two variables. b. there is a negative association between the two variables. c. there is no correlation between the two variables. d. there is a cause-and-effect relationship between the two variables.

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