There is a 0.86 correlation between variables A and B. The partial correlation between A and B, after con- trolling for a third variable, is 0.67. Does this third variable completely account for the relation between A and B? Explain your answer.

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A correlation of 0.5. The community of having a cat and dog average is 60% and SD = 15. find the score of people having cats that show 75%.

Two variables are found to have a strong positive linear correlation. Pick the correct statement. An increase in one variable potentially causes a decrease in the other. An increase in one variable does not cause a decrease in the other. An increase in one variable does not cause an increase in the other. An increase in one variable potentially causes an increase in the other. An increase in one variable causes a decrease in the other. An increase in one variable causes an increase in the other.

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.

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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

The data below shows the selling price (in hundred thousands) and the list price (in hundred thousands) of homes sold. Construct a scatterplot, find the value of the linear correlation coefficient r, and P-value using a = 0.05. Is there sufficient evidence to conclude that there is a linear correlation between the two variables? Selling Price (x) List Price (y) H₁: p#0 400 412 Construct a scatterplot. Choose the correct graph below. 301 315 376 387 434 440 459 488 H₁ p > 0 477 480 319 324 352 368 417 434 330 341

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.     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.   B. Yes. The presence of a linear correlation between two variables implies that one of the variables is the cause of the other variable.

After gathering data about the number of starfish and measuring the pollution in areas of the ocean you find a negative linear correlation between pollution levels and number of starfish. What can you conclude based on this information? a. There is a confounding variable that is affecting both pollution and starfish. b. As pollution rises the number of starfish falls c. That pollution is causing starfish to die, leading to the negative correlation d. That pollution is supporting starfish, leading to the negative correlation