A researcher has a large number of data pairs (age, height) of humans from birth to 70 years. She computes a correlation coefficient, r. a. Would you expect it to be positive or negative? Why? b. What would you suggest to be a major problem with this approach? In other words, would you trust the correlation coefficient? c. The researcher now decides to use data only for adults ages 21 to 60 to compute a correlation coefficient. What value of r should she expect now?

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

The maximum weights (in kilograms) for which one repetition of a half-squat can be performed and the jump heights (in centimeters) for 12 international soccer players are given in the accompanying table. The correlation coefficient, rounded to three decimal places, is r=0.707. At & = 0.05, is there enough evidence to conclude that there is a significant linear correlation between the variables? Click the icon to view the soccer player data. Determine the null and alternative hypotheses. Ho:p = 0 Ha:p # 0 Determine the critical value(s). to = (Round to three decimal places as needed. Use a comma to separate answers as needed.)

Please explain

A study was done asking people how much money they spend per month on their natural gas bill and how much money per month they spend on their electric bill. The correlation r was found to be 0.94 and the p- value for correlation was 0.0003. Then a person with a high natural gas bill will also have a high electric bill. O true false

If SST = 864, SSE = 494, SSxy = -20, and SSxx = 1.08 what is the value of the coefficient of correlation? 0.756 0.428 -0.654 -0.572

Statistics Question

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.

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?