Find the linear correlation coefficient, r, then determine whether there is sufficient evidence to support the claim of a linear correlation between the two variables.
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- K The 'pizza connection' is the principle that the price of a slice of pizza is always about the same as th the pizza and subway cost data in the table below to determine whether there is a linear correlation b items. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value whether there is sufficient evidence to support a claim of linear correlation between the two variables results does it appear that the subway fare is always about the same as a slice of pizza? Use a signi X Pizza Cost and Subway Fares Year Pizza Cost Subway Fare CPI 1960 1973 1986 1995 2002 2003 2009 2013 2015 2019 D 0.15 0.35 1.00 1.25 1.75 2.00 2.25 2.30 2.75 3.00 0.15 0.35 1.00 1.40 1.50 2.00 2.25 2.50 2.75 2.75 29.5 43.9 109.6 152.1 180.0 184.0 214.5 233.0 237.0 252.2 Print Done The linear correlation coefficient is r = (Round to three decimal places as needed.)A past STAT 200 student tells you that there is a very strong positive linear association between the STAT 200 final exam score and the WeBWork Assignment total. What is a plausible value of the correlation coefficient (r)? OA. -1.1 OB. 0.95 OC. -0.95 OD. 0.01 OE. 1.1 OF. 0.56Police sometimes measure shoe prints at crime scenes so that they can learn something about criminals. Listed below are shoe print lengths, foot lengths, and heights of males. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value of r. Determine whether there is sufficient evidence to support a claim of linear correlation between the two variables. Based on these results, does it appear that police can use a shoe print length to estimate the height of a male? Use a significance level of a= 0.01. Shoe Print (cm) | 28.8 Foot Length (cm) 24.8 Height (cm) 30.8 30.4 31.1 28.6 24.6 27.8 26.1 25.3 177.6 179.2 179.2 169.4 169.5
- Consider a two-dimensional scatterplot representing the relationship between two continuous variables. If the correlation coefficient is -1, then: a. All points lie in a straight line with a slope of -1. b. All points lie in a straight line with an unknown negative slope. c. All points do not lie in a straight line but the best fitting regression line has a slope of -1 d. There is a strong positive relationship between the two variables.Calculate the Spearman correlation coefficient between two sets of data: set A = [6, 8, 10, 12, 14] and set B = [2, 4, 6, 8, 10].Listed below are annual data for various years. The data are weights (metric tons) of imported lemons and car crash fatality rates per 100,000 population. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value using a = 0.05. Is there sufficient evidence to conclude that there is a linear correlation between lemon imports and crash fatality rates? Do the results suggest that imported lemons cause car fatalities? Lemon Imports Crash Fatality Rate 231 265 358 483 530 15.8 15.7 15.5 15.2 14.8 What are the null and alternative hypotheses? OA. Ho: p 0 H₁ p=0 OC. Ho p=0 H₁: p>0 Construct a scatterplot. Choose the correct graph below. OA. Ay 17- 16- Q do ° 15- ° 14+ 0 200 400 600 The linear correlation coefficient is r= (Round to three decimal places as needed.) B. Ho: p=0 H₁p 0 OD. Ho: p=0 H₁: p<0 B. COD. Ay 17- Ay 17- Ay 17+ Q о 16- 16- 16- Q 0 ° ° 15- 15- ° G 15- G 14- 14- 14+ 0 200 400 600 0 200 400 600 0 200 400 600
- C. Using the linear correlation coefficient found in the previous step, determine whether there is sufficient evidence to support the claim of a linear correlation between the two variables. Choose the correct answer below. a.) there is sufficient evidence to support the claim of a linear correlation between the two variables. b.) there is insufficient evidence to support the claim of a nonlinear correlation between the two variables. c.) there is sufficient evidence to support the claim of a nonlinear correlation between the two variables. d.) there is insufficient evidence to support the claim of a linear correlation between the two variables. C. Identify the feature of the data that would be missed if part (b) was completed without constructing the scatterplot. Choose the correct answer below. a.) The scatterplot reveals a distinct pattern that is not a straight-line pattern. b.) The scatterplot reveals a distinct pattern that is a straight-line pattern with negative…The blood pressure measurements of a single patient were taken by twelve different medical students and the results are listed below. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value using a = 0.05. Is there sufficient evidence to conclude that there is a linear correlation between systolic measurements and diastolic measurements? systolic (x) diastolic (y) 137 133 139 119 122 121 127 132 130 143 141 137 95 93 100 80 88 80 82 84 81 98 103 94 С. Но: р#0 D. Ho: p=0 H1:p=0 H1:p#0 Construct a scatterplot. Choose the correct graph below. O A. ОВ. C. D. Ay 160- Ay 160- 160- 160- 120- 120- 120- 120- 80- 80- 80- 80- O. 40- 40- 40- 40- X X 0- 0- O 40 80 120 160 0- 0- 40 80 120 160 40 80 120 160 40 80 120 160 The linear correlation coefficient r is (Round to three decimal places as needed.) The P-value is (Round to three decimal places as needed.) Because the P-value is than the significance level 0.05, there sufficient evidence to support the…For a data set of weights (pounds) and highway fuel consumption amounts (mpg) of five types of automobile, the linear correlation coefficient is found and the P-value is 0.033. Write a statement that interprets the P-value and includes a conclusion about linear correlation. The P-value indicates that the probability of a linear correlation coefficient that is at least as extreme is nothing%, which is ▼ high, low, so there ▼ is not is sufficient evidence to conclude that there is a linear correlation between weight and highway fuel consumption in automobiles.
- Use the given data set to complete parts (a) through (c) below. (Use a= 0.05.) 10 8 13 11 14 4 12 7.46 6.77 12.73 7.12 7.81 8.84 6.08 5.38 8.15 6.42 5.74 y Click here to view a table of critical values for the correlation coefficient. 4'8' 12 16 12 16 12 16 *48 12 16 b. Find the linear correlation coefficient, r, then determine whether there is sufficient evidence to support the claim of a linear correlation between the two variables. The linear correlation coefficient is r=. (Round to three decimal places as needed.)Listed below are systolic blood pressure measurements ( in mm Hg ) from the same woman. Right arm 102 101 94 79 79 Left arm 175 169 182 146 144 a) Find the linear coefficient correlation r. What is the critical value in this case ?? ? b) Is there sufficient evidence to conclude that there is a linear correlation between right and left arm systolic blood pressure measurements? c) Find the equation of the regression line between right and left arm systolic. d) What proportion of left arm systolic can be explained by the right arm systolic ? e) Find the best predicted systolic blood pressure in the left arm given that the systolic blood pressure in the right arm is 100 mm Hg.