a) Determine the independent and dependent variable. b) Calculate the Pearson's product moment coefficient of correlation and explain its meaning.
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A: a)
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- Use Pearson’s Product Moment correlation coefficient (r) to find the relationship between the independent variable (hour spent in studying) to the dependent variable (achievement score). Complete the table below and follow the steps in solving Pearson’s Product Momentcorrelation coefficient (r). Round off your answer into two decimal places.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. Do the results suggest that imported lemons cause car fatalities? oom 482 531 14.9 ons Lemon Imports Crash Fatality Rate 230 264 359 15.9 15.7 15.5 15.2 ct placement ercial as a pn t principle: In Construct a scatterplot. Choose the correct graph below. OB. Oc. OD. ean a lot of r OA. ry". inal persuas Ay 17- Q 17- Ay 17- 17- 16- 16- 16- 16- 15- 15- 15- 15- 14- 14- 14+ 600 14+ 200 400 600 200 400 600 200 400 60 200 400Properties of scaling. Suppose that you want to examine the relationship between wages and experience measured in months rather than years. a) What is the variance of experience in months? Compare this to 1b). b) What is the covariance of wages and experience in months? Compare this to 1d). c) What is the correlation of experience and wages? Compare this to le). d) Prove mathematically that the Corr(cX,Y) = Corr(X,Y) using the properties of summation from class. Show each step of your proof.
- Find the equation of the regression that model the relationship between the weight of mail and number of order using HYPERBOLIC EQUATION. Compute for the correlation coefficient using PEARSON PRODUCT MOMENT CORRELATION COEFFICIENT (PPMCC).Q12 a) Construct a regression model to determine the relationship between individual yearly income and the value of the car owned. b) Using the regression equation from (a) determine the value of the car if the yearly income is $40,000 c) Describe the relationship between yearly income and value of the car owned d) Identify the independent variable and dependent variable based on the regression model constructed in (a) e) Explain why it is incorrect to predict the value of the car if an individual income is $10,000Can you please check my work
- Data was gathered on the amount of rainfall X (in inches) for the last 5 years to analyze if the amount of rainfall X (in inches) could be used to predict the acorn output Y (in tons) for a group of oak trees. Researchers expect the the acorn output to increase linearly with the increase in rainfall amount. That is, they are specifically interested in testing if the correlation between the rainfall and the acorn output is positive (i.e.: ) . When the necessary conditions are satisfied, under the null hypothesis, test statistic for above test Group of answer choices follows a t distribution with degrees of freedom (n-1) follows a chi-square distribution with degrees of freedom (n-1) follows a t distribution with degrees of freedom (n-2) follows a standard normal distribution. follows a chi-square distribution with degrees of freedom (n-2)The following table shows the number of units of a certain item sold by a store over a month in terms of the price in dollars charged by the store. Price in dollars 0.90 1.00 1.15 1.25 1.40 Number sold . 315 280 230 215 195 Use technology to find the correlation coefficient for the data. (Use decimal notation. Give your answer to two decimal places.) correlation coefficien What type of correlation is there between the price and the number sold?A car salesperson wants to develop a method to predict the resale value of trucks based on the age of the truck. age of car Resale Value O 35000 1 32000 2 31250 3 29000 4 32350 S 25000 6 26000 7 23000 8 22000 9 19000 10 21500 11 20000 Use the data provided and excel to calculate the correlation coefficient. (Round your answer to 4 decimal places).
- 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 correlationListed 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.13 A Calculate Pearson's product Moment Correlation Coefficient and indicate its significance. Age(x) 3031 4243 44 45 Mark (y) 30 36 42 44 48 58 B Calculate the spearman's rank correlation for the data and explain the value. Age (x) 25 26 28 32 35 40 Mark (y) 60 65 77 89 72 87