1. Find Karl Pearson's co-efficient of correlation of the following data. Age of husband (x): 20 22 23 25 25 28 29 30 30 34 Age of wife (y): 18 20 22 24 21 26 26 25 27 29
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- You are given the total number of weekly sales from two employees over a 7-week period. Calcu- late the Pearson correlation coefficient given the following data: Week 1 Week 2 Week 3 Week 4 Week 5 Week 6 Week 7 Employee A Sales 15 20 25 18 22 30 28 Employee B Sales 12 18 22 15 19 27 253.Given the following data X= additional number of Y= Grade improvement since last exam studying hours since last exam 2 5 4 6 5 8 5 10 7 11 8 12 10 13 12 14 12 15 9 12 a. Draw a scatter diagram and speculate on the direction linear relationship between the two variables (in complete sentence)...Clearly label the 2 axes... b.…0. 16. Calculate co-efficient of rank correlation from the following data. x= 15 12 14 13 8 7 5. y = 18 6 8 9. 12 7 11 10.
- Assuming the following table of the cost (X) and selling (Y) price of flight tickets in dollars ($): Cost Price (X) Sell Price (Y) 200 300 230 250 500 510 540 700 670 730 320 500 190 412 280 355 625 635 Compute the following: 1. Plot a scatter plot of the data (manual plot or use any software like excel). (2 marks) 2. Pearson correlation coefficient (r). 3. The relation type and strength. 4. Linear regression formula (9, = Bo +B,X,). 5. The estimated of the ticket selling price when the cost is $500. 6. The error of the ticket selling price estimate when the cost is $500. 7. What is the percent of cost price variable interpret the variation of sell price variable (How much the coefficient of determination)? (2 marks) (Imark) (2 marks) (I mark) (I mark) (I mark)2. For this question use the following set of data points. Use Excel's CORREL function to find the value of the correlation coefficient. 1 1 2 2 3 3 3 10 1 2 3 1 3 1 2 3 10 (a) Obtain a scatter plot of the 10 data points. (b) Find the value of the correlation coefficient for the 10 data points. (c) Use Excel with a = 0.05 to determine if there is a linear correlation. Now remove the point with coordinates (10, 10) so there are 9 pairs of points. (d) Obtain a scatter plot of the 9 data points. (e) Find the value of the correlation coefficient for the 9 data points. (f) Use Excel with a = 0.05 to determine if there is a linear correlation. (g) What conclusion do you make about the possible effect of a single pair of values?13.
- Calculate Coefficient of Correlation from the following data: 0.1 0.2 0.3 0.4 0.5 0.6 0.7 y 30,000 50,000 60.000 80,000 1.00,000 1,10,000 1.30,000After 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 correlationThis is a continuation of the last question I posted: f. The value of linear correlation coefficient r is i. 0.948 ii. 0.974 iii. -0.948 iv. -0.974 g.Based on your answer in part (f), the linear dependance between weekly exercise time and change in cholesterol level is strong negative i. True ii. False H. When weekly exercise time is 460 minutes (approximately 66 minutes per day), the 95 percent confidence interval for change in cholesterol level is (197.3, 225.4). This means that: i. If one person exercises 460 minutes per week, his/hers change in cholesterol level will be between 197.3 and 225.4 with 95 percent certainty.ii. If several people exercise 460 minutes per week, their average change in choles- terol level will be between 197.3 and 225.4 with 95 percent certainty. I. When weekly exercise time is 460 minutes (approximately 66 minutes per day), the 95 percent prediction interval for change in cholesterol level is (155.1, 267.6). This means that i. If one person…
