The table below shows the final marks in Mathematics and English obtained by 10 students selected at random from a large group of students. Math (x) 75 80 93 65 87 71 98 68 84 77  English (y) 82 78 86 72 91 80 95 72 89 74  Obtain the relationship between the final marks in Mathematics and English by correlation coefficient. Draw a scatter diagram for the data given in the table above. 3. Find the equation of regression line.

Research was conducted on the amount of training for 5K and the time a contestant took to run the race. The researcher recorded the number of miles during training ( a 1 month period) and the time to complete the 5K. The results are below. Miles Trained 45 77 37 25 60 64 Time (Minutes) 32.9 28 36.2 27.5 19.5 18.3 a) Give the correlation coefficient. r = b) Give the equation of the regression line. Round the values to 4 deimal places.This is in the form y = ax + b, so the slope goes in the first box and the y-inercept in the 2nd box.y = x + c) Interpret the y-intercept (Explain it's meaning, do not just give its value.)d) Predict the time in the 5K if someone trained 37 miles.Use the rounded values entered for the slope and intercept of the regression line to compute the predicted y-value.y = e) Give the residual for 37 miles trained.This is the actual y value for the runner who trained for miles minus the predicted value.Residual=

< Prev The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, y = bo + b₁x, for predicting a woman's bone density based on her age. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Age 40 61 62 68 69 Bone Density 357 350 343 340 315 Step 6 of 6: Find the value of the coefficient of determination. Round your answer to three decimal places. Table Copy Data Next

A manager wishes to determine the relationship between the number of years the manager's sales representatives have been with the company and their average monthly sales (in thousands of dollars). Calculate the linear correlation coefficient.Years with company, x: 6,7,14,11,12,19,7,5,15Sales, y: 21,23,68,52,55,51,38,45,110