Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Find the regression equation, letting the fight arm blood pressure be the predictor (x) variable. Find the best predicted systolic blood pressure in the left arm given that the systolic blood pressure in the right arm is 90 mm Hg. Use a significance level of 0.05. Right Arm 101 94 80 Left Arm 177 172 143 143 143 Click the icon to view the critical values of the Pearson correlation coefficient r 102 The regression equation is y=+_x. (Round to one decimal place as needed.) Given that the systolic blood pressure in the right arm is 90 mm Hg, the best predicted systolic blood pressure in the left arm is mm Hg. (Round to one decimal place as needed) 1 79 mim √ Vi 1. More X

The slope of a regression line=-6.879 How do you interpret the slope? Is it significant?

Plot X & Y axis as a scatter plot and describe the plotted data. Calculation (no changes here): Does increased rainfall correlated to higher crop yield? If you were testing for significance, state the null hypothesis and alternative hypothesis you were testing for both correlation and regression. List three factors that contributes to your conclusion. Thanks

Using your favorite statistics software package, you generate a scatter plot with a regression equation and correlation coefficient. The regression equation is reported asˆy=−29.73x+47.69 and the r=−0.588What proportion of the variation in y can be explained by the variation in the values of x?Report answer as a percentage accurate to one decimal place.

The data show systolic and diastolic blood pressure of certain people. Find the regression equation, letting the systolic reading be the independent (x) variable. If one of these people has a systolic blood pressure of 125 mm Hg, what is the best predicted diastolic blood pressure? Systolic Diastolic Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? ŷ-+x (Round to two decimal places as needed.) What is the best predicted diastolic blood pressure? y=(Round to one decimal place as needed.) C 148 115 82 83 82 136 115 127 128 140 97 60 65 93 145 101 108

A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of sit-ups a person can do (y). The results of the regression were: y=ax+b a=-1.019 b=39.062 R squared = 0.931225 R= 0.965

Does how long young children remain at the lunch table help predict how much they eat? Twenty toddlers were observed over several months at a nursery school. "Time" is the average number of minutes a child spent at the table when lunch was served. "Calories" is the average number of calories the child consumed during lunch, calculated from careful observation of what the child ate each day. A regression was run and the results were: = 114 + 2.4*x R² = 0.68 r = 0.822 Predict the number of calories a toddler consumes who remains at the table for 14.5 minutes (round your answer to two decimal places)

Use the value of the linear correlation coefficient to calculate the coefficient of determination. What does this tell you about the explained variation of the data about the regression​ line? About the unexplained​ variation? r= -0.438   please dont copy content from other sources

Listed below are systolic blood pressure measurements (in mm H) obtained from the same woman. Find the regression equation, letting the fight arm blood pressure be the predictor (x) variable, Find the best predicted systolic blood pressure in the left arm given that the systolic blood pressure in the right arm is 90 mm Hg. Use a significance level of 0.05. Right Arm 100 99 93 76 77 9 Left Arm 176 169 118 145 146 EB Click the icon to view the critical values of the Pearson correlation coefficient r The regression equation is 9 = 7 + 7x (Round to one decimal place as needed.) Given that the systolic blood pressure in the right arm is 90 mm Hq, the best predicted systolic blood pressure in the left arm is mm Hg. (Round to one decimal place as needed.)

Save The data show the bug chirps per minute at different temperatures. Find the regression equation, letting the first variable be the independent (x) variable. Find the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute. Use a significance level of 0.05. What is wrong with this predicted value? Chirps in 1 min 776 1173 1034 951 975 1214 D Temperature (°F) 70.1 89 77.4 76.2 77 92.6 What is the regression equation? (Round the x-coefficient to four decimal places as needed. Round the constant to two decimal places as needed.) Incorrec ary ns