The regression equation is Ý = 29.29 – 0.72X, the sample size is 8, and the standard error of the slope is 0.22. What is the the slope? Multiple Cholce z=-3.273
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- The regression line for the given data is = 6.91x + 46.26. Determine the residual of a data point for which x = 4 and y = 75.The best predicted circumference for a diameter 1.2 cm is?I’m taking a statistics and probability class. Please get this correct because I want to learn. I have gotten wrong answers on here before
- Find the regression equation, letting overhead width be the predictor (x) variable. Find the best predicted weight of a seal if the overhead width measured from a photograph is 2.3 cm. Can the prediction be correct? What is wrong with predicting the weight in this case? Use a significance level of 0.05. Overhead Width (cm) Weight (kg) 7.8 175 7.3 9.5 274 7.4 156 9.9 294 9.2 183 256 Click the icon to view the critical values of the Pearson correlation coefficient r. ..... The regression equation is y =+x. (Round to one decimal place as needed.)Using your favorite statistic software package, you generate a scatter plot with a regression equation and correlation coefficient. The regression equation is reported as y = - 10.71 x + 65.32 and the r = 0.044. What proportion of the variation in y can be explained by the variation in the values of x? r^2 = % % to one decimalListed below are the overhead widths (cm) of seals measured from photographs and weights (kg) of the seals. Find the regression equation, letting the overhead width be the predictor (x) variable. Find the best predicted weight of a seal if the overhead width measured from a photograph is 1.8 cm, using the regression equation. Can the prediction be correct? If not, what is wrong? Use a significance level of 0.05. Overhead Width (cm) 7.3 7.4 9.8 9.5 8.8 8.5 Weight (kg) 152 187 286 247 237 231 The regression equation is y =+ (x. (Round the y-intercept to the nearest integer as needed. Round the slope to one decimal place as needed.)
- The regression equation is: ŷ = 67.16 + 8.417x where ŷ is the miles traveled, and x is the MPG. The sample size used was all 110 MPG records. The correlation coefficient r = 0.620. Use the information to obtain an estimate of my mileage if my MPG is 22. Is it option: a.) cannot estimate ŷ rcrit = 0.195; the correlation IS NOT significant b.) ŷ = 252.33 rcrit = 0.195; the correlation IS significant c.) ŷ = 252.33 rcrit = 0.187; the correlation IS significant d.) cannot estimate ŷ rcrit = 0.187; the correlation IS NOT significantFind the regression equation, letting the diameter be the predictor (x) variable. Find the best predicted circumference of a beachball with a diameter of 44.4 cm. How does the result compare to the actual circumference of 139.5 cm? Use a significance level of 0.05. Baseball Basketball Golf Soccer Tennis Ping-Pong Volleyball Diameter 7.3 23.8 4.2 22.3 7.1 4.0 21.2 Circumference 22.9 74.8 13.2 70.1 22.3 12.6 66.6 LOADING... Click the icon to view the critical values of the Pearson correlation coefficient r.Find the regression equation, letting the diameter be the predictor (x) variable. Find the best predicted circumference of a marble with a diameter of 1.9 cm. How does the result compare to the actual circumference of 6.0 cm? Use a significance level of 0.05. Baseball Basketball Golf Soccer Tennis Ping-Pong Volleyball 5 Diameter 7.4 23.6 4.3 21.7 7.1 3.9 21.5 Circumference 23.2 74.1 13.5 68.2 22.3 12.3 67.5
- 2Find the regression equation, letting overhead width be the predictor (x) variable. Find the best predicted weight of a seal if the overhead width measured from a photograph is 2.5 cm. Can the prediction be correct? What is wrong with predicting the weight in this case? Use a significance level of 0.05. Overhead Width (cm) 7.6 7.4 9.8 8.8 9.3 7.3 Weight (kg) 142 163 256 188 231 156 The regression equation is y= + x. (Round to one decimal place as needed.) The best predicted weight for an overhead width of 2.5 cm is kg? (Round to one decimal place as needed.) Can the prediction be correct? What is wrong with predicting the weight in this case? A. The prediction cannot be correct because a negative weight does not make sense. The width in this case is beyond the scope of the available sample data. B. The prediction cannot be correct because a negative weight does not make sense and because there is…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 Bone Density 61 62 68 69 40 357 350 343 340 315 Step 1 of 6: Find the estimated slope. Round your answer to three decimal places. Table Copy Data Next