The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 63 inches. Is the result close to the actual weight of 462 pounds? Use a significance level of 0.05. Chest size (inches) Weight (pounds) E Click the icon to view the critical values of the Pearson correlation coefficient r. 58 50 65 59 499 59 48 O 414 312 450 456 260 What is the regression equation? y=+x (Round to one decimal place as needed.) What is the best predicted weight of a bear with chest size of 63 inches? The best predicted weight for a bear with a chest size of 63 inches is pounds. (Round to one decimal place as needed.) Is the result close to the actual weight of 462 pounds? O A. This result is very close to the actual weight of the bear. O B. This result is close to the actual weight of the bear. OC. This result is not very close to the actual weight of the bear. O D. This result is exactly the same as the actual weight of the bear.

Use the summary statistics to calculate the regression line for this data. Explain each coefficient. What is the total amount of weight would you expect a weightlifter with a body weight of 84kg to lift? At the 5% significance level, is there evidence that the body weight of the athlete is a useful predictor for the total amount an athlete can lift? Assume the assumptions can be verified.

Select the statistic test that best fits each description. Study examing how much of the variation in blood pressure reading as explained by the variation in test scores       A. T-test independent samples B. T-test dependent samples C. One-way ANOVA D. Correlation E. Simple Regression

a tab = The table below gives the number of hours spent unsupervised each day as well as the overall grade averages for seven randomly selected middle school students. Using this data, consider the equation of the regression line, bo + bx, for predicting the overall grade average for a middle school student based on the number of hours spent unsupervised each day. 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. Answer How to enter your answer (opens in new window) esc Step 3 of 6: Substitute the values you found in steps 1 and 2 into the equation for the regression line to find the estimated linear model. According to this model, if the value of the independent variable is increased by one unit, then find the change in the dependent variable . Google Play Store alt 1…

he data show the chest size and weight of several bears. Find the regression​ equation, letting chest size be the independent​ (x) variable. Then find the best predicted weight of a bear with a chest size of 39inches. Is the result close to the actual weight of 126 ​pounds? Use a significance level of 0.05.   Chest size​ (inches) 44 41 41 55 51 42   Weight​ (pounds) 213 206 176 309 300 178     Critical Values of the Correlation Coefficient r n α=0.05 α=0.01 ​NOTE: To test H0​: ρ=0 against H1: ρ≠​0, reject H0if the absolute value of r is greater than the critical value in the table. 4 0.950 0.990 5 0.878 0.959 6 0.811 0.917 7 0.754 0.875 8 0.707 0.834 9 0.666 0.798 10 0.632 0.765 11 0.602 0.735 12 0.576 0.708 13 0.553 0.684 14 0.532 0.661 15 0.514 0.641 16 0.497 0.623 17 0.482 0.606 18 0.468 0.590 19…

Students Who Major in Business It has been reported that 20.4% of incoming freshmen indicate that they will major in business or a related field. A random sample of 400 incoming college freshmen were asked their preference, and 92 replied that they were considering business as a major. Estimate the true proportion of freshman business majors with 98% confidence. Round intermediate calculations to three decimal places and final answers to one decimal place. % <p< %

Use the value of the linear correlation coefficient r to find the coefficient of determination and the percentage of the total variation that can be explained by the linear relationship between the two variables. r = 0.173 What is the value of the coefficient of determination? 2 = (Round to four decimal places as needed.)

You generate a scatter plot using Excel. You then have Excel plot the trend line and report the equation and the r2r2 value. The regression equation is reported asy=55.82x+32.43y=55.82x+32.43and the r2=0.3136r2=0.3136.What is the correlation coefficient for this data set?r =

use the sample data to construct a scatterplot. Use the first variable for the x-axis. Based on the scatterplot, what do you conclude about a linear correlation? FORECAST AND ACTUAL TEMPERATURES The table lists actual high temperatures and the high temperatures that were previously forecasted for these same days. The table includes data for ten different days near the author’s home. What does the result suggest about the accuracy of five-day predicted high temperatures?

You generate a scatter plot using Excel. You then have Excel plot the trend line and report the equation and the r value. The regression equation is reported as y = 75.56z + 78.71 and the r = 0.2209. What is the correlation coefficient for this data set?