Suppose that you run a correlation and find the correlation coefficient is -0.346 and the regression equation is ˆy=−6.5x+65.65y^=-6.5x+65.65. The mean of your x-data was 6.9 and the mean of your y-data was 20.9. If the critical value is .606, use the appropriate method to predict the y value when x is 5.3
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If the critical value is .606, use the appropriate method to predict the y value when x is 5.3
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- The table below gives the number of hours seven randomly selected students spent studying and their corresponding midterm exam grades. Using this data, consider the equation of the regression line, yˆ=b0+b1xy^=b0+b1x, for predicting the midterm exam grade that a student will earn based on the number of hours spent studying. 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. Hours Studying 2 2.5 3 3.5 4 4.5 5 Midterm Grades 72 74 80 82 87 88 93 Find the value of the coefficient of determination. Round your answer to three decimal places.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, yˆ=b0+b1xy^=b0+b1x, 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. Hours Unsupervised 00 11 1.51.5 22 2.52.5 44 4.54.5 Overall Grades 9797 9393 8585 7474 7272 7171 6666 Step 2 of 6 : Find the estimated y-intercept. Round your answer to three decimal places.Suppose that you run a correlation and find the correlation coefficient is 0.338 and the regression equation is ˆy=−12.7+4.3xy^=-12.7+4.3x.The mean for the xx data values was 7, and the mean for the y data values was 17.A T Test for the slope of the regression line is performed, and the p-value is greater than the level of significance of 0.05. Use the appropriate method to predict the y value when x is 4.4.
- The table below gives the number of hours five randomly selected students spent studying and their corresponding midterm exam grades. Using this data, consider the equation of the regression line, yˆ=b0+b1xy^=b0+b1x, for predicting the midterm exam grade that a student will earn based on the number of hours spent studying. 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. hours studying 0 1 3 4 5 grades 63 65 80 81 87 Find the value of the coefficient of determination. Round your answer to three decimal places.Using your favorite statistics software package, you generate a scatter plot with a regression equation and correlation coefficient. The regression equation is reported asˆy=−28.33x+68.73y^=-28.33x+68.73and the r=−0.014r=-0.014.What proportion of the variation in y can be explained by the variation in the values of x?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^=b0+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. Find the estimated value of y when x=52. Round your answer to three decimal places. age 35 41 52 56 66 bone density 358 350 348 332 321
- Complete the missing information for this regression model. Note: N=26N=26. (Except for P-values, report all values accurate to 3 decimal places. For P-values, report accurate to 4 decimal places.) ˆYY^ = 26.759 + 0.818X10.818X1 −- 2.999X22.999X2 + X3X3 2.382 0.547 1.674 0.734 Standard Errors 11.234 1.495 t-ratios 0.0991 P-valuesThe table below gives the number of hours seven randomly selected students spent studying and their corresponding midterm exam grades. Using this data, consider the equation of the regression line, yˆ=b0+b1xy^=b0+b1x, for predicting the midterm exam grade that a student will earn based on the number of hours spent studying. 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. Hours Studying 2 2.5 3 3.5 4 4.5 5 Midterm Grades 72 74 80 82 87 88 93 Find the estimated slope. Round your answer to three decimal places.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, yˆ=b0+b1xy^=b0+b1x, 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. Hours Unsupervised 00 0.50.5 11 1.51.5 22 3.53.5 44 Overall Grades 8989 8181 7373 7272 6969 6767 6363 Table Copy Data Step 6 of 6: Find the value of the coefficient of determination. Round your answer to three decimal places.
- 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, yˆ=b0+b1xy^=b0+b1x, 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. Hours Unsupervised 1.51.5 2.52.5 33 44 4.54.5 55 66 Overall Grades 9494 9292 8282 7979 7171 7070 6262 Find the value of the coefficient of determination. Round your answer to three decimal places.A researcher found a linear correlation between course grades and the average number of hours spent on a mobile phone each day. The line of best fit has equation y ^ = 3.7 − 0.786 x with correlation coefficient r = − 0.84. a. Does this prove that spending too much time on a phone causes students to get lower grades? b. What does the regression line predict your final grade in a course will be if you spend an average of 150 minutes per day on your phone?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, yˆ=b0+b1x�^=�0+�1�, 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. Hours Unsupervised 00 11 1.51.5 22 2.52.5 44 4.54.5 Overall Grades 9797 9393 8585 7474 7272 7171 6666 Table Copy Data Step 1 of 6 : Find the estimated slope. Round your answer to three decimal places.
