From 8 observations the following results were obtained ΣXΣ =544, ΣY =552, ΣXY = 37560, ΣX^2 =37028, ΣY^2 =38132. Find i) the correlation co- efficient, ii) and, state the relationship, iii) the regression line equation = Y=mX+bY=mX+b

From 8 observations the following results were obtained ΣXΣ =544, ΣY =552, ΣXY = 37560, ΣX^2 =37028, ΣY^2 =38132. Find i) the correlation co- efficient, ii) and, state the relationship, iii) the regression line equation = Y=mX+bY=mX+b

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

See similar textbooks

Similar questions

For 40 eruptions of the Old Faithful geyser in Yellowstone National Park, duration times (sec) were recorded along with the heights (ft) of the eruptions. The linear correlation coefficient is r = 0.0915 and the regression equation is = 119 + 0.0331x, where x represents duration time. The mean of the 40 duration times is 245.0 sec and the mean of the 40 heights is 127.2 ft. What is the best predicted height of an eruption with a duration time of 120 min?
Suppose the entering freshmen at a certain college have a mean combined SAT score of 1231 with a standard deviation of 122 In the first semester, these students attained a mean GPA of 2.64, with a standard deviation of 0.53. A scatterplot showed the association to be reasonably linear, and the correlation between SAT score and GPA was 0.47 How do i find the regression line using the equation
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+b1x�^=�0+�1�, 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 1 2 3 3.5 4 4.5 5 Midterm Grades 60 66 73 76 78 84 90 Table Copy Data Step 1 of 6: Find the estimated slope. Round your answer to three decimal places.
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+b1x�^=�0+�1�, 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 11 1.51.5 2.52.5 33 44 4.54.5 55 Midterm Grades 6666 6969 7575 7979 9090 9595 9898 Find the estimated slope. Round your answer to three decimal places. Find the estimated y-intercept. Round your answer to three decimal places. Determine if the statement "Not all points predicted by the linear model fall on the same line" is true or false.…
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+b1x�^=�0+�1�, 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 1 2 3 3.5 4 4.5 5 Midterm Grades 60 66 73 76 78 84 90 Step 2 of 6: Find the estimated y-intercept. Round your answer to three decimal places. Step 3 of 6: Find the estimated value of y when x=2�=2. Round your answer to three decimal places. Step 4 of 6: Substitute the values you found in steps 1 and 2 into the equation for the regression line to find the estimated…
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. ^y=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 3 4 5 6 Midterm Grades 60 81 86 98 100 Find the error prediction when x= 5. Round your answer to three decimal places. * What we know: Estimated slope b1=9.700Estimated intercept b0=46.200
The table below gives the number of hours ten randomly selected students spent studying and their corresponding midterm exam grades. Using this data, consider the equation of the regression line, yˆ=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 0.5 1.5 2 2.5 3 4.5 5 5.5 6 Midterms Grades 60 63 64 69 73 76 82 90 91 95 Step 1 of 6: Find the estimated slope. Round your answer to three decimal places. Step 2 of 6: Find the estimated y-intercept. Round your answer to three decimal places. Step 3 of 6: Determine if the statement "All points predicted by the linear model fall on the same line" is true or false Step 4 of 6:…
The table below gives the number of hours ten randomly selected students spent studying and their corresponding midterm exam grades. Using this data, consider the equation of the regression line, y^=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 2 2.5 3 3.5 4 4.5 5.5 6 Midterm Grades 61 64 65 66 71 79 84 88 94 98 Summation Table x y xy x2 y2 Student 1 0.0 61 0.0 0.00 3721 Student 2 1.0 64 64.0 1.00 4096 Student 3 2.0 65 130.0 4.00 4225 Student 4 2.5 66 165.0 6.25 4356 Student 5 3.0 71 213.0 9.00 5041 Student 6 3.5 79 276.5 12.25 6241 Student 7 4.0 84 336.0 16.00 7056 Student 8 4.5 88 396.0 20.25 7744…
One set of 20 pairs of scores, X and Y values, produces a correlation of r = 0.70. If SSY = 150, calculate the standard error of the estimate for the regression line
The table below gives the number of absences and the overall grade in the class for seven randomly selected students. Based on this data, consider the equation of the regression line, yˆ=b0+b1x�^=�0+�1�, for using the number of absences to predict a student's overall grade in the class. 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. Number of Absences Grade1 3.72 3.33 3.14 2.96 2.47 2.28 1.9
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, y^=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 1 2 4 5 6 Midterm Grades 67 68 70 79 87 Summation Table x y xy x2 y2 Student 1 1 67 67 1 4489 Student 2 2 68 136 4 4624 Student 3 4 70 280 16 4900 Student 4 5 79 395 25 6241 Student 5 6 87 522 36 7569 Sum 18 371 1400 82 27823 Step 1 of 6: Find the estimated slope. Round your answer to three decimal places. Step 2 of 6: Find the estimated y-intercept. Round your…
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+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 0.5 1 1.5 2 3 3.5 4.5 Midterm Grades 63 66 68 72 74 93 94 Table Step 4 of 6 : Determine if the statement "Not all points predicted by the linear model fall on the same line" is true or false.