The statistical software output for this problem is:
Simple linear regression results:
Dependent Variable: Overall grades
Independent Variable: Hours
Overall grades = 66.333333 + 9.3333333 Hours
Sample size: 5
R (correlation coefficient) = 0.77331545
R-sq = 0.59801678
Estimate of error standard deviation: 10.821789
Parameter estimates:
Parameter | Estimate | Std. Err. | Alternative | DF | T-Stat | P-value |
---|---|---|---|---|---|---|
Intercept | 66.333333 | 10.074537 | ? 0 | 3 | 6.5842562 | 0.0071 |
Slope | 9.3333333 | 4.4179767 | ? 0 | 3 | 2.1125809 | 0.1251 |
Analysis of variance table for regression
model:
Source | DF | SS | MS | F-stat | P-value |
---|---|---|---|---|---|
Model | 1 | 522.66667 | 522.66667 | 4.4629981 | 0.1251 |
Error | 3 | 351.33333 | 117.11111 | ||
Total | 4 | 874 |
Hence,
Step - 1: SSE = 351.333
Step - 2: Estimated error variance = 117.111
Step - 3: Estimated variance of slope = 19.519
Step - 4: 98% confidence interval: (-10.727, 29.394)
Step - 5: 95% confidence interval: (-4.727, 23.393)
The following table gives the average number of hours 5 junior high students were left unsupervised...
12. The following table gives the average number of hours 6 junior high students were left unsupervised each day and their corresponding grade averages. (6 points) Hours unsupervised 02 3 4 5 Overall grade average l 91 | 94 | 87 | 85 | 80 74 a) Provide a scatterplot of this data. Be sure to label both axes. b) Interpret the strength and direction of the linear relationship between the two variables. o) Suppose a similar sample of junior...
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.ỹ = 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...
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. 9 = b + b x. 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....
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, y - bo t bix. 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,...
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. y = 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,...
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. Ĵ = bo+byx, 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,...
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, 9 = bi + 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,...
The table below gives the number of hours spent unsupervised each day as we'll as the overall grade averages for seven randomly selected middle school students. uising this data. consider the equation of the regression line. by by, for predicting the overall grade average for a middle school student based on the number of hours spent unsupervised each day. Keep in mind he correlation coefficient may or may not be statistica y s rificant for the data ven. Remember, in...
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, y =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...
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, 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...