Question 1
This histogram shows residuals from a simple linear regression:
It appears that:
◦
there is a dependence among the errors.
◦
the mean of the error distribution is not zero.
◦
the error distribution is not normal.
◦
the error variance is not constant.
Question 2
We record the amount of time (x in minutes) per day that a group of 12 high school students spend using their cell phone (texting, talking, and web use). We also record the overall GPA (y) of each student. Following a regression summary for these data:
The regression equation is
GPA = 4.01 - 0.0153 CellTime
Predictor Coef SE Coef T P
Constant 4.0084 0.2486 6.12 0.000
CellTime -0.015334 0.003226 -4.75 0.001
S = 0.472864 R-Sq = 69.3% R-Sq(adj) = 66.3%
Analysis of Variance
Source DF SS MS F P
Regression 1 5.0519 5.0519 22.59 0.001
Residual Error 10 2.2360 0.2236
Total 11 7.2879
Does there appear to be a significant linear relationship between theamount of cell phone use and GPA? (Use α = 0.01.)
◦
No, because ther2value is too low.
◦
Yes, because the regression equation is defined.
◦
Yes, because thep-value from the test for significance is 0.000.
◦
Yes, because thep-value from the test for significance is 0.001.
The principle of faunal succession uses animal fossils to tell relative time.
Deconvolution fluorescence microscopy yields high-resolution optical sections th
Elizabeth Murray, Just in Time.
The microchip is transforming our lives—the way we shop, spend our leisure, relate to one another, ...
Insecticide application over time
The percentage of Canadian students in Grades 7 through 12 who used drugs