In: Statistics and Probability
A professor notices that more and more students are using their notebook computers in class, presumably to take notes. He wonders if this may actually improve academic success. To test this, the professor records the number of times each student uses his or her computer during a class for one semester and the final grade in the class (out of 100 points). If notebook computer use during class is related to improved academic success, then a positive correlation should be evident. Given the following data, test whether notebook computer use and grades are related at a .05 level of significance.
State the conclusions for this test using APA format. First, describe the correlation coefficient in words and give the value of r. Then give the value of R2 and describe (in words) the effect size using the coefficient of determination. Finally, is there a significant relationship?
The hypothesis being tested is:
H0: ρ = 0
Ha: ρ ≠ 0
Pearson's r is -0.140.
The critical r-value is 0.404.
Since 0.140 < 0.404, we cannot reject the null hypothesis.
Therefore, we cannot conclude that notebook computer use and grades are related.
Pearson's r is-0.140. It means that there is a weak negative relationship between notebook computer use and grades.
The coefficient of determination is 0.020. 2% of the variation in the model is explained.
The relationship is not significant.
Notebook Computer Use | Final Grade for Course | |||||
30 | 86 | |||||
23 | 88 | |||||
6 | 94 | |||||
0 | 56 | |||||
24 | 78 | |||||
36 | 72 | |||||
10 | 80 | |||||
0 | 90 | |||||
0 | 82 | |||||
8 | 60 | |||||
12 | 84 | |||||
18 | 74 | |||||
0 | 78 | |||||
32 | 66 | |||||
36 | 54 | |||||
12 | 98 | |||||
8 | 81 | |||||
18 | 74 | |||||
22 | 70 | |||||
38 | 90 | |||||
5 | 85 | |||||
29 | 93 | |||||
26 | 67 | |||||
10 | 80 | |||||
r² | 0.020 | |||||
r | -0.140 | |||||
Std. Error | 11.996 | |||||
n | 24 | |||||
k | 1 | |||||
Dep. Var. | Final Grade for Course | |||||
ANOVA table | ||||||
Source | SS | df | MS | F | p-value | |
Regression | 63.6652 | 1 | 63.6652 | 0.44 | .5129 | |
Residual | 3,165.668 | 22 | 143.8940 | |||
Total | 3,229.333 | 23 | ||||
Regression output | confidence interval | |||||
variables | coefficients | std. error | t (df=22) | p-value | 95% lower | 95% upper |
Intercept | 80.5590 | |||||
Notebook Computer Use | -0.1325 | 0.1993 | -0.665 | .5129 | -0.5458 | 0.2807 |