The following data represent the results from an independent-measures study comparing two treatment conditions. Treatment I II 10 7 N = 16 8 4 G = 120 7 9 ∑X² = 1036 9 3 13 7 7 6 6 10 12 2 M = 9.000 M = 6.000 T = 72 T = 48 SS = 44 SS = 56 Use an independent-measures t test with α = .05 to determine whether there is a significant mean difference between the two treatments. (Use three decimal places; subtract MIIII from MII.) t-critical = ± t = t Distribution Degrees of Freedom = 21 -3.0-2.0-1.00.01.02.03.0t Conclusion: Fail to reject the null hypothesis; there are significant differences between the two treatments. Reject the null hypothesis; there are significant differences between the two treatments. Fail to reject the null hypothesis; there are no significant differences between the two treatments. Reject the null hypothesis; there are no significant differences between the two treatments. Use an ANOVA with α = .05 to determine whether there is a significant mean difference between the two treatments. You should find that F = t². (Round to two decimal places where needed.) Source SS df MS F Fcriticalcritical Between treatments Within treatments Total F Distribution Numerator Degrees of Freedom = 6 Denominator Degrees of Freedom = 16 0.01.02.03.04.05.06.07.08.09.010.011.012.0F Conclusion: Reject the null hypothesis; there are significant differences among the three treatments. Reject the null hypothesis; there are no significant differences among the three treatments. Fail to reject the null hypothesis; there are no significant differences among the three treatments. Fail to reject the null hypothesis; there are significant differences among the three treatments.
The following data represent the results from an independent-measures study comparing two treatment conditions. Treatment I II 10 7 N = 16 8 4 G = 120 7 9 ∑X² = 1036 9 3 13 7 7 6 6 10 12 2 M = 9.000 M = 6.000 T = 72 T = 48 SS = 44 SS = 56 Use an independent-measures t test with α = .05 to determine whether there is a significant mean difference between the two treatments. (Use three decimal places; subtract MIIII from MII.) t-critical = ± t = t Distribution Degrees of Freedom = 21 -3.0-2.0-1.00.01.02.03.0t Conclusion: Fail to reject the null hypothesis; there are significant differences between the two treatments. Reject the null hypothesis; there are significant differences between the two treatments. Fail to reject the null hypothesis; there are no significant differences between the two treatments. Reject the null hypothesis; there are no significant differences between the two treatments. Use an ANOVA with α = .05 to determine whether there is a significant mean difference between the two treatments. You should find that F = t². (Round to two decimal places where needed.) Source SS df MS F Fcriticalcritical Between treatments Within treatments Total F Distribution Numerator Degrees of Freedom = 6 Denominator Degrees of Freedom = 16 0.01.02.03.04.05.06.07.08.09.010.011.012.0F Conclusion: Reject the null hypothesis; there are significant differences among the three treatments. Reject the null hypothesis; there are no significant differences among the three treatments. Fail to reject the null hypothesis; there are no significant differences among the three treatments. Fail to reject the null hypothesis; there are significant differences among the three treatments.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
The following data represent the results from an independent-measures study comparing two treatment conditions.
Treatment
|
|
|
---|---|---|
I
|
II
|
|
10 | 7 | N = 16 |
8 | 4 | G = 120 |
7 | 9 | ∑X² = 1036 |
9 | 3 | |
13 | 7 | |
7 | 6 | |
6 | 10 | |
12 | 2 | |
M = 9.000 | M = 6.000 | |
T = 72 | T = 48 | |
SS = 44 | SS = 56 |
Use an independent-measures t test with α = .05 to determine whether there is a significant mean difference between the two treatments. (Use three decimal places; subtract MIIII from MII.)
t-critical | = | ±
|
t | = |
|
t Distribution
Degrees of Freedom = 21
-3.0-2.0-1.00.01.02.03.0t
Conclusion:
Fail to reject the null hypothesis; there are significant differences between the two treatments.
Reject the null hypothesis; there are significant differences between the two treatments.
Fail to reject the null hypothesis; there are no significant differences between the two treatments.
Reject the null hypothesis; there are no significant differences between the two treatments.
Use an ANOVA with α = .05 to determine whether there is a significant mean difference between the two treatments. You should find that F = t². (Round to two decimal places where needed.)
Source
|
SS
|
df
|
MS
|
F
|
Fcriticalcritical
|
---|---|---|---|---|---|
Between treatments |
|
|
|
|
|
Within treatments |
|
|
|
||
Total |
|
|
F Distribution
Numerator Degrees of Freedom = 6
Denominator Degrees of Freedom = 16
0.01.02.03.04.05.06.07.08.09.010.011.012.0F
Conclusion:
Reject the null hypothesis; there are significant differences among the three treatments.
Reject the null hypothesis; there are no significant differences among the three treatments.
Fail to reject the null hypothesis; there are no significant differences among the three treatments.
Fail to reject the null hypothesis; there are significant differences among the three treatments.
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