Problem 1: Reaction Time Analysis
Problem Description:
The Jamovi assignment involves analyzing reaction time data from 20 participants using jamovi. The tasks include creating a jamovi spreadsheet, calculating z-scores, and answering specific questions based on the results.
Participant ID# |
Reaction Time (ms) |
---|---|
101 | 416 |
102 | 332 |
103 | 375 |
104 | 470 |
105 | 421 |
106 | 341 |
107 | 1262 |
108 | 359 |
109 | 396 |
110 | 392 |
111 | 431 |
112 | 464 |
113 | 496 |
114 | 438 |
115 | 493 |
116 | 1015 |
117 | 440 |
118 | 375 |
119 | 460 |
120 | 472 |
Table 1: Jamovi spreadsheet for participant ID and Reaction time
Solution: To analyze the data, a jamovi spreadsheet was created, and z-scores for reaction times were calculated. The following are the results:
a) Participant Closest to Mean:
- Answer: Participant 115 had a reaction time closest to the sample mean, with a z-score of 0.003.
b) Participants within ±0.5 Standard Deviations:
- Answer: 14 participants had reaction times within ±0.5 standard deviations of the sample mean.
c) Identifying Outliers:
- Answer: Participant 107, with a z-score of 3.351, would be removed as an outlier.
Problem 2: PE Class Jumping Distance
Problem Description:
Students' jumping distances at the beginning and end of the semester are analyzed. Questions involve hypothesis testing and result interpretation.
Student ID | First Week | Last Week |
---|---|---|
001 | 3 | 5 |
002 | 4 | 3 |
003 | 4 | 4 |
004 | 2 | 4 |
005 | 3 | 4 |
006 | 3 | 5 |
007 | 2 | 4 |
008 | 4 | 5 |
009 | 2 | 5 |
010 | 3 | 3 |
Table 2: A weekly testing for student’s jumping distance
Solution:
a) Rejecting Null Hypothesis:
- Answer: The null hypothesis of no change would be rejected as the difference in jumping distance is statistically significant at the 5% level.
b) Results Statement:
- Answer: A paired sample t-test showed significant improvement (t(9) = 3.1, p = .01, d = 0.2) in jumping distance over the semester.
c) Plain Explanation:
- Answer: On average, students jumped significantly farther in the last week compared to the first week, indicating improvement.
Problem 3:Dark Chocolate and Diet
Problem Description:
The effects of dark chocolate on a diet plan are investigated using an independent sample t-test.
Diet | Diet + Chocolate |
---|---|
2 | 3 |
3 | 3 |
2 | 5 |
4 | 4 |
3 | 2 |
3 | 3 |
2 | 4 |
4 | 4 |
1 | 3 |
2 | 2 |
Table 3: The number of pounds each group lost at the end of the study.
Solution:
a) Rejecting Null Hypothesis:
- Answer: The null hypothesis is not rejected as the difference in weight loss is not significant (p = .1).
b) Results Statement:
- Answer: The t-test result (t = -1.6, p = .12, d = -0.7) indicates no significant effect of dark chocolate on weight loss.
c) Simple Explanation:
- Answer: Dark chocolate did not significantly impact weight loss; both groups showed similar results.
Problem 4: Journal Article Analysis
Selected Article: a) [Brustkern, J., Heinrichs, M., Walker, M. et al. Facial threat affects trust more strongly than facial attractiveness in women than it does in men. Sci Rep 11, 22475 (2021).
b) Description:
- Answer: The study explores the sex-specific effects of facial attractiveness and threat on trust. The t-test (t(91) = 1.415, p = 0.161) found no significant differences.
c) Appropriateness of T-Test:
- Answer: An independent samples t-test was appropriate for comparing two independent groups (men and women).
d) Assumptions:
- Answer: The paper did not explicitly report the test of normal distribution.
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