Question

The authors used a more advanced statistical method than is covered by this course, however, you can apply what you know about hypotheses and statistical tests to understand their approach. Present hypotheses and conduct the appropriate statistical test to assess if the intervention and control groups differed in their Trail Making Test B results at follow-up (see Table 2). Comment on whether the conditions were met for using the selected test, include the StatCrunch output, and interpret your results in context.

Table 2: Self-reported and measured heights of UIC Students
ID	Self-Reported	Measured
1.	68	67.9
2.	71	69.9
3.	63	64.9
4.	70	68.3
5.	71	70.3
6.	60	60.6
7.	65	64.5
8.	64	67.0
9.	54	55.6
10.	63	74.2
11.	66	65.0
12.	72	70.8
13.	66	64.8
14.	68	67.6
15.	64	62.1
16.	56	56.8
17.	57	57.3
18.	58	59
19.	54	54
20.	53	52.2
21.	52	51
22.	61	61.4
23.	62	63
24.	62	61.2
25.	60	59.4
26.	59	57.5
27.	58	59
28.	57	57.3
29.	53	51.8
30.	57	56.5
31.	66	64
32.	72	70.8
33.	66	64
34.	68	67
35.	64	62
36.	56	56.8
37.	57	55
38.	58	59
39.	54	54
40.	53	52.2

Answer 1

we use t-test (paired)

t-Test: Paired Two Sample for Means
	Self-Reported	Measured
Mean	61.45	61.3925
Variance	35.43333333	36.85096795
Observations	40	40
Pearson Correlation	0.934691299
Hypothesized Mean Difference	0
df	39
t Stat	0.167145011
P(T<=t) one-tail	0.434059806
t Critical one-tail	1.684875122
P(T<=t) two-tail	0.868119612
t Critical two-tail	2.02269092

p-value for 2-tailed = 0.8681

p-value > 0.05 (alpha)

we fail to reject the null hypothesis

there is not significant evidence that intervention and control groups differed in their Trail Making Test B