At a large Australian university, the coordinator ofDesigning Experiments and Analysing Results wanted to know if student performance in the unit was equivalent across the three campuses where the subject was taught. There was one class at each campus, each with 25 students. Classes at the Fundsborough and Sans Souci campuses were held on a Monday. The class at Monarch's Grove is held on a Thursday.

To find out how the students are performing, the coordinator gives the students a surprise quiz on the subject content that had been covered in the previous week's class. The quiz was scored out of 100.

Compare the students' marks to determine whether there are any differences in performance across the three classes. The data are provided in Table 3.

(2) What is the name of the statistical analysis you used?1 mark

(3) What is thestandard deviation of theage of female and males at the Monarch's Grove campus? 1 mark

Male =

Female =

(4) Which (if any) participant was an outlier? (Provide their ID number, or write "no outlier" if you didn't identify anyone. Remember to check for outliers separately for each group). 2 marks

(5) Was the assumption of normality met forall three groups? (Yes/No/Not applicable).1 mark

(10) Was an overall difference found between the three campuses? 1 mark

(11) If there was an overall difference, the marks of students from which campus(es) differed from the others? Say what test used to determine the differences and explain why you chose that test. (write "Not applicable" if no differences were found).2 marks

Circle the number next to the statement which most accurately summarises the research findings.2 marks

(1) There was a significant difference in the marks between the three campuses.

(2) There was no significant difference in the marks between the three campuses.

(3) It was not possible to run the analysis because the assumptions of the test were violated.

(4) Not enough information provided to determine an answer.

TASK 3

You've mistakenly allowed an obvious design flaw to potentially affect the validity of your results. What is it? (write a short phrase or simple sentence only; for example, "lack of reliability" or "experimenter effect"). 3 marks

Table 3

ID	Sex	Age	Campus	Mark	ID	Sex	Age	Campus	Mark
1	M	19	1	50	26	F	19	2	64
2	F	46	1	80	27	F	20	2	80
3	M	20	1	74	28	M	27	2	71
4	F	19	1	55	29	F	19	2	85
5	F	20	1	54	30	M	20	2	61
6	F	20	1	65	31	F	19	2	77
7	F	21	1	53	32	F	20	2	32
8	F	32	1	87	33	M	19	2	87
9	M	19	1	70	34	M	19	2	87
10	F	25	1	64	35	F	19	2	59
11	F	19	1	72	36	M	19	2	59
12	F	22	1	77	37	F	22	2	64
13	M	19	1	57	38	M	19	2	83
14	F	20	1	59	39	F	19	2	69
15	F	19	1	51	40	M	20	2	78
16	M	19	1	67	41	M	19	2	71
17	M	19	1	65	42	F	20	2	65
18	M	20	1	58	43	M	20	2	60
19	M	19	1	56	44	F	21	2	69
20	M	20	1	75	45	M	18	2	53
21	F	20	1	67	46	F	19	2	71
22	M	19	1	65	47	F	19	2	84
23	M	20	1	84	48	M	20	2	64
24	F	19	1	67	49	F	19	2	69
25	M	19	1	61	50	M	19	2	84

ID	Sex	Age	Campus	Mark
51	F	19	3	55
52	F	18	3	92
53	F	18	3	85
54	F	19	3	62
55	F	20	3	59
56	F	19	3	73
57	F	19	3	59
58	F	18	3	95
59	M	19	3	79
60	F	20	3	73
61	M	19	3	82
62	F	18	3	89
63	F	18	3	64
64	F	18	3	66
65	F	19	3	57
66	F	19	3	76
67	F	19	3	73
68	F	18	3	64
69	F	18	3	62
70	F	18	3	86
71	F	18	3	76
72	F	19	3	74
73	F	19	3	97
74	F	19	3	77
75	M	19	3	69