Question 1
(24 marks)
A human-computer interaction (HCI) researcher was interested in examining
whether humans are better able to use a joystick or a mouse to point a computer cursor.
She therefore constructed an experiment in which participants used either a joystick
(joystick condition) or a mouse (mouse condition) to point a cursor to a target displayed on
a computer monitor. She measured the time (seconds) that it took to place the cursor over
the target (dependent variable referred to as time, where a higher time score indicates
poorer performance). To determine whether potential benefits of using the joystick or
mouse generalized to difficult HCI scenarios, the target was either stationary (static
condition) or moved slowly across the computer screen at a constant velocity (motion
condition). Participants were randomly and uniquely assigned to 1 of 4 conditions in the
interface (levels: joystick, mouse) × target type (levels: static, motion) experimental design.
Given the data collected by the researcher (see Table 1 below), what can she conclude
about how easily humans interact these HCI interfaces and how are these HCI interfaces
influenced by target type? Include a line graph of the means.
3
Table 1. Target localization times in the interface × target type conditions.
Subject Interface Target Time
1 Joystick Static 2.53
2 Joystick Static 2.24
3 Joystick Static 3.16
4 Joystick Static 1.50
5 Joystick Static 3.06
6 Joystick Static 2.76
7 Joystick Static 2.57
8 Joystick Static 4.03
9 Joystick Static 1.70
10 Joystick Static 0.70
11 Joystick Motion 2.00
12 Joystick Motion 2.54
13 Joystick Motion 2.23
14 Joystick Motion 0.10
15 Joystick Motion 0.75
16 Joystick Motion 1.30
17 Joystick Motion 2.11
18 Joystick Motion 2.60
19 Joystick Motion 1.05
20 Joystick Motion 2.05
21 Mouse Static 1.39
22 Mouse Static 0.67
23 Mouse Static 1.62
24 Mouse Static 1.69
25 Mouse Static 0.29
26 Mouse Static 2.29
27 Mouse Static 0.93
28 Mouse Static 1.32
29 Mouse Static 0.33
30 Mouse Static 1.67
31 Mouse Motion 1.35
32 Mouse Motion 1.29
33 Mouse Motion 1.31
34 Mouse Motion 2.48
35 Mouse Motion 1.83
36 Mouse Motion 1.03
37 Mouse Motion 2.18
38 Mouse Motion 2.01
39 Mouse Motion 1.79
40 Mouse Motion 1.87
4
Question 2
(11 marks)
A marketing team wants to determine which of two prospective product lines
consumers might prefer. They randomly select subjects to participate in a quantitative
focus group in which half of the participants were given product A, while the other half of
participants were given product B. Participants completed a questionnaire that probed
their affinity for the product they inspected during the focus group. Questionnaires items
were collapsed into a continuous-valued composite index of product affinity. In a
preliminary analysis, the marketing team ensured that the assumption of homogeneity of
variance was met:
𝐹𝑚𝑎𝑥 =
𝑠𝑙𝑎𝑟𝑔𝑒𝑠𝑡
2
𝑠𝑠𝑚𝑎𝑙𝑙𝑒𝑠𝑡
2 =
5.59
4.33 = 1.29, 𝐹𝑚𝑎𝑥.𝑐𝑟𝑖𝑡 = 4.04 .
Given the product affinity data they collected (see Table 2 below), which product are
consumers more likely to prefer? Show all relevant descriptive statistics.
Table 2. Product affinity scores for Product A and product B.
Subject Product Scores
1 A 3.27
2 A 2.52
3 A 4.83
4 A 0.68
5 A 4.59
6 A 3.84
7 A 3.35
8 A 7.00
9 A 1.19
10 A –1.32
11 B 2.69
12 B 4.04
13 B 3.26
14 B –2.08
15 B –0.44
16 B 0.93
17 B 2.97
18 B 4.17
19 B 0.30
20 B 2.80
5
Question 3
(18 marks)
Sociologists investigated whether there is an association between salary and life
enjoyment. They administered questionnaires to randomly selected participants who
reported their salary in thousands of dollars (salary) and a battery of questionnaire items
that probe life enjoyment. The life enjoyment items were collapsed into a continuousvalued composite index of life enjoyment (LE). Given their data (see Table 3 below), is
there an association between salary and life enjoyment? If so, how does a change in salary
quantitatively relate to a change in life enjoyment? Include a scatterplot of the data and the
line of best fit.
Table 3. Salary in thousands of dollars (salary) and life enjoyment composite index (LE).
Subject salary LE
1 29 24
2 25 13
3 37 30
4 16 21
5 35 13
6 32 36
7 29 18
8 48 32
9 18 5
10 6 16
11 28 14
12 35 16
13 31 14
14 5 16
15 13 12
16 20 5
17 30 25
18 36 26
19 17 13
20 29 20