# Data Analysis

Submitted By JustJohn
Words 1122
Pages 5
Question 1.
a.

b.
According to the contingency table, 24 people who also bought a small car were buying for safety reasons

c.
The proportion for who bought a car for performance reasons was 34 people
d. Size of Car Dominant | Small | Medium | Large | Cost | 20
20% | 14
14% | 12
12% | Performance | 17
17% | 6
6% | 11
11% | Safety | 24
24% | 27
27% | 33
33% | Other | 29
29% | 53
53% | 44
44% | Total | 100 | 100 | 100 |

Looking at the distribution where the size of car is dominant, the percentages (marked in colours for easier identification) show little to no sign of association, with the exception of the ‘other’ variable which is too vague to consider any specific variable would show an association.

Question 2.
a.

b. The graph “Distribution of the Ages of the Participants” displays a Unimodal peak of ages approximately 20 years. You could argue that this graph is bimodal where there is a slight peak at ~45-50 years of age where the centre is also found. With a range of ~18 to ~78, the distribution skews significantly to the right. No noticeable outliers
c.
Sample Size: 300 drivers
Mean: 34.12 years
Standard Deviation: 15.345 years
300 drivers with a mean of 34.12 years of age with a standard deviation of 15.35 years
d.
Median: 27 years IQR: Q3 - Q1 = 46 - 21 = 25 years Median of 27 years of age with an inter-quartile range of 25 years
Question 3.
a.
The variable of interest is the heart rate of long distance triathletes using bpm (beats per minute) as the unit of measurement
b. Finding the proportion of triathletes that have a very high resting heart rate (above 62 bpm) Adjustment will be needed after checking the z-table Mean (μ) = 49 bpm Standard deviation (σ) = 6 bpm Observation (y) = 62 bpm Z score = y - μ σ = 62-49 6 = 13/6 = 2.17 Z = 2.17 0.9850 = 98.5%...

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