## A.3 Answers to Teaching Week 3 tutorial

1. Volume of drinks in 375ml: Graph D. (Students sometimes say Graph A, thinking that most cans have very similar amounts.)
2. Time in exam for short or easy exam: Graph C.
3. Time in exam for long or hard exam: Graph B.
4. The heights of females USC students: Graph D.
5. The starting salaries: Graph C. (Students sometimes say Graph B, thinking that salaries rise over time.)

1. For this scenario, the explanatory variable is the number of hours of light each plant received.
For this scenario, the response variable is the number of flowers each plant received.
The units of observation are the individual plants.

2. For this scenario, the explanatory variable is the number of smokers at the restaurant.
For this scenario, the response variable is the concentration of fine particulate matter.

3. For this scenario, the response variable is the waiting time.
For this scenario, the explanatory variable is the time of admission.

4. For this scenario, the explanatory variable is the "Level of Playfulness".
For this scenario, the response variable is the "Level of Coping".

1. Female Weddell: about 260--270 cm long, vary from about 200 to 310 cm. Slight negative skewness; possible small outlier at about 170--180 cm.
2. Dotchart. (Too much data for a useful stem-and-leaf plot probably.)
3. Better with a title; some more labelled tick marks would be better.

1. A few issues...
• The vertical axis is not labelled. Presumably burn time in seconds.
• The horizontal axis is not labelled. We have no way of knowing what is happening there.
2. A few issues...
• This is not a summary: This shows the burn-time of every individual candle. This makes it hard to compare means, which is the RQ.
• Why is every bar labelled? That just adds unnecessary clutter.
• Fonts are hard too read (small).
• A boxplot (or dotchart) would be the appropriate graph.
• The largest value is over 70 minutes! Do a quick project!
3. A few issues...
• Compares just two numbers (means) using lots of ink.
• No indication of variation in the data.
• A boxplot (or dotchart) would be appropriate.

### A.3.1 Answer to Sect. 3.7

Histogram: for quantitative (usually continuous) data; Bar chart: for qualitative data.

### A.3.2 Answer to Sect. 3.8

1. To display the relationship between the age of athletes, and the times taken for each athlete to complete the `beep test': Scatterplot 2. To display the percentage of elderly people in nursing homes that can independently complete a given task, for each of the seven tasks on a given list: Bar chart or Dot chart 3. To display the relationship between the type of fertiliser applied to a vegetable crop (either A, B or C) and the yield per hectare, measured over numerous plots: Boxplot 4. To display the distribution of the hardness measurements taken of 250 samples of bamboo: Histogram 5. To display the relationship between the age of concrete test cylinders (under 5 years; 5 years and older) and their strength (fit for purpose; or not fit for purpose): Side-by-side or stacked bar chart

### A.3.3 Answers to Sect. 3.9

1. Observational; the ant nest would be pre-existing. 2. Both are 'ant nests'. 3. Looks good! 4. Uphill looks different to the other two. Also: the lower dots comprise mostly blue dots (Sourdough Trial), so perhaps a difference between locations too.

### A.3.4 Answers to Sect. 3.10

1. True experiment: Treatments given (experiment), and the researchers selected the groups, groups did not previously existed (so true experiment). 2. Observation: Each patient. Analysis: The patient. 3. Pretty good. A label on the horizontal axis would be better, but the caption does contain that information. 4. Pain is reduced. 5. Yes, probably. We cannot be sure due to randomness...

### A.3.5 Answer to Sect. 3.11

Centre: About 11.4 inches; Variation: Most are between 11.0 and 12.3 inches; Shape: Slightly skewed right (apart from that outlier...); A small outlier (near 10.5 inches)

### A.3.6 Answer to Sect. 3.12

1. Boxplot. 2. Scatterplot.