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Return to Presenting Scientific Data in R Student Resources
Chapter 5 Multiple Choice Questions
Quiz Content
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Which of the following statements best describes our opinion of bar charts?
They are great alternatives to histograms.
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They are rarely the best option for quantitative data.
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They are a combination of the best features of a histogram and a boxplot.
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They are preferable for scientifically trained readers.
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Which of the following is always a good design choice to make when presenting boxplots of several samples?
Removing the whiskers to reduce clutter
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Avoiding labelling the y-axis
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Deleting outliers
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None of the above
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Which of the following could aid interpretation when comparing histograms of different samples?
Using the same bin sizes for each sample
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Using contrasting colours for each histogram
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Making bins as small as possible
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Making bins as large as possible
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In what situations might it be useful to manipulate the transparency of colours in a figure?
Where charts might have to be read in variable lighting conditions
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In any situation when you want a chart to have a more professional look
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When overlaying histograms on top of each other
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When presenting data as a strip-chart
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Complete the statement: "When comparing multiple samples of quantitative data, "
histograms are more effective than boxplots.
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Sturges' rule becomes more reliable than the Rice rule.
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effective use of colour is the most important issue.
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boxplots are generally more effective than histograms.
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What should be an important consideration when deciding whether to use a boxplot or a bar chart?
Boxplots generally provide less detail about the distribution of the data than bar charts.
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Bar charts generally provide less detail about the distribution of the data than boxplots.
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Bar charts handle logged data more naturally than boxplots.
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Bar charts are a better option for grouped data than boxplots.
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In a situation where you had grouped data and plotted values from two different treatments alongside each other, it would be important to include a ______ to explain the difference in design feature (most commonly colour) used to differentiate the treatments.
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