MathBench > Statistics

Bar Graphs and Standard Error

Practice with quantitative and qualitative.

In each case below, decide whether the data presented is qualitative or quantitative. You can use the "check" button to check your answers.

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Scatter or Bars?

Answer Case

You do an experiment in which you measure growth of fish depending on the percentage of protein in their diet. Percent protein can be measured in numbers, therefore use a scatterplot

You compare average growth of three different species of fish, all of which are fed 3 grams of Fish2Whale per day. "Species" is not quantifiable, therefore you need a barchart.

You take 20 fish and measure their nose-to-tail length. You then feed each fish 1.5 grams/day of Fish2Whale for the first week and 2 grams/day for the second week. At the end of the experiment, you measure each fish's final nose-to-tail length. You need to compare final to initial length, both of which can be measured with numbers. Therefore, use a scatterplot.

You start with 30 fish, which you classify as "healthy", "unhealthy" or "dying", and feed each group a mixture of Fish-O-Matic and Ballmart fish food. At the end of 2 weeks, you measure the weight of each fish. The categories "healthy", "unhealthy", and "dying" are qualitative, so use a barchart.

You start with 6 tanks (1 week olds, 2 week olds, 3 week olds, etc) and measure how long, on average, the fish in each tank spend eating in minutes per day. You can measure fish age in weeks, so use a scatterplot.

You start with 3 tanks (newly hatched, juvenile, and adult fish) and measure how long, on average, the fish in each tank spend eating in minutes per day. Your age categories are not measured using numbers, so you must use a bar chart.


Answers:
Scatter, Bar, Scatter, Bar, Scatter, Bar

 

Here is a rule of thumb: if your x-axis contains qualitative data, you must use some sort of bargraph. If you're x-axis contains quantitative data, you will usually use some kind of scatter plot or line plot -- unless you have only a very few data points. You have to admit, a scatterplot with very few data points looks a little silly!