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Look before you leap: EDA before hypothesis testing

Kleinteich and Gorb (Sci. Rep., 4, 5225, 2014) performed an interesting experiment with South American horned frogs. They held a plate connected to a force transducer, along with a bait fly, in front of them. They then measured the impact force and adhesive force of the frog's tongue when it struck the target.

Frog A is an adult and Frog B is a juvenile. The researchers measured the impact force of 20 strikes for each frog. In the next exercise, we will test the hypothesis that the two frogs have the same distribution of impact forces. But, remember, it is important to do EDA first! Let's make a bee swarm plot for the data. They are stored in a pandas DataFrame, df, where column ID is the identity of the frog and column impact_force is the impact force in Newtons (N).

Diese Übung ist Teil des Kurses

Statistical Thinking in Python (Part 2)

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Anleitung zur Übung

  • Use sns.swarmplot() to make a bee swarm plot of the data by specifying the x, y, and data keyword arguments.
  • Label your axes.
  • Show the plot.

Interaktive Übung zum Anfassen

Probieren Sie diese Übung aus, indem Sie diesen Beispielcode ausführen.

# Make bee swarm plot
_ = ____

# Label axes
_ = plt.____('frog')
_ = plt.____('impact force (N)')

# Show the plot
____
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