Introduction to learning with Computational Models AP Version Preview CT-STEM

Constructing knowledge by engaging in scientific inquiry practices

Hypothesis Testing

Hypothesis testing refers to procedures used by scientists to reject or fail to reject statistical hypotheses. It helps us attend to uncertainty and deal with random error in data collected during an investigation.

There are two types of statistical hypotheses:

Null hypothesis (H0): the hypothesis that there is no difference between two groups of data in an investigation and that the experimental observations are the result of chance.

Alternative hypothesis (HA): one of several hypotheses that experimental observations are the result of some nonrandom cause

Questions

Please answer the questions below.

Question 4.1

Explore a more detailed version of the fire model above.

Explain what "probability-of-spread" might mean in the model and how it would affect the behavior of the model.

Question 4.2

Write a question that is of interest to you which can be investigated using this model.

An example of such a question would be: How does wind-speed affect the spread of fire?

Question 4.3

Based on your exploration of the model, make a guess, and state it in the form of testable statements (hypotheses) – ones that you can test using the model. Write a null hypothesis and an alternative hypothesis for your research question.

Question 4.4

Design an experiment to test your null hypothesis. Describe the independent and dependent variables and the control treatment for the null hypothesis you wrote.

Question 4.5

Perform the experiment. Describe your observations and explain whether those support your null and alternative hypotheses or not.

Question 4.6

Provide one example of how using this computational model would benefit researchers.

Question 4.7

Provide one example of limitations that researchers might face while using this computational model.

Notes

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