When testing the correlation between two different variables, one could perform a z-test. When calculating the result, a z value will be calculated. From there based on the z value, you will find the significance and relevance of the correlation. If the z value if greater than a certain value than the null hypothesis set before the test is rejected and the results are non significant. I also remember a lot about probability and how to calculate certain situations. Another set of key terms I remember is the difference between a sample and a population. A population for example is all the students at Umass Amherst. While a sample is 100 of the students attending Umass Amherst. Lastly, I remember how to read a graph, differentiate between multiple graphs, and decipher them. A graph that’s mean and tail is skewed to the left means that the graph is negatively skewed. While a graph that’s mean and tail is skewed to the right means that the graph is positively skewed.
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