500-800 words with word count on the top of the paper.Instructions: This final Peerceptiv assignment for the term gives you an opportunity to write the Results and Discussion sections for your prior work observing cricket dominance interactions.
One thing that you need to do in order to write your text for Peerceptiv Assignment 3 is to perform a statistical test on the combination of your data (you should have three “wins” from last week’s observations) and class data (shown below in Table 1). You will then interpret these results.
Table 1: Class Data
Observed wins Expected wins
Intruders 64 +?
You will add your three observations (indicated by the “?” marks) to the data set in Table 1 and then calculate the expected value for wins. Because our null hypothesis is that there is no relationship between residency and the likelihood of winning fights, our expected values for residents and intruders should be 50:50. That’s the total count of observed wins for residents and intruders (class plus yours) divided by 2.
Data Analysis: Next you will go to GraphPad (Links to an external site.) and complete the following steps
Enter your data in Rows 1 & 2.
Click the “Calculate Now” button.
Document the following results of the Chi-square test. You will need to report both of these results in your Results section, as well as whether or not you could reject the null hypothesis.
Chi-square value: This is the value calculated by the Chi-square equation based on your data
P-value: This is the probability that you would have observed this result if your null hypothesis were true (there is no relationship between residency and winning). By convention in biology, we reject the null hypothesis if our statistical test produces a p-value that is .05 or smaller.
We have added a supplemental p-value explanation that hopefully will help you better grasp the concept.
In the files below, you will find the p-value explanation sheet referred to and 2 example papers to help create a new, unplagiarized paper for this assignment. It will be screened through “TURN IT IT” plagiarize screener.
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