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Peercetiv 4 Assignment

Peercetiv 4 Assignment

Q 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 4 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 Residents 141+? ________ 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. Supplemental P-value Explanation Download Supplemental P-value Explanation Literature Search: For your Discussion section, you will need to perform a literature search in the Web of Science similar to what you did when writing your introduction sections. (Refer to Lab 5 for instructions on how to do your search.) You will need to relate your results to the scientific literature in your discussion. It is possible that some papers you cited in the introduction can also be cited in your discussion, but, if not, you will need to find some new references. You must cite at least THREE references in your Discussion section. Once you have completed your analysis and literature search, proceed to the Peerceptiv website and begin Assignment 4. Writing Guidelines: See the below document and the Writing in Biology Handbook for guidelines when writing your Results and Discussion. Be sure to also include a References section in your submission. Scientific writing guidelines (pdf) Download Scientific writing guidelines (pdf) Grading: This assignment is worth 17 points. 40% of your grade is based on the quality of your writing, 30% comes from your peer reviews (next week’s activity), and 30% is earned by completing tasks on time. Submission Guidelines: You'll need to submit your text IN TWO PLACES. On this Canvas page, where your writing will be checked for academic integrity using the TurnItIn application On the Peerceptiv website (Links to an external site.) by following the submission prompts.

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The total count of observed wins observed here is 120. The results of the following tests includes : P value and statistical significance : The Chi squared equals 26.667 with 1 degrees of freedom . The two tailed value is less than 0.0001. The difference is considered to be extremely statistically significant . In this experiment 240 crickets were contested which including the overall data . The p value is less than 0.5 and so the null hypothesis is rejected here. In the experiment , the alternative hypothesis is predicted that males that have been residents in an artificial territory for several days and will win pairwise contest more often than the intruders. Statistical data analyses is used to interpret data along with the p values. When the p value is less than the significant level we can reject the null hypothesis .