Lab Report 5- Grace Meschke

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University of North Dakota *

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Anthropology

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Apr 3, 2024

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Lab 5 Report 1. In your own words, what is a null hypothesis? What questions do you still have? [2 pts] A null hypothesis is the assumption that there is no significant relationship between the variables in an experiment. It is the opposite of a hypothesis. An example of this would be, if you were hypothesizing that animals grow at different rates due to temperature and climate change, then your null hypothesis would be that the temperature and climate change has no effect on animal’s growth. 2. In your own words, what is a p-value? What questions do you still have? [2 pts] The p-value is the probability that differences in the data are because of chance, and the assumption that there is no effect or difference. 5% or 0.05 chance of data being different due to chance, as opposed to process. 3. What’s your p-value for your species habitat-season relationship? [1 pt] P-value < 0.0001 4. Does the p-value you provided support or reject the null hypothesis? Were the observed values significantly different than what would be expected due to chance? Can you make claims about the statistical significance of your data? [2 pts] The p-value given rejects the null hypothesis, which also makes the observed values significantly different from what we were expecting to chance. We can make claims from here on out due to the p- value provided. Helpful reminders from the week 4 lab report: Null hypothesis : the distribution of observed numbers in your contingency table is NOT different from the expected numbers. In other words, you are testing the assumption that there is no difference in the groups tested. See the table below to learn more about what these p-values mean. P < 0.05 P > 0.05 REJECTS null hypothesis SUPPORTS the null hypothesis Observed values are significantly different from what would be expected due to chance. Observed values are NOT significantly different from what would be expected due to chance. Claims about the differences CAN be made Claims about the differences CANNOT be made 5. Percent Deviation Table [2 pts] Floodplain Grassland Mixed Savanna and Woodland Limestone Gorge Dry 4.50% -7.90% -30.40%

Dry-Wet 3.60% -5.20% -100% Wet 49.90% -100% 416.20% Wet-Dry -31.40% 54% 328.50% 6. What claims can you make from the percentage deviations table? [4 pts, 1 pt for each season] Hint : You can only make claims about the significance of the data if you rejected your null hypothesis (p<0.05). If your null hypothesis was supported, briefly explain what that means regarding claims you make from your data. The data about was significantly different, which tells us that the elephants use of habitats change with the seasons. This is shown through: a. In the dry season, the floodplain grassland had 4.5 more elephants than expected. b. In the dry-wet season and dry season, the floodplain grassland was the only habitat with a positive deviation. c. In the wet season, the limestone gorge had a significantly larger number than any other habitat. d. In the wet-dry season, the limestone gorge had a significantly larger number than any other habitat. 7. Based on your graph from Lab 4 and your analyses above, how would you describe the movement of animals in the Gorongosa National Park over the course of the year? [2 pts] Throughout the course of a year, the elephants in the Gorongosa National Park favor floodplain grassland region during the dry and dry-wet seasons. This is shown in the compound bar graph from Lab 4. During the wet season, the elephants also tend to choose the floodplain grassland, and stay out of the mixed savanna and woodland. Once we get into the wet-dry season, the elephants move more towards the mixed savanna and woodland, but some seem to stay in the floodplain grassland. 8. During Lab 4, you learned that graphs show patterns or trends in data, but claims should come from the statistical test. Analyze the following research question with their data visualization and statistical reporting. [4pts] Research Brief : J. Bristol Foster hypothesized in the 1960’s that an animal species (martens, a small mammal) on an island would evolve over generations to be larger or smaller than individuals of the same species living on the mainland . To test this hypothesis, I examined natural history databases for American martens, a member of the weasel family, living in Alaska and the Alexander archipelago off the coast of Alaska. To measure size, I used the weight of martens on the mainland and martens on the islands. The average weight of these groups is graphed right. A t-test was used to determine whether there is a significant size difference between martens and the statistical test returned a p-value of 0.0322.

a. What is the null hypothesis regarding martens’ weights on the mainland and the island? There will be be no significant difference between the average weights of the people from the mainland and that of the island. b. Based on the graph, what trend do you see and is this trend significant according to the t-test? According to this graph, we can see that the average weight of the people belonging to the island is more than that of the mainland. The t-test shows that the p-value is 0.0322, which shows that the result is due to chance, which we can see is not true, hence the t-test is not significant. c. What claims can we make about Foster’s hypothesis? Foster’s hypothesis helps us claim that because of the evolution people from the island tend to move to the mainland, and their average weights gets reduced. d. What would you study next or what criticism of this study would you try to fix? I would choose to study what factors are causing people on the island to migrate toward the mainland, and what is governing them to reduce their weights after the process. 9. What was the main point of today’s lab? Are there any concepts that you are still struggling with? If so, what are they? [1 pt] The main points from today’s lab was to analyze and interpret data from week 4’s lab. We continued to work on the experiment of how temperatures and habitat changes affect the physical appearance of animals and species. We also learned about inferential statistics, percent deviation, and more about the p-values and how they affect the hypothesis and null hypothesis. I still am having some trouble with the p-value and the significance of it, but I think reviewing the lab 4 PDF handout will help me to get a better understanding.

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Lab Report 5- Grace Meschke

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