Lab Report 5- Grace Meschke

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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.
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