Part A: Palmer Penguins (Questions 1-5)
Question 1 (8 points)
We are interested in the body mass (in grams), body_mass_g, of the penguins included in these data. Create a visualization of this variable that will help us evaluate its center, shape, and spread, using appropriate labels for all axes, and a useful title for the visualization.
Question 2 (8 points)
Identify the mean, standard deviation, median and interquartile range of the penguin’s body mass (in grams). Do not simply report R output but (in addition to presenting your code and the resulting output) state, in complete English sentences, your results.
Question 3 (8 points)
Given your visualization in Question 1 and the numeric summary in Question 2, please discuss the center, shape, and spread of the body mass of the penguins. Does it seem that body mass follows a Normal distribution? Would it be more appropriate to examine the mean or median in this setting, and why?
Question 4 (8 points)
The dataset also contains information on the penguin’s species (species). Now, build a visualization and a numeric summary to examine body mass across the three species types.
Question 5 (8 points)
Given your findings in Question 4, what can we conclude about the body mass across species?
Part B: County Health Rankings (Questions 6-9)
Question 6 (10 points)
Take a random sample of 750 counties from the County Health Rankings Data provided in
lab03_counties.csv. As part of this work, use the command:
set.seed(20212022)
so that each of us selects the same sample of data. Name this random sample chr_sample in R. Select only the following variables: state, county_name, adult_obesity, and food_insecurity.
Once this is done, demonstrate that Cuyahoga County in Ohio is in your sample and that the mean of adult_obesity across all 750 sampled counties is 0.3345.
Note 1
The value for Cuyahoga County’s adult_obesity should in fact be 0.318, and the value for
food_insecurity should be 0.159, if you’re interested.
Note 2
The adult_obesity and food_insecurity variables are reported in the data as proportions. Please leave them as proportions for this lab, rather than converting to percentages.
Question 7 (10 points)
We are interested in looking at adult_obesity as an outcome. Build a visualization and describe the center, spread, and shape of the distribution of this variable. Does a Normal model for this distribution seem appropriate? Why or why not?
Question 8 (10 points)
Now we’d like to examine the relationship between food_insecurity (our predictor) and adult_obesity (our outcome). Build a useful, well-labeled visualization and then use it to motivate your description of the relationship between these two variables in complete sentences. Does a linear model seem appropriate to describe the association of these variables? Why or why not? Hint: you will likely want to include a smooth of some sort in your visualization.
Question 9 (10 points)
Create a new figure (perhaps building on the one you built in Question 8) so that this new Figure identifies where Cuyahoga County falls when examining the relationship between adult_obesity and food_insecurity. Briefly interpret Cuyahoga County’s position on each variable relative to the others in the random sample.
Part C: Spiegelhalter Reaction
Question 10 (20 points)
Reflecting on Chapter 4 of The Art of Statistics, please write an essay of no more than 100 words which discusses the relationship between adult_obesity and food_insecurity we observe in our sample of counties. Specifically, discuss whether or not we can conclude that lack of access to adequate food causes obesity.
In your response be sure to also discuss whether the method that we used to identify these data (our 750 observation random sample) strengthens or weakens your conclusion(s).
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