Editing Statistics and Statistical Programming (Spring 2019)/Problem Set: Week 2
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:'''PC0.''' Create a new project and RMarkdown script for this week's problem set. | :'''PC0.''' Create a new project and RMarkdown script for this week's problem set. | ||
:'''PC1.''' Run the following command | :'''PC1.''' Run the following command at the R console: <code> sample(x=c(1:10), size=1)</code> (''Optional bonus'': Explain what this command does.) | ||
:''' | :'''PC1.''' Navigate to the [https://communitydata.cc/~ads/teaching/2019/stats/data data repository for the course] and download the RData file in the <code>week_02</code> subdirectory with the output of PC1 associated with it (e.g., <code>group_<output>.Rdata</code>). | ||
:''' | :'''PC2.''' Load that file into R. It should contain one variable. Find that variable! | ||
:''' | :'''PC3.''' Compute and present summary statistics for your variable. Be sure to include the minimum, maximum, mean, median, variance, standard deviation, and interquartile range. | ||
:'''PC4.''' Write your own functions in R to re-compute the mean and the median. Be ready to walk us through how your function works. | |||
:'''PC5.''' Create some visualizations of your dataset: at the very least, create a boxplot and histogram. | :'''PC5.''' Create some visualizations of your dataset: at the very least, create a boxplot and histogram. | ||
:'''PC6.''' Some of you will have negative numbers. Whoops! Recode all negative numbers as missing (i.e. NA) in your dataset. Now compute a new mean and standard deviation. How does it change? ('''Hint:''' the <code>mean()</code> function may now produce an error. You have to include the argument <code>na.rm=TRUE</code> to work around this.) | :'''PC6.''' Some of you will have negative numbers. Whoops! Recode all negative numbers as missing (i.e. NA) in your dataset. Now compute a new mean and standard deviation. How does it change? ('''Hint:''' the <code>mean()</code> function may now produce an error. You have to include the argument <code>na.rm=TRUE</code> to work around this.) | ||
:'''PC7.''' Log transform your dataset (i.e., take the natural logarithm for each value). | :'''PC7.''' Log transform your dataset (i.e., take the natural logarithm for each value). Create new histograms and boxplots, as well as new mean, median, and standard deviation. | ||
:'''PC8.''' Briefly discuss any important differences you observe between the original | :'''PC8.''' Briefly discuss any important differences you observe between the original data and the log-transformed data. | ||
:'''PC9.''' Save your work and archive the project (i.e., in a .zip file) and | :'''PC9.''' Save your work and archive the project (i.e., in a .zip file) and upload it to canvas. | ||
== Statistical Questions | == Statistical Questions == | ||
=== Exercises from OpenIntro §2 === | |||
: ''' | : '''Q0.''' Any questions or clarifications from the OpenIntro text or lecture notes? | ||
: ''' | : '''Q1.''' Exercise 2.12 on kids missing school | ||
: ''' | : '''Q2.''' Exercise 2.20 on "assortative mating" | ||
: ''' | : '''Q3.''' Exercise 2.26 on twins (and conditional probability) | ||
: ''' | : '''Q4.''' Exercise 2.32 on the birthday problem (This is a super famous problem! Don't look it up!) | ||
: ''' | : '''Q5.''' Exercise 2.38 with the example of baggage fees | ||
: ''' | : '''Q6.''' Exercise 2.44 on income and gender | ||
== Empirical Paper | === Empirical Paper === | ||
Let's take a look at this (very dated!) paper which I published in graduate school: | Let's take a look at this (very dated!) paper which I published in graduate school: |