Statistics and Statistical Programming (Winter 2017)/Problem Set: Week 3: Difference between revisions

Revision as of 21:05, 12 January 2017

This is general advice going forward but it makes sense to include it here: My advice is to start working through the programming challenges first. The programming challenges will only include material that we covered in the readings for the previous week.

If you're having trouble loading up your dataset (PC2) find me in the next day or so as you will only be able to do the other challenges once you've done that one.

Programming Challenges

PC0. Check the list of GitHub repositories page here. A few of you (Maggie, Luyue, and Janny) named yours something like "week_02." Although there's no problem with this, it might cause confusion going forward when you add homework for future works. So if you're Maggie, Janny, and Luyue, I recommend that you create and push a new repository/directory with a more generic name which you can use for all your future assignments. For everybody else, please copy your files and work for this (and all future) problem sets into the same repository you used last time.

PC1. In the class assignments GitHub repository (uwcom521-assignments), I've uploaded a new dataset for each person in the class in the subdirectory week_03. Sync my repository, find your file, copy into your homework directory which is managed by Git. Commit your dataset file into your personal homework git repository.

PC2. Open the dataset in a spreadsheet (Google Docs, Excel, etc) to take a look at it. It's often a good idea to open it in NotePad as well so you can look at the structure of the "raw data." If you want to generate statistics or visualize things, that might be OK. Manually inspecting the raw data is often a useful step.

PC3. Load the CSV file into R. Also make sure that you loaded the week 2 dataset file.

PC3. Get to know your data! Do whatever is necessary to summarize the dataset. Now many columns and rows are there? What are the range of variables? What are the appropriate summary statistics to report for each variable? What are the ranges, minimum, maximums, medians, medians, standard deviations of the variables of variables? Draw histograms.

PC4. Compare the week2.dataset vector with the first column (x) of the data frame. I mentioned in the video lecture that they are similar? Do you agree? How similar? Write R code to demonstrate or support this answer convincingly?

PC5. Visualize the data using ggplot2. Graphing x on the x-axis and y on the y-axis seem pretty reasonable! If only it were always so easy!

:PC6.

PC7.

PC8.

PC9.

Statistical Questions

Exercises from OpenIntro §2

Q0. Any questions or clarifications from the OpenIntro text or lecture notes?

Q1. Exercise 3.4 on triathlon times

Q2. Exercise 3.6 which is basically a continuation of 3.4

Q3. Exercise 3.18 on evaluating normal approximation

Q4. Exercise 3.32 on arachnophobia (spiders are frequent concern in statistical programming)

Empirical Paper

There will be no empirical paper this week. Understanding probability distributions is fundamental to statistics but few people really end there so it's hard to find a paper that is just about this.

@@ Line 7: / Line 7: @@
 :'''PC0.''' Check the [https://wiki.communitydata.cc/Statistics_and_Statistical_Programming_(Winter_2017)/List_of_student_git_repositories list of GitHub repositories page] here. A few of you (Maggie, Luyue, and Janny) named yours something like "week_02." Although there's no problem with this, it might cause confusion going forward when you add homework for future works. So if you're Maggie, Janny, and Luyue, I recommend that you create and push a new repository/directory with a more generic name which you can use for all your future assignments. For everybody else, please copy your files and work for this (and all future) problem sets into the same repository you used last time.
 :'''PC1.''' In the [https://github.com/makoshark/uwcom521-assignments/ class assignments GitHub repository]  (uwcom521-assignments), I've uploaded a new dataset for each person in the class in the subdirectory <code>week_03</code>. Sync my repository, find your file, copy into your homework directory which is managed by Git. Commit your dataset file into your personal homework git repository.
-:'''PC2.'''
+:'''PC2.''' Open the dataset in a spreadsheet (Google Docs, Excel, etc) to take a look at it. It's often a good idea to open it in NotePad as well so you can look at the structure of the "raw data." If you want to generate statistics or visualize things, that might be OK. Manually inspecting the raw data is often a useful step.
-:'''PC3.'''
+:'''PC3.''' Load the CSV file into R. Also make sure that you loaded the week 2 dataset file.
-:'''PC4.'''
+:'''PC3.''' Get to know your data! Do whatever is necessary to summarize the dataset. Now many columns and rows are there? What are the range of variables? What are the appropriate summary statistics to report for each variable? What are the ranges, minimum, maximums, medians, medians, standard deviations of the variables of variables? Draw histograms.
-:'''PC5.'''
+:'''PC4.''' Compare the <code>week2.dataset</code> vector with the first column (<code>x</code>) of the data frame. I mentioned in the video lecture that they are similar? Do you agree? How similar? Write R code to demonstrate or support this answer convincingly?
+:'''PC5.''' Visualize the data using <code>ggplot2</code>. Graphing x on the x-axis and y on the y-axis seem pretty reasonable! If only it were always so easy!
+ :'''PC6.'''
+:'''PC7.'''
+:'''PC8.'''
+:'''PC9.'''
 == Statistical Questions ==