This is the course website for Applied Statistical Methods 1 course taught by Dr. Robin Donatello in Spring 2019. This landing page is used for posting of regular announcements and information for students of the class.

5/12/19 - Finals Week

Final assignments (Due Friday 5/17)

Good luck with all of your finals, and congratulations to those who are graduating on Saturday!

5/6/19 - Week 15

Expanded Office Hours - 11 hours!!!

  • Monday: 10-11am, 3-4pm
  • Tuesday: 10-12pm, 2-4pm (Tehama 116)
  • Thursday: 10-11am, 2-4pm (Tehama 116)
  • Friday: 11-12pm, 2-3pm

4/15/19 - Week 12

SET’s this week. Please be present.

We’re starting to talk about multivariable models this week. This involves understanding how to think about simultaneous relationships between multiple variables.

Life isn’t bivariate. We “know” there is more to how big a caterpillar is than simply the species. What about the temperature? was it a drought year? what type of tree is it on? How heavy is the bird predation in that area? What other species are on the same tree that could be competing for resources? To understand the singular effect of bird predation on caterpillar size, we must consider how all other factors affect caterpillar size, and how those other factors might be related to each other as well.

The course notes is a “cliff notes” version of the lecture material for this coures. If you’re not watching the videos (even on 1.5x speed) you are missing critical information that I will not lecture on in class, but that you will be responsible for on the homework and exam.

Due this week

4/8/19 - Week 11

DataFest is over and so I’m back 100% with you!

We’re finishing up Bivariate Inference this week.

Self and peer evaluation form available: Due Sunday

4/1/19 - Week 10

This week got lost in the post-sickness & pre-DataFest ether.

3/25/19 - Week 9

The rest of the semester is all about Inference! This is what you’ve been training for, and waiting for. This week we’ll start out with setting the foundations of the process on 1 variable, then quickly move into testing relationships between two variables.

Due this week

  • Hypothesis testing quiz on Tue/Wed
  • HW 8 BIG assignment! Has multiple parts. Procrastinate and be doomed.

Midterm Error Assessment (Optional - Due 4/5/19)

As an opportunity to look for patterns in your test taking and to develop strategies to perform better in the future, there is an optional error assessment that you can complete. If you do so you can earn up to half the points missed on the exam back. To do this you must use the Analyzing exam errors form available on the materials page. Using this form you will:

  • Classify the types of errors you made (where you lost points).
    • Identify common patterns or themes.
  • On a separate paper, correctly re-work every problem you missed.
  • Go over your corrections with a tutor (or me).
    • Explain what you did wrong and why your corrections are right.
    • Discuss strategies to perform better on future exams.

3/11/19 - Week 8

Office Hours for this week:

Due this week

  • Poster Prep Stage I: Setting the Stage & Exploratory Data Analysis.
    • Draft due Tuesday, Peer Review by Thursday, Final by Saturday
  • Foundations worksheet. Practice setting up inference on your research question
    • Done in class, docx available on Materials page.
    • Come prepared! Choose 1 binary and 1 quantitative variable from your data set.
      • Create a frquency table for the binary catgorical
      • Calculate the mean, sd, and number of valid records for the quantitative.
    • Due with Midterm
  • Midterm Thursday/Friday
    • Sample exam posted on the Materials page. Shows you the structure of the exam.
    • A calculator is not needed, but you may want one.
    • Only your course packet is allowed on the exam.

3/4/19 - Week 7

Monday I will be at the WiDS conference (across the creek) and so Kathy Gray will cover class for me. You will be covering material in the course packet 4.1-4.4, foundations for inference. Also be sure to watch the PDS video, the relevant content starts at 14 minutes and goes until about 16 minutes.

Due this week

  • Worksheets on discovering the Central Limit Theorem
    • Both worksheets (parameters vs statistics and the CLT) can be found on the materials page under homework
    • Worked on in class on Monday/Tuesday, turned in Wednesday/Thursday
    • Quiz on interval estimates due Wednesday (for TR) or Thursday (for MWF)
      • Review Course packet section 4.5 for this material
  • Draft of your research proposal is due on Tuesday, peer review Thursday, final version due Saturday.
    • Read the peer review instructions in Homework 7 carefully. (they were updated Tuesday AM)

Events for this week (always free and open to all unless specified)

  • Monday 3/4: Women in Data Science technical conference. Live stream of the global conference out of Stanford, lunchtime career panel featuring local women in Data Science, and an opportunity to present your research in our “local women sympoisum”
  • Tuesday 3/5: DSI seminar on strategies to manage big data. 2-3pm, Tehama 116.

2/24/19 - Week 6

Now that you’ve had a chance to learn what your data looks like, exploring relationships and learning more about the variables that you are interested in researching, let’s take a step back and look at the big picture. You will use lecture notes on writing empirical research (found on the materials page of this website) to guide the writing of a research proposal.

Applied statistics is used to support research. Numbers and measures don’t stand on their own. It is important that you understand how to use data to support scienctific research.

So far you have been conducting an exploratory data analysis to learn the distributions of your measures, and to assess for any possible relationships in your research. You cannot make any statistical claims about whether or not a relationship is significant at this point. That is under the realm of inferential statistics and will be the topic of the class after Spring break.

To understand why inferential statistics can be used to make valid claims, we have to learn a little bit about Probability first. This topic is only briefly covered in the PDS videos. You will have to spend more time in the course packet, AND in the OpenIntro textbook if you have never taken a statistics course before.

This is a much more mathematical section of the course, so be sure to plan your time accordingly. Over the next two weeks you should be writing your research proposal, working on your poster preparation slides, and filling out the notes and examples in the course packet. We will be working heavily out of the course packet, so it is essential that you read the material ahead of time so the examples we work through in class are meaningful.

Three quizzes this week

  • Sun/Mon: Writing about empirical research. Based on these lecture notes.
  • Tue/Wed: Probability distributions. Based primarily on course packet chapter 3, and on PDS video 8 (only up to 14 minutes).
  • Saturday: Upcoming assignments. Making sure you know the expectations for the Research proposal and poster prep stage I.

Events for this week (always free and open to all unless specified)

  • Thursday 2-4pm, Tehama 116: Data Science Seminar: Getting Started with R and Python Are you ready to install R onto your own laptop? Do you want to try out Python? Come drop in and get help getting started with either of these two languages.
  • Saturday 3/2: Women in Business Summit
  • Monday 3/4: Women in Data Science technical conference. Live stream of the global conference out of Stanford, lunchtime career panel featuring local women in Data Science, and an opportunity to present your research in our “local women sympoisum”

2/18/19 - Week 5 - Exploring Relationships

It’s ok to struggle, it’s not OK to not do anything. If you are having trouble with coding, you need to ask for help. This class builds on each assignment. You can’t do HW05 well if you didn’t do HW04. You won’t be able to do HW06 if you can’t do HW05. Don’t risk falling behind, you will struggle to catch up and may not pass. There are five of us available to help you with a combined total 10 hours of office hours. You can make appointments with any of us outside of our scheduled hours as well.

Items due this week:

  • HW 06 - Bivariate Graphing
  • Data Camp - Intro to Data (practice data management with R)
    • Don’t forget to do the corresponding BBL quiz.

Events for this week (always free and open to all unless specified)

2/10/19 - Week 4 - Making pretty pictures to win friends and influence people!

No quiz on exploring numeric data. Prepare answers in the course notes section 2.1 instead (for Mon/Tue) and 2.2 (for Wed/Thu).

If there’s one take home message for this week, is to describe the distribution of variables you need:

  1. a picture
  2. summary statistics
  3. a complete sentence interpretation

While your goal should be to make figures stand alone, you won’t be there quite yet. Your coding skills will develop as you go on throughout the semester.

Advice: Complete the ggplot2 lesson in DataCamp (and corresponding blackboard learn quiz) EARLY this week. It will make coding in ggplot throughout the week much easier.

Events for this week (always free and open to all unless specified)

  • “Women Like You” Leadership Symposium (Drop in 10-2pm) Distinguished female leaders share stories and discuss topics designed to inspire and empower all. With highlights from our own, Chico State faculty and staff will tell their personal stories of success and failure, sharing their journeys of resilience and rise as a woman in today’s social climate. Student attendees can enter to win from a pool of $5000 in textbook scholarship funds.

  • Data Science Seminar: Spatial is Special (Th 2-3pm, Tehama 116) Learn how to start exploring and analyzing geographic data using GIS (Geographic Information Systems) software.

2/4/19 - Week 3 - Hello R!

OH Monday cancelled. I will be available 12-2pm and possibly 4-5pm instead.

Second chance at Blackboard learn quizzes connected to DataCamp.

  • The quizzes in Blackboard that correspond to DataCamp quizzes will be re-opened for partial credit this week.

You have 2 assignments (and 2 pre-class video quizes) to turn in this week!

Read the instructions of each carefully to ensure that they are completed and submitted correctly.

  1. A literature review [Homework 03].
  2. Demonstration of data management code [Homework 04].

We are starting to code in R this week. You must have completed the Data Camp assignments from last week to be ready for this. In class you will work with your partner to take a closer look at your codebook to identify what types of data management you will have to do. The [lec03_dm_prep_questions] lecture notes that can be found on the course materials page contain questions to help guide this process.

Extra Materials

  • I have created a video to walk you through how to get your data into R Studio.
    • Right now this can only be acessed through Blackboard Learn.
    • Watch this before class on Wednesday/Thursday
  • The [Help with R] page has been updated to include more info such as useful functions and how to navigate data.

Entering a challenging time

You may feel like this in the next couple weeks:

But if you use the references in the course notes, the peer mentors, videos and engage in the most effective way of learning a new programming language,

then you will learn how to dominate debugging and come out a stronger and more capable of being able to answer research questions using data.

1/28/19 - Week 2 Generating research questions

My office hours (Holt 202)- M 10-11am, T: 11-12noon, F 12-1pm.

Peer mentor office hours have been posted on the [peer mentor page]

I am out of town this week starting at 1pm on Thursday.

On Thursday/Friday you will be meeting with a research librarian who will help you use our Library resources to find primary source articles to support your research.

Class will meet in MLIB 226

Upcoming Quizzes:

Upcoming Assignments:

1/21/19 - Week 1 Welcome to Spring 19!