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EPSY 530 - Statistics I - Summer 2015

Instructor: Jason Bryer, Ph.D. jason@bryer.org
TA: Justin Chase jpchase@albany.edu
Website: epsy530.bryer.org
Class Time: Monday & Wednesday 4:15pm to 7:05pm
Class Location: Humanities 111
Office Hours: By appointment

Course Description

Descriptive statistics including measures of central tendency and variability, correlation and regression. Introduction to statistical inference, including sampling distributions, significance tests, confidence intervals, and power of tests of significance.

Grading

  • Homework (25%)
  • Labs (50%)
  • Final exam (25%)

Grade Distribution

A = 93+; A- = 90-92; B+ = 87-89; B = 84-86; B- = 80-83; C+ = 75-79; C = 70-74; D = 65-69; E = <65

Schedule

NOTE: Tentative. Subject to change

Date Chapter Topic Resources
May 27 1 Intro to Data Chapter 1 Slides
Lab 0 In class
June 1 2 Probability Chapter 2 Slides
June 3 3 Distributions Chapter 3 Slides
Distribution Calculator
Probability Tables
June 8 4 Foundation for Inference Chapter 4 Slides
June 10 5 Inference for Numerical Data Chapter 5 Slides
Shiny App for Error Rates
Shiny App for t-distributions
t-Test Exercise (Rmd, R)
June 15 6 Inference for Categorical Data Chapter 6 Slides
Why .05?
June 17 7 Linear Regression Chapter 7 Slides
Linear Regression PDF
June 22 Linear Regression Exercise Handout
Slides
June 24 Review
June 29 Final Exam - Take Home Due

Textbook

Required

Diez, D.M., Barr, C.D., & Çetinkaya-Rundel, M. (2012). OpenIntro Statistics (2nd Ed).

This is an open source textbook and can be downloaded in PDF format here, from the OpenIntro website, or a printed copy can be ordered from Amazon.

Recommended

Kabacoff, R.I. (2011). R in Action. Manning Publications.

You can find a lot of the material in R in Action on Kabacoff's website, statmethods.net. You can receive 38% off using the ria38 promo code when ordering from here.

Other Documents

Homework Assignments

  • Chapter 1. p. 47: 1.2, 1.4, 1.8, 1.10, 1.12, 1.16 (part a only), 1.23, 1.30, 1.39, 1.47, 1.48
  • Chapter 2. p. 107: 2.1, 2.2, 2.6, 2.8, 2.11, 2.12, 2.15, 2.17, 2.21, 2.28, 2.46
  • Chapter 3. p. 149: 3.1, 3.3, 3.5, 3.10, 3.16, 3.18, 3.19
  • Chapter 4. p. 197: 4.1, 4.3, 4.4, 4.9, 4.11, 4.15, 4.19, 4.22, 4.29, 4.33, 4.47
  • Chapter 5. p. 247: 5.2, 5.4, 5.5, 5.7, 5.9, 5.15, 5.17, 5.18, 5.21, 5.24, 5.33
  • Chapter 6. p. 298: 6.1, 6.5, 6.13, 6.16, 6.23, 6.26, 6.32, 6.37, 6.39, 6.42
  • Chapter 7. p. 330: 7.3, 7.6, 7.7, 7.13, 7.17, 7.19, 7.20, 7.24, 7.28

Labs

These mini projects will have you explore statistical topics using R. For each project, create a R Markdown file (you can download the template for each lab below by right clicking and choosing "Save Link As..."). Name your file using the following format: LastName-X.Rmd where X is 0 to 8 for the project number. You can email your projects with EPSY530-Lab in the subject.

  1. Introduction to R and RStudio (Template)
  2. Introduction to Data (Template)
  3. Probability (Template)
  4. Distributions of Random Variables (Template, Preview)
  5. Foundations for Statistical Inference
    1. Sampling Distributions (Template, Preview)
    2. Confidence Levels (Template)
  6. Inference for Numerical Data (Template)
  7. Inference for Categorical Data (Template)
  8. Introduction to Linear Regression (Template)

Software

An RStudio will be available through the web (Google Chrome is recommended) at http://learnrstats.com/rstudio. You will be given a username and password in class. However, it is highly recommended that you also install R and RStudio on your computer if possible.

Although this course will emphasize statistical concepts, we will make use of R, an open source statistics program and language. Be sure to install R and RStudio on your own computers within the first week of the class.

If using Windows, you also need to download and install these:

Once everything is installed, execute the following command in RStudio to install the packages we will use for this class (you can copy-and-paste):

install.packages(c('openintro','OIdata','devtools','ggplot2','psych','reshape2',
				   'knitr','markdown'), repos='http://cran.r-project.org')
devtools::install_github("seankross/lego")

Here are some resources to help you learn and use R Markdown:

Academic Integrity

Whatever you produce for this course should be your own work and created specifically for this course. You cannot present work produced by others, nor offer any work that you presented or will present to another course. If you borrow text or media from another source or paraphrase substantial ideas from someone else, you must provide a reference to your source.

The University policy on academic dishonesty is clearly outlined in the Student Bulletin, and includes, but is not limited to plagiarism, cheating on examinations, multiple submissions, forgery, unauthorized collaboration, and falsification. These are serious infractions of University regulations and could result in a failing grade for the work in question, a failing grade in the course, or dismissal from the University. http://www.albany.edu/undergraduate_bulletin/regulations.html

Reasonable Accommodation

Reasonable accommodations will be provided for students with documented physical, sensory, sys- temic, cognitive, learning and psychiatric disabilities. If you believe you have a disability requiring accommodation in this class, please notify the Director of Disabled Student Services (Campus Center 137, 442-5490). That office will provide the course instructor with verification of your dis- ability, and will recommend appropriate accommodations. For more information, visit the website of the UAlbany Office for Disabled Student Services. http://www.albany.edu/studentlife/DSS/ guidelines/accomodation.html

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EPSY 530 Statistics I - Division of Educational Psychology, University at Albany

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