SDS/MTH 290 - Spring 2018
  • Home
  • Syllabus
  • Schedule
  • Resources
    • Helpful Links
    • Troubleshooting R Markdown
  • Lectures
    • Notes
    • 01 - Intro to Experimental Design
    • 02 - Four Basic Designs
    • 03 - Informal Analysis
    • 04 - Experiment Decisions
    • 05 - Formal ANOVA
    • 06 - BF[1] Design
    • 07 - BF[1] Design in R
    • 08 - Exam 1 Review
    • Review Questions
    • 09 - BF[2] Design
    • 10 - BF[2] Design (cont.)
    • 11 - CB[1] Design
    • 12 - CB[1] Design (cont.)
    • 13 - SP/RM[1,1] Design
    • 14 - SP/RM[1,1] Design (cont.)
    • 15 - Extending the Basic Designs
    • 16 - Extending the Basic Designs (cont.)
    • 17 - Multiple Comparisons
    • 18 - Fisher Assumptions
    • 19 - Exam 2 Review
    • Code
    • 02 - Four Designs
    • 03 - Informal Analysis
    • 05 - Formal ANOVA
    • 07 - BF[1] Design in R
    • 09 - BF[2] Design in R
    • 13 - CB[1], Latin Square, SP/RM[1,1] Design in R
    • 15 - Extensions in R
    • 18 - Multiple Comparisons and Assumptions
  • Homework
    • Problem Sets
    • HW1: Record your names on Moodle
    • HW2: Review Exercises (p. 34-37), 3, 6, 9, 11, 13a, 14, 16, 17
    • HW3: Review Exercises (p. 57), 1-3, 5, 6 (but using software)
    • HW4: Ch4: B1-3, C3, D1, RE CH 3: 3-4 (data in fig 3.21), 11-13, 17-19
    • HW5: Using software; Due 3/23 at 5p
    • HW6: Cancelled, no homework
    • HW7: **Ch 7**: A1-A3, A6, B5-B6, C1-C3, C6-C9
    • HW8: Cancelled, no homework
    • HW9: Using software-last homework
  • Project
    • Project
    • Instructions
    • Schedule
    • Advice

Resources

  • Smith Moodle
  • Basic Math Reviewsheet
  • OpenIntro with Randomization and Simulation
    • PDF of the textbook
    • R packages: openintro and OIdata
    • Click on “Typos and feedback” to send corrections to the authors
    • an online survey
  • RStudio IDE
    • Choose one of two options:
      1. Log on to the Smith College RStudio Server
      2. Download and install RStudio Desktop
        • Download and install R
    • Learn more about R Markdown
      • printable Reference Guide for R Markdown
    • RStudio’s cheatsheets for:
      • R Markdown
      • Data Wrangling with dplyr
      • Data Visualization with ggplot2
    • Packages you should install: mosaic, mosaicData, openintro, OIdata, knitr, markdown
    • Interactive tutorials via swirl and DataCamp
  • Using R with the mosaic package
    • the mosaic package
    • Graphics with mosaic
    • Less Volume, More Creativity
    • Minimal R for Intro Stats: one page handout with R commands
    • mosaic resources
    • A Student’s Guide to R
    • Randomization-based inference using the mosaic package
    • Data Computing at Macalester
  • Quantitative Resources on campus
    • Statistics TAs are available Sunday through Thursday from 7-9 pm in Burton 301
    • visit the Spinelli Center for Quantitative Learning
    • list of single-topic workshops hosted by the Spinelli Center

Created by Randi Garcia.

Originally based on course by Katherine Halvorsen.

Webcode by Ben Baumer.