SDS 290 - Interterm 2021
Home
Syllabus
Schedule
Resources
Helpful Links
Downloading R and RStudio
Modern Data Science with R
Troubleshooting R Markdown
Qualtrics
Data Ethics Resources
Lectures
Notes
01 - Intro to Experimental Design
02 - Four Basic Designs
03 - Four Basic Designs (cont.)
04 - Informal ANOVA
05 - Informal ANOVA (cont.)
06 - Formal ANOVA I
07 - Formal ANOVA II
08 - Formal ANOVA III
09 - BF[1] Design
10 - BF[2] Design I
11 - BF[2] Design II
12 - CB[1] Design I
13 - CB[1] Design II
14 - Latin Square Design
15 - SP/RM[1,1] Design I
16 - SP/RM[1,1] Design II
17 - Scatterplots for Within-Block Factors I
18 - Scatterplots for Within-Block Factors II
19 - Design Practice
20 - Extending the Basic Designs I
21 - Extending the Basic Designs II
22 - Multiple Comparisons
Code
01 - Four Designs
02 - Informal ANOVA
03 - Formal ANOVA
03b - BF[1] Design in R
04 - BF[2] Design in R
05 - CB[1], Latin Square, SP/RM[1,1] Design in R
06 - Extensions in R
07 - Multiple Comparisons
Homework
Problem Sets
HW1a: Record your names on Moodle
HW1b: CITI Training
HW2 (OPTIONAL): Getting started with R
HW3: Review Exercises (p. 34-37), 3, 6, 9, 11, 13a, 14, 16, 17
HW4: Review Exercises (p. 57), 1-3, 5, 6 (but using R)
HW5: RE CH 3: 3-4 (data in fig 3.21 on pg. 102), 12, 13, 17
HW6: Using software; Due 2/02 at 9:20a
HW7: RE CH 7: A1-A3, A6, B5-B6, C1-C3, C6-C9
HW8: Using software - BF[2], Compound factors
Projects
Mini project 1
Mini Project 2
Book Office Hours
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:
Log on to the Smith College
RStudio Server
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