SDS 201 - Spring 2018
Home
Syllabus
Schedule
Resources
Helpful Links
Troubleshooting R Markdown
Lectures
Notes
01 - Yawning
02 - Data & Sampling
03 - Experimental Design
04 - Center, Shape, and Spread
05 - Bivariate Relationships
06 - Linear Regression
07 - Linear Fit
08 - Regression
09 - Multiple Regression
10 - Randomization and Hypothesis Testing
11 - Simulation
12 - Normal Model
Code for Normal Model
13 - Confidence Intervals
14 - More on Confidence Intervals
15 - Inference for a Single Proportion
16 - Difference of two Proportions
17 - Difference of two Proportions (cont.)
18 - Goodness of Fit
22 - Independence
23 - Inference for a Mean
24 - Difference of Two Means
25 - ANOVA
26 - The Bootstrap
27 - Inference for Regression
28 - Bootstrap for Regression
29 - Regression Diagnostics
Labs
Labs
Introduction to R and RStudio
Introduction to Data
Simple Linear Regression
Data Visualization
Sampling Distributions
Confidence Intervals
Normal Distribution
Inference for Categorical Data
Inference for Numerical Data
Bootstrapping
Multiple Regression
Bridge Seminar
Assignments
Homework
All Homework Assignments
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:
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