SDS/MTH 220 - Fall 2017
Syllabus
Schedule
Resources
Helpful Links
Seelye Exam Instructions
Troubleshooting R Markdown
Undergraduate Statistics Project Competition
Handouts
R quiz study guide
Syntax comparison cheatsheet
Data wrangling cheatsheet
RMarkdown cheatsheet
ggplot2 cheatsheet
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 - Outliers, Leverage, and Influence
09 - Multiple Regression
09a - Midterm Review
10 - Randomization Test
11 - Hypothesis Testing
12 - Simulation
13 - Normal Distribution
14 - Confidence Intervals
15 - More on Confidence Intervals
16 - Probability
17 - Conditional Probability
18 - Random Variables
18a - Midterm 2 Review
19 - Inference for a Single Proportion
20 - Difference of two Proportions
21 - Goodness of Fit
22 - Independence
23 - Inference for a Mean
24 - Difference of Two Means
25 - ANOVA
26 - The Bootstrap
25 - Inference for Regression
26 - More Regression
Inference overview
Which test review
Sources
01 - Yawning
02 - Data & Sampling
03 - Experimental Design
04 - Center, Shape, and Spread
05 - Bivariate Relationships
06 - Linear Regression
07 - Linear Fit
08 - Outliers, Leverage, and Influence
09 - Multiple Regression
10 - Randomization Test
11 - Hypothesis Testing
12 - Simulation
13 - Normal Distribution
14 - Confidence Intervals
15 - More on Confidence Intervals
16 - Probability
17 - Conditional Probability
18 - Random Variables
18a - Midterm 2 Review
19 - Inference for a Single Proportion
20 - Difference of two Proportions
21 - Goodness of Fit
22 - Independence
23 - Inference for a Mean
24 - Difference of Two Means
25 - ANOVA
26 - The Bootstrap
25 - Inference for Regression
26 - More Regression
Inference overview
Labs
Labs
Introduction to R and RStudio
Introduction to Data
Simple Linear Regression
Confidence Intervals
Probability
Inference for Categorical Data
Normal Distribution
Inference for Numerical Data
Lab Sources
Introduction to R and RStudio
Introduction to Data
Simple Linear Regression
Confidence Intervals
Probability
Inference for Categorical Data
Normal Distribution
Inference for Numerical Data
Lab Templates
Introduction to R and RStudio
File -> New File -> R Markdown -> From Template
Lab CSS
Assignments
Homework
All Homework Assignments
Project
Instructions
Schedule
Proposal
Data Appendix
Presentation
Project peer evaluation
Technical Report
Sample Data Appendix
Sample Writeup 1
Sample Writeup 2
Group Dynamic
Advice
Resources
Smith Moodle
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
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