| Daemen
University Data Exploration -- MTH 400
Course Description (from the College): An advanced statistical
methods course on exploratory data analysis and its application in the
fields of health science, marketing, finance, and political science. Using
the R software package, students will examine the basic tenants of
Exploratory Data Analysis (EDA). Topics will include: transforming and
standardizing data, handling missing data, data visualization
(distributions, relationships, clusters, et.), data summarization, data
reduction, cluster identification, and hypothesis development. (3
hours)
Prerequisite: MTH 325 and CSC 350 (UG)
Syllabus/Syllabus -- in Word format
Final
Project Directions
Homeworks
Important Dates
see the syllabus for a more detailed
calendar
Email List
can be gotten through Blackboard
Announcements:
Math Adjunct Office
My voicemail
My Daemen email: bmccall@daemen.edu
Office hours: see syllabus
Homeworks
Swirl Course: Getting and
Cleaning Data
Package Summaries
Data Explorations
(data files are in .xlsx format)
DE #1
DE #2
DE #3
DE #4
DE #5
DE #6
General Data Exploration Directions
Final Project Suggestions (or
select your own)
Readings
R Tutorials:
Bar Graphs (base
R)
Boxplot
(base R)
Dotplots
(base R)
Histogram
(base R)
Normal Distribution shaded between two values
(base R)
Normal Probability Plots
(base R)
Scatterplots with Trendlines and Residual Graphs
(base R)
Handouts:
Answer
Keys
Resources
Tutorials on Advanced Stats and Machine
Learning With R
Applied
Statistics with R (textbook)
Intermediate Statistics with R (textbook)
Probability and Statistics for Engineering and the Sciences, Jay. L.
Devore, 8th ed. (textbook)
Introductory Statistics (textbook)
Practical Statistics for Data Scientists (textbook)
Online Statistics Book
(textbook)
A Little Book of Time Series Analysis for R (textbook)
A Course in Time Series Analysis (textbook/notes)
Introduction to Probability
for Data Science (textbook)
Friedman's ANOVA
Test
How to
Perform Friedman's Test in R
Kendall's Tau
Calculating Kendall's Rank Correlation in R
Introduction to Bootstrapping (Statistics by Jim)
Boostrapping in R
Tutorial on Permutation Tests in R
How to use Permuation Tests
Understanding AUC-ROC Curves
Some Packages for ROC Curves
Time
Series Analysis in R
Getting Started with Multiple Imputation in R
Basic Statistics Using R
Learning Statistics with R
Statistics with R (Table of Contents)
Stats
and R
Intro
to Hypothesis Testing in R
R-Tutorial: An R
Introduction to Statistics
Tidy
Modeling with R
R Cheatsheets
Free Web Books for Learning (Statistics) with R
Easier ggplot with ggcharts
R
Color Brewer's Palettes
Markdown Cheat Sheet
Smoothing
Cubic and Smoothing Splines in R
B-Spline Basis for Polynomial Splines
R Project
R Studio
Anaconda
Using R with Anaconda
Links!
PDF Graph Paper
Bad Graphs (Convention Speeches)
Visualizing Data Badly: 8 Examples
Correlation is not Causation:
orginal article /
handout
Presidents by State
TI-Connect Software
How much people lie on surveys
On the Hazards of Significance
Testing
Exploring Correlation and Regression
Central Limit Theorem: with Bunnies and Dragons
SOCR: Statistics Online Computational
Resources
How Many Ways Can You Arrange a Deck of Cards?
Free Online Math
Courses
Confidence
Interval for Rho
Free Courses from Coursera
Coding
MTH 324/MTH
325
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