| Daemen
University Statistics II -- MATH 325
Course Description (from the College):
An introduction to statistical regression models with emphasis on
applications in
health sciences, marketing, finance, and political
science. Students will explore commonly used regression
techniques,
including: univariate and multi-variable linear models, logistic
regression models, and ANOVA
models represented as general linear
models. These methods will be illustrated using the computer
software
R. Time permitting, advanced topics will include time-series models and
statistical measures of
validity (sensitivity, specificity, and basic
ROC analyses).
Prerequisite: MTH 324
Syllabus -- in Word format
Final
Project Directions/Peer
Review Form
Homeworks
Important Dates
Exam I Home/Class Data-- Tuesday, February 21st
key/practice exam
Exam II Home/Class Data -- Thursday, April 6th
key/practice exam
Final Exam Home/Class Data -- Thursday, May 9th at 5:15 p.m.
key/final
supplement practice
see the syllabus for a more detailed
calendar
note: the start date of the semester was pushed back a week with no change
to the end date, so all dates on the syllabus and posted here are
tentative and in flux.
Email List
can be gotten through Blackboard
Announcements:
Math Adjunct Office
My voicemail
My Daemen email:
Office hours: see syllabus
MyOpenMath: Course ID: 181998,
Enrollment Key: mccall_324_fall_2023 (same from fall
semester)
Homeworks
Homework #1
Homework #2
Homework #3
Homework #4 --
Data
Homework #5
Homework #6
Homework #7 --
Data/Data
Homework #8
Homework #9 --
Data/Data
Labs
(data files are in .xlsx format)
Instructions for Completing &
Submitting Labs
Lab #1 docx
pdf
Lab #2 docx
pdf
Lab #3 docx
pdf
Data
Lab #4 docx
pdf
Lab #5 docx
pdf
Data
Lab #6 docx
pdf
Data/Data
Lab #7 docx
pdf
Data/Data/Data/Data
Lab #8 docx
pdf
Lab #9 docx
pdf
Lab
#10 docx
pdf
Bonus Lab #1: Non-parametric Regression docx
pdf
Bonus Lab #2: Smoothing Methods
docx pdf
Tutorial
Directions
Journal
Directions
Lecture Notes
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:
Formulas
MLE exercise --
key
Maximum Likelihood Functions (pdf)
-- key
Which Test is This? (pdf)
Venn Diagrams and Set Notation (pdf)
Ven Diagrams and Probability (pdf)
Answer
Keys
Quiz #1 --
key
Quiz #2 --
key/key
Quiz #3 --
key/key
Quiz #4 Data --
key/key
Quiz #5 Data --
key/key
Quiz #6 Data --
key/key
Quiz #7 --
key
Quiz #8 --
key
Quiz #9 --
key/key
Quiz #10 --
key/key
Quiz #11 --
key/key
R files used for keys posted in Blackboard
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
Adding Marginal Distributions to Regression plots with ggplot
Bayesian inference for logistic regression Part 1
4 explainable ML plots
Plotting high density regions
Logistic
Regression for Classification
Easystats: Easily investigate model performance
12 ggplot extensions
Data Viz packages in R
Introduction to Statistical Learning (book)
GLM function
Metrics for uncertainty evaluation in regression
R Cheat Sheet: R for data science workflow
Introduction to Data Mining (course)
Topics in the Mathematics of Data Science (course)
Mathematics for Machine Learning
10 Machine Learning courses
Chart Suggestions Guide
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
Free Courses from Coursera
Confidence
Interval for Rho
Other Statistics courses
Coding
R Tutorials
Spring 2023
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