stats_ch1


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Rrrrrrr Shivers me Timber Its Rrrrr time for some Ere Rrrrrrr

MATH 4753

The Battle of the Bulge

Tiger 2

Where were the tanks made?

The Tiger I and Tiger II tanks were primarily manufactured at the Henschel factory in Kassel, Germany.

Serial numbers

Classical

Bayesian

1,2,3,…,N 𝑚 ෡=𝑚 + 𝑁 −1 𝑘

Tanks left after a battle

3,8,18,50

m = max(sample), k = sample size

𝑚−1 𝑘−1 ෡= 𝑁 𝑘−2

How did the estimation go?

Today (Possibly) 1. 2. 3. 4. 5. 6. 7. 8. 9.

Introduce the course Canvas Syllabus Expectations GIT and GITHUB Clone Intro2R Make R package Lab 1 (Lab order 1,2,3,4,5,6,7,) Chapters 1 and 2 (possibly)

Chapter 1 Dr. Wayne Stewart

Make sure you do the quiz

Chapter 1

Introduction “The role of statistics in data analysis”

You will need to be “competent” in R • This means for this course that you will need to understand • Vectors • Matrices • Data frames • Subsetting • Assignment • Creating Functions • Plotting • Base R • Ggplot

Make sure you clone package “Intro2R”

Install my package devtools::install_github(“https://github.com/MATHSTAT SOU/Intro2R.git”, build_vignettes = TRUE,force = TRUE)

Plenty of resources – mostly labs!!

Free books https://bookdown.org/

New 2024 and continues this semester. Bayesian STATS using STAN https://canvas.ou.edu/courses/222644/pages/help

You will learn the basic Bayesian Algorithm Graphical user interface, text, website Description automatically generated

Types of Data

For our purposes!!

Sampling

> choose(100,5) [1] 75287520

sample(1:100, 5, replace = FALSE) [1] 43 75 58 55 28

Simple Random Sampling

Choose every kth value Random Sampling Designs

Stratified Sampling

Cluster sampling Diagram

https://www.statology.org/cluster-sampling-vs-stratified-sampling/

Description automatically generated

Stratified sampling Diagram Description automatically generated with low confidence

https://www.statology.org/cluster-sampling-vs-stratified-sampling/

Required R skills

Data wrangling

Plotting

Example of sampling: Swiss municipalities

Cluster sampling

View(swiss1)

Stratified sampling

BIAS

Read the examples