Class Lecture
Traditional Statistics methods can conducted using either linear or logistic regression.
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It is the study of variation and randomness!
INFERENCE
Use our sample data to understand the larger population.
The data will tell us how the population generally behaves.
The data will guide us in the differences in units.
Data will tell us if there is a signal or just noise.
When conducting a study, literature review and study design are as equally important as statistics.
If you don’t see variability in the data, something is wrong.
Focus on consistency in the methodology, not consistency in data.
Understand that you can be wrong, and that is okay.
Don’t let data influence the methodology during a study/experiment.
All models are wrong,
some are useful!
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Introduction to Data Science
Dr. Catalina Medina
MW 3-4:15 PM
TTH: 1:30-2:45 PM
Programming for Data Science
Dr. Alona Kryshchenko
TTH 3-4:15 PM
Mathematics for Data Science
Dr. Cynthia Flores
MW 2-3:50 PM
https://cloud.r-project.org/
https://learn.microsoft.com/en-us/cpp/windows/latest-supported-vc-redist?view=msvc-170#latest-supported-redistributable-version
https://positron.posit.co/install.html
Scripts
Console
Environment
Files
Everything else
install.packages("tidyverse")
install.packages('csucistats', repos = c('https://inqs909.r-universe.dev', 'https://cloud.r-project.org'))
install.packages(c("ggthemes", "statmod", "car", "ggtext", "ggpubr", "lmtest", "rms", "palmerpenguins"))
library(tidyverse) library(csucistats) library(ggthemes) library(ggtext) library(ggpubr) library(ThemePark) library(car) library(lmtest) library(rms) library(palmerpenguins)
u1 <- "https://www.inqs.info/p/plotathon/owenWilsonWows.csv" u2 <- "https://www.inqs.info/p/plotathon/owenWilsonWows.xlsx" download.file(u1, file.path(getwd(), basename(u1))) download.file(u2, file.path(getwd(), basename(u2)))
