Publications by Karlerik Naslund
Week 9 Lecture
Linear Regression library(tidyverse) ## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ── ## ✔ dplyr 1.1.4 ✔ readr 2.1.5 ## ✔ forcats 1.0.0 ✔ stringr 1.5.1 ## ✔ ggplot2 3.5.1 ✔ tibble 3.2.1 ## ✔ lubridate 1.9.4 ✔ t...
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Homework 4
library(tidyverse) ## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ── ## ✔ dplyr 1.1.4 ✔ readr 2.1.5 ## ✔ forcats 1.0.0 ✔ stringr 1.5.1 ## ✔ ggplot2 3.5.1 ✔ tibble 3.2.1 ## ✔ lubridate 1.9.4 ✔ tidyr 1.3.1 ## ...
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Lecture Week 8
T-TESTING: Differences between groups The essence of hypothesis testing is asking “are there differences between group X and group Y”? Does the group that gets the medicine get well versus the group that doesn’t get the medicine? Does the school with more teachers do better than the school with fewer teachers? Etc. There is a simple way to co...
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Week 7 Lecture
CORRELATION Correlation (as we will be using it, the Pearson Correlation) is a valuable tool to analyze data. Perhaps ironically, it is rarely reported in academic work (typically in favor of different types of regression), however it’s a useful tool when investigating data … as long as you are aware of the dangers. The idea behind correlation ...
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Week 7 Review
Week 7 Review Parametric tests require at least four assumptions: Data (or residuals) are normally distributed Variance is homogenous Interval data (numbers) Variables are independent How to tell if data is normally distributed: # first, visual inspection: hist(mtcars$mpg,probability = T) lines(density(mtcars$mpg),col='red',lwd=2) qqnorm(mtcars...
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Data Selection
library(readxl) library(tidyverse) ## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ── ## ✔ dplyr 1.1.4 ✔ readr 2.1.5 ## ✔ forcats 1.0.0 ✔ stringr 1.5.1 ## ✔ ggplot2 3.5.1 ✔ tibble 3.2.1 ## ✔ lubridate 1.9.4 ✔ tid...
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in class review wk 6
How to load data: Getting Started with Homework Videos Modern Statistics with R, Chapter 2 R for Data Science, Chapter 1 Creating new data frames: library(tidyverse) ## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ── ## ✔ dplyr 1.1.4 ✔ readr 2...
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Week 6 Lecture
Assumptions of linear models (parametric tests): Data (or residuals) are normally distributed Variance is homogeneous (the same) or normalized the errors in the data do not change based on their position within the data (the model is accurate equally across all values) Interval data the data should be continuous and numerical Variables are ind...
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Homework 3
library(tidyverse) ## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ── ## ✔ dplyr 1.1.4 ✔ readr 2.1.5 ## ✔ forcats 1.0.0 ✔ stringr 1.5.1 ## ✔ ggplot2 3.5.1 ✔ tibble 3.2.1 ## ✔ lubridate 1.9.4 ✔ tidyr 1.3.1 ## ...
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Week 4 Lecture
Recap on Dispersion library(tidyverse) ## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ── ## ✔ dplyr 1.1.4 ✔ readr 2.1.5 ## ✔ forcats 1.0.0 ✔ stringr 1.5.1 ## ✔ ggplot2 3.5.1 ✔ tibble 3.2.1 ## ✔ lubridate 1.9.4 ✔...
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