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Teaching an Introductory Data Science course with tidyverse workshop

Wrap up

Dr. Mine Dogucu

2021-12-15

1 / 10

Schedule for the Day

10:00 - 10:15 Introduction and Setup
10:15 - 11:15 Introduction to Toolkit and Data Basics
11:20 - 12:30 Data Visualization
1:00 - 1:45 Data Wrangling
1:45 - 2:15 Packages and External Datasets 2:15 - 2:30 Wrap Up

2 / 10

If we had more time

  • Inference using library(infer).
  • Modeling (linear regression and logistic regression)
  • Git and GitHub (maybe second year of teaching)
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Where to Find Datasets - R Packages

library(fivethirtyeight)
## Some larger datasets need to be installed separately, like senators and
## house_district_forecast. To install these, we recommend you install the
## fivethirtyeightdata package by running:
## install.packages('fivethirtyeightdata', repos =
## 'https://fivethirtyeightdata.github.io/drat/', type = 'source')
library(openintro)
## Loading required package: airports
## Loading required package: cherryblossom
## Loading required package: usdata
##
## Attaching package: 'openintro'
## The following object is masked from 'package:fivethirtyeight':
##
## drug_use
library(titanic)
library(palmerpenguins)
library(bayesrules)
##
## Attaching package: 'bayesrules'
## The following object is masked from 'package:fivethirtyeight':
##
## bechdel

Search for package vignette

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Weekly folder

  • .Rmd file for taking lecture notes
  • .Rmd file for homework
  • .Rmd file for quizzes
  • datasets
  • One .Rproj file per week.
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Making slides with xaringan package

  1. install the package
  2. File -> New File -> R Markdown -> From Template -> Ninja Presentation;
  3. Knit the template
9 / 10

Schedule for the Day

10:00 - 10:15 Introduction and Setup
10:15 - 11:15 Introduction to Toolkit and Data Basics 11:20 - 12:30 Data Visualization
1:00 - 1:45 Data Wrangling
1:45 - 2:15 Packages and External Datasets
2:15 - 2:30 Wrap Up

10 / 10

Schedule for the Day

10:00 - 10:15 Introduction and Setup
10:15 - 11:15 Introduction to Toolkit and Data Basics
11:20 - 12:30 Data Visualization
1:00 - 1:45 Data Wrangling
1:45 - 2:15 Packages and External Datasets 2:15 - 2:30 Wrap Up

2 / 10
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