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Data Analysis for Researchers

About

This is an extended lecture note of a course jointly taught mainly with Professor Taisei Kaizoji in the Winter term AY2020-AY2023. It is a ten-week course with two periods a week; one period is 70 minutes. This note mainly covers the contents of week two to week six, which I taught. Professor Kaizoji introduced and provided examples, somewhat related to his specialty Macroeconomics. By his request, I included work to recreate charts in the executive summary of the World Inequality Report 2022.

PART I, The Introduction, basically consists of the course contents presented in class and my responses to assignments two to five. The first assignment is in Chapter 1, Introduction.

PART II is the basics of exploratory data analysis, abbreviated as EDA, summarized in several components. There are overlaps with the contents scattered around in PART I.

PART III explains the data source we mainly used in class: World Development Indicators of the World Bank, Our World in Data, OECD, and UN Data. As an introduction, we often used the package WDI to search and download the World Development Indicator data.

In APPENDICES, we included miscellaneous topics closely related to the contents of this lecture note.

The package tidyverse

We focused on the tidyvese packages, which includes ggplot2, dplyr, tidyr, readr and tibble, and did not use other packages unless it is crucial. As you can see below, other packages are automatically attached when we load tidyverse by library(tidyverse) However, some packages installed with tidyverse need to be loaded when they are necessary. The package readxl for Excel is one of them.

library(tidyverse)
#> ── Attaching core tidyverse packages ──── tidyverse 2.0.0 ──
#> ✔ dplyr     1.1.3     ✔ readr     2.1.4
#> ✔ forcats   1.0.0     ✔ stringr   1.5.0
#> ✔ ggplot2   3.4.4     ✔ tibble    3.2.1
#> ✔ lubridate 1.9.3     ✔ tidyr     1.3.0
#> ✔ purrr     1.0.2     
#> ── Conflicts ────────────────────── tidyverse_conflicts() ──
#> ✖ dplyr::filter() masks stats::filter()
#> ✖ dplyr::lag()    masks stats::lag()
#> ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

The package bookdown

We used the bookdown package to create this page with bs4_book style of bootstrap4. See the Bookdown book for the detail.