Career Tips for DEDP Learners

See how learners may present the education and skills from the DEDP MicroMasters program on their resumes and CVs, and explore other additional resources from the DEDP team.

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Preparation Resources

While there are no formal prerequisites for any of the DEDP courses, some of the courses do require some familiarity with calculus, probability, and statistics. We have compiled resources for learners to refer to should they feel like they need to supplement their coursework or knowledge with additional materials.

Basic Math and Statistics Resources:

• MIT OpenCourseWare | Free Online Course Materials
  • Single Variable Calculus
  • Multivariable Calculus
  • Introduction to Probability and Statistics
  • Probabilistic Systems Analysis and Applied Probability

• Khan Academy’s Probability and statistics
  1. Summarizing quantitative data
  2. Modeling data distributions
  3. Exploring bivariate numerical data
  4. Study Design
  5. Significance Tests (Hypothesis testing)
  6. Advanced Regression (Inference and transforming)
  7. Analysis of Variance (ANOVA)

• Khan Academy’s Differential Calculus
• Khan Academy’s AP/College Calculus AB
• Khan Academy’s AP/College Calculus BC
• Harvard University on edX: Calculus Applied!
• Statistics 110 at Harvard

Basic Economics Resources:

1. Principles Of Microeconomics - MIT OpenCourseWare
2. An Introduction to Linear Regression Analysis
3. Introduction to Regression Analysis: Causal Inference Bootcamp
4. Khan Academy’s AP Microeconomics

R Resources:

A key component of the DEDP program is analyzing data. The DEDP courses use and offer support for R and we have included resources for learning how to use this programming software. These will help you get familiar and comfortable with using R before the course.

Downloading R and RStudio

You can find instructions for how to download R here. We also recommend downloading RStudio, an integrated development environment (IDE) for R, which will make the R interface more user friendly.

Introduction to R

These courses will introduce you to R. The first two are Swirl (interactive in R) courses. Swirl is a software package for R which turns the R console into an interactive learning environment. You will get immediate feedback as you work through self-paced lessons on R programming. You can learn more about it here. Please follow the instructions here to get started!

• A (very) short introduction to R: This is an interactive swirl course which will very briefly introduce you to R
• R Programming: This is an interactive swirl course which will introduce R in a little bit more depth than the previous course.
• R Tutorial for Beginners: Learning R Programming: This tutorial is a complete guide to R for beginners. It will cover everything from basics to advanced topics such as regressions, statistical inference, time series, etc.
• R Orientation Video: This tutorial video walks you through R’s orientation, how to set a working directory, how to import datasets, and some other helpful tips.
• History of Teacup Giraffes: This interactive site uses R to teach the basics of statistics and is also aesthetically pleasing to look at.
• Introduction to Econometrics with R: Once you are comfortable using R, this interactive book is a great way to apply your R skills to concepts taught in the MicroMasters courses.

Useful R Tutorials

These tutorials have interactive components to help you get familiar with performing basic R tasks.

• R Tutorial: Built-in Functions
• R Tutorial: Creating a Graph
• R Tutorials: Basic Functions - Import Data
• R Tutorials: Basic Functions - Assess Data
• R Tutorials: Basic Functions - Manipulate Data
• R Tutorial: Simulations - Sampling, for-loops, and the apply function
• A Gentle Introduction to Tidy Statistics in R: “This one-hour introduction covers how to get started quickly with the basics of research statistics in R, providing an emphasis on reading data into R, exploratory data analysis with the tidyverse, statistical testing with ANOVAs, and finally producing a publication-ready plot in ggplot2. Plus, you’ll find a host of other RStudio webinars and videos to explore via the topic menus on the left side of that page.” (citation)
• ggplot2 (article)
• ggplot (tutorial video)
• Introduction to class lm

Cheatsheets and Quick Resources

1. R cheat sheet: This pdf file has all the most used commands and tasks in R.
2. Table of Useful R Commands: This file has a list of useful commands and how to use them.
3. Data Wrangling with dplyr and tidyr Cheat Sheet
4. Data Visualization with ggplot2 Cheat Sheet
5. R for Beginners by Emmanuel Paradis

Additionally, here is a list of some of the best books on R programming.

Troubleshooting:

The first resource to consult about programming issues is Google. You can simply copy-and-paste the error message or the name of the function you are attempting to use into Google. Adding “R” to your Google search will be helpful in narrowing your results to R, since many programming languages have similar errors and function names.

As you Google, you will see that you are very often led to a forum called Stack Overflow. Stack Overflow is a helpful forum used by programmers to help each other troubleshoot. You can search in the forum to see if your question (or something similar) has been asked and answered before. Adding “[R]” to your search inside the forum will help guide you towards R-tagged entries. Additionally, you can create your own account and post your own questions.Career Tips for DEDP MicroMasters Program LearnersCareer Tips for DEDP MicroMasters Program Learners (1)https://ocw.mit.edu/courses/18-05-introduction-to-probability-and-statistics-spring-2022/