💓 If you enjoyed the information and the web site, please donate or become a Patreon.
🌍 Love to travel? Check out Booking.com for all your travel needs.
Want to know why I decided to pursue a Master’s in Data Science? Go here
Looking for DTSC 550 week 1? Week 1
Looking for DTSC 550 week 3? Week 3
Looking for DTSC 550 week 4? Week 4
Looking for DTSC 550 week 5? Week 5
For my first course, I am taking DTSC 550 Introduction to Statistical Modeling. It’s the first course on utilizing the programming language R.
✍🏿 Here’s a description of the course:
- Introduction to foundational concepts, theories, and techniques of statistical analysis for data science. Students will begin with descriptive statistics and probability, and advance through multiple and logistic regression. Students will also conduct analyses in R. This course is approachable for students with little statistical background and prepares them for DTSC 650: Data Analytics in R
The book we are using is free and located here. I’m not saying the book is bad because I’m only one chapter in, but it reads like someone is talking. It’s a little too wordy for me. 😴 I believe a lot can be cut out. Just give me the facts and move on.
💪🏿 This is what I accomplished my second week in the DTSC 550 course:
📘 Chapter 2 goes over:
- A brief introduction to research design (the same topics listed below mirror the book)
📘 Chapter 4 goes over:
- Additional R concepts (the same topics listed below mirror the book)
📺 Videos watched (each video has a 1 question quiz at the end):
- Research Design:
- Overall Types of Data
- Level of Measurement
- Nominal Data
- Ordinal Data
- Interval Data
- Ratio Data
- Non-Numeric Coded as Numeric
- Continuity
- Observational Studies and Sampling Strategies
- Designing Experiments
- Operationalization
- Classical Test Theory
- Reliability
- Predictor Outcomes
- Validity
- Confounds
- Additional R Concepts
- Comments
- Load a package
- Unload a package
- Download and install new packages
- Ran into a problem with the environment variable
- Updating packages
- Loading and saving data (.csv)
- Factors
- Data frames
- Lists
- Formulas
- Generic functions
- Help menu and other resources (rseek.org, r-project.org)
- Vectors, Functions, and Help
- Packages
- Workspace
- More to Know
🧪 Labs
- 4 different labs that reinforced the concepts with the answers given with walkthrough videos on how to do it. I really like learning R and the labs definitely reinforce the concepts from the book.
💯 Exam
- Module exam had 36 questions: fill in the blank, true/false, and multiple choice (some with more than one answer). You can take the exam as many times as needed to get the score you want, but each test has different questions. I took the exam twice. First score was 70% and second was 80%. I’ll see how the rest of the course progresses with my grades before I decide to take it again. You have until the end of the semester to take all your exams.
Want to know why I decided to pursue a Master’s in Data Science? Go here
Looking for DTSC 550 week 1? Week 1
Looking for DTSC 550 week 3? Week 3
Looking for DTSC 550 week 4? Week 4
Looking for DTSC 550 week 5? Week 5
💓 If you enjoyed the information and the web site, please donate or become a Patreon.
⚡ Use NordVPN for the protection you need when surfing the web. One of the few providers that have a dedicated IP address you can buy to increase your safety.
Elyse Y. Robinson is the Founder of Switch Into Tech where she does monthly seminars, posts weekly freebies to help you switch into tech, Writer of Nube: Switch Into A Cloud Career, podcaster for Nobody Wants To Work Tho, creator of FullTuitionScholarships.org to help you not go into college debt, and in school for Data Science. Elyse is in love with Mexico, researching any and everything, and helping people switch into tech.