My Final (7th) Week In Eastern University's Master's In Data Science DTSC550

Week 7

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Looking for DTSC 550 week 1? Week 1
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Looking for DTSC 550 week 4? Week 4
Looking for DTSC 550 week 5? Week 5
Looking for DTSC 550 week 6? Week 6

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.

💡 Learning Objectives

Articulate what least squares regression is
Calculate linear regression by hand
Select the best linear regression models

💪🏿 This is what I accomplished my final (7th) week in the DTSC 550 course:

📘 Chapter 5 goes over:

Correlation

📘 Chapter 15 and 16 goes over:

Linear Regression
Factorial ANOVA

📺 Videos watched (some videos have a 1 question quiz at the end):

Correlation, part 1
Correlation, part 2
Correlation, part 3
Regression-basics
Regression intro (03:19)
The model (08:46)
Causality (12:13)
Least squares (06:08)
Regression-math
The math (08:29)
Regression interpretation (02:52)
More R and model fit (06:40)
Regression with categorical predictors (07:26)
Multiple regression
R Intro Lab 5 Video Solution, Part 1 (08:29)
R Intro Lab 5 Video Solution, Part 2 (10:01)
R Intro Lab 5 Video Solution, Part 3 (11:07)
R Intro Lab 5 Video Solution, Part 4

🧪 Labs

Correlation Practice Problems where I was given 3 datasets and had to calculate the correlation between the two variables using both the covariance method and the computational method.
Regression Practice Problems where I was given 3 datasets and had to produce the regression equation for u predicting v and a graph of the regression equation for u predicting v using -1SD, X, and +1SD.
R Intro Lab 5 where I had to explore, visualize, clean, and model Texas housing data
CG Lab 5 where I explored the dataset, visualized variables of interest, cleaned the data, and modeled the data.

💯 Exam

Module exam had 26 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 3 times. Final score was 100%. You have until the end of the semester to take all your exams.

Week 7

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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.