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**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 2? Week 2****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.

โ๐ฟ 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:ย 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. ๐ด I believe a lot can be cut out. Just give me the facts and move on.

๐ก Learning Objectives

- Understand the distinction between measures of central tendency and measures of variability
- Calculate and define each measure of central tendency and variability
- Describe how the mean is the first model weโll discuss, and how we can assess it
- Demonstrate an elementary understanding of probability
- Articulate why understanding distributions is important
- Identify ways distributions can differ
- Describe the normal and binomial distributions

๐ช๐ฟ This is what I accomplished my third week in the DTSC 550 course:

๐ Chapter 5 goes over:

- Descriptives

๐ Chapter 9 goes over:

- Probability

๐ Chapter 6 goes over:

- Graphs

๐บ Videos watched (each video has a 1 question quiz at the end):

- Descriptives:
- Central Tendency
- Variability
- Connections
- Skew And Kurtosis
- Standard Scores

- Probability
- Probability Introduction
- What is Probability
- Probability Basics Part 1
- Probability Basics Part 2
- Probability Distribution Overview
- Binomial Distribution Part 1
- Binomial Distribution Part 2
- Normal Distributions Part 1
- Normal Distributions Part 2
- Other Distributions

- Graphs
- Intro to Plots
- Plots

๐งช Labs

- 2 Practices lab with the answers: mean, median, min, max, range, variance, standard deviation, summary, z-score of a loaded dataset
- Descriptive Statistics practice problems: Calculated the mean, median, mode, range, variance, and standard deviation for 3 datasets using RStudio and the programming language R.

๐ฏ Exam

- Module exam had 31 questions: fill in the blank, true/false, and multiple choice (some with more than one answer). It was heavy on the graphs from chapter 6, so study that deeply. I had to do a few calculations using R in R Studio. 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 five times. Final score was 85%. I’m noticing for the fill in the blank questions I’m not typing it exactly how the system wants it. For example, I put equal to one when it should have been just one. ๐ 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 2? Week 2****Looking for DTSC 550 week 4? Week 4****Looking for DTSC 550 week 5? Week 5**

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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.