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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
- Describe what the Chi-square Tests are and how they work
- Calculate Chi-square tests
- Describe and calculate a one-sample z test
- Calculate t-test and ANOVA by hand
- Articulate how the equations for all tests relate to what we’ve discussed about model building previously
💪🏿 This is what I accomplished my sixth week in the DTSC 550 course:
📘 Chapter 12 goes over:
- Categorical Analyses
📘 Chapter 13 goes over:
- Comparing Two Means
📘 Chapter 14 goes over:
- Comparing More than Two Means
📺 Videos watched (some videos have a 1 question quiz at the end):
Chi Square Goodness Of Fit
Loading the ‘cards’ CSV into R
Chi Square Goodness Of Fit Part 2
Chi Square Goodness Of Fit Part 3
Chi Square Test of Independence Part 1
Chi Square Test of Independence Part 2
Chi Square Test of Independence Example
t distribution
Inference for a mean
Inference for paired data
t test part 1
Independent Samples t-test: Math - Quiz (08:27)
Independent Samples t test: How It Works - Quiz (06:47)
Independent T-Test Example
Introduction to ANOVA
ANOVA Introduction
ANOVA Part 2: Math
Multiple comparisons
ANOVA Practice Problems
t-Test Practice Problems: I was given four different datasets and I had to calculate the t-statistic by hand, calculate the degrees of freedom, determine the critical t-value, interpret the results
ANOVA Practice Problems: I needed to figure out which hypothesis is supported, calculate the total sum of squares, calculate the model sum of squares, calculate simple linear regression, compute degrees of freedom, calculate mean squares, calculate F value, find critical value
💯 Exam
- Module exam had 21 questions: fill in the blank, true/false, and multiple choice with one answer. It was heavy on true/false which was nice. This test looked easy but was difficult even with the true/false questions. Tricky wording! No 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 5 times. Final score was 87.04%. You have until the end of the semester to take all your exams.
🔥 Summary
- I really enjoyed the practice problems since last week didn’t have any. This week had a short test, but could have been longer for reinforcement.
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 3? Week 3
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.