Foundations of Data Analysis - Part 1: Statistics Using R

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Foundations of Data Analysis - Part 1: Statistics Using R

Overview

In this first part of a two part course, we’ll walk through the basics of statistical thinking – starting with an interesting question. Then, we’ll learn the correct statistical tool to help answer our question of interest – using R and hands-on Labs. Finally, we’ll learn how to interpret our findings and develop a meaningful conclusion. This course will consist of: Instructional videos for statistical concepts broken down into manageable topics Guided questions to help your understanding of the topic Weekly tutorial videos for using R Scaffolded learning with Pre-Labs (using R), followed by Labs where we will answer specific questions using real-world datasets Weekly wrap-up questions challenging both topic and application knowledge We will cover basic Descriptive Statistics – learning about visualizing and summarizing data, followed by a “Modeling” investigation where we’ll learn about linear, exponential, and logistic functions. We will learn how to interpret and use those functions with basic Pre-Calculus. These two “units” will set the learner up nicely for the second part of the course: Inferential Statistics with a multiple regression cap. Both parts of the course are intended to cover the same material as a typical introductory undergraduate statistics course, with an added twist of modeling. This course is also intentionally devised to be sequential, with each new piece building on the previous topics. Once completed, students should feel comfortable using basic statistical techniques to answer their own questions about their own data, using a widely available statistical software package (R). With these new skills, learners will leave the course with the ability to use basic statistical techniques to answer their own questions about their own data, using a widely available statistical software package (R). Learners from all walks of life can use this course to better understand their data, to make valuable informed decisions.

Course Content

Week One: Introduction to Data

Week Two: Univariate Descriptive Statistics

Week Three: Bivariate Distributions

Week Four: Bivariate Distributions (Categorical Data)

Week Five: Linear Functions

Week Six: Exponential and Logistic Function Models

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About the Author:

Ed Neil O. Maratas is an instructor of Jose Rizal Memorial State University, Dapitan Campus, Philippines as regular status. He earned his Bachelor of Science in Statistics at Mindanao State University-Tawi-Tawi College of Technology and Oceanography in the year 2003 and finished Master of Arts in Mathematics at Jose Rizal Memorial State University year 2009. He Became a researcher, a data analyst, and engaged to several projects linked to the university as data processor.

Prepared by:ednielmaratas@gmail.com or you can visit the facebook pageStatisticss For Funfor more details about statistics.

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