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This is an introductory course to Simple Linear Regression, one of the most basic courses in Statistics.
This course is most suitable for students of professionals with basic knowledge or beginning level in Statistics and R coding. It also fits for anybody who want to explore the field of statistics using R in any discipline.
We will start with an introduction section where I will explain the regression equation with a detailed example. Next, we will cover the essentials of modeling. At this section, I added an emphasis to data cleaning which is essential nowadays with big data issues. Then will follow visualization, modeling and diagnostics.
We will be using R studio which is a nice coding open source environment. R studio is suitable for academic and professional needs.
This course is important in the sense that data analysis needs are constantly growing with the emerging complexity of data. Quick data driven decisions need to be made at the management level. Data Analytics is the most efficient way to get the most accurate information to make decisions.
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Certificate of completion.
|Section 1: Introduction|
|Section 2: Data Analysis|
Data Investigation and Visualization Part 1
Data Investigation and Visualization Part 2
This is the first part of the modeling process where the first model iteration consists of modeling with outliers
Data Modeling Part 2
|Section 3: conclusion|
My name is Oscar Adimi. I tought and tutored a variety of courses such as Statistics and Mathematics for undergraduates.
I have a strong interest and background in Data Analytics and Predictive Modeling. I am currently working in the Insurance Industry and my daily work consists of building actuarial and statistical models.
I received a Master's degree in Mathematics and Actuarial Science at Roosevelt University. I am married and have 2 children. I love basketball and cartoons.