4.7 out of 5
4.7
199 reviews on Udemy

Learn Statistics and Regression Modeling for Data Science

Learn statistics and build regression models step by step through real business scenarios
Instructor:
Data Science Guide
552 students enrolled
English [Auto]
Learn about different types of Regression Models and their use
Run Regression Analysis in several computer applications
Learn in detail to build Linear Regression Model and Logistic Model which are highly used in business analysis
Interpret the results of the Regression Analysis and translate them to business recommendations
Build Regression Models and use them in your business
Assess quality and efficiency of your model using several measures and indicators
Hands on three real business scenarios

A complete hands on practical exercises to learn statistics and build regression models which are highly used in business data analysis. This course is designed to start with the very basics and then add up information gradually till the professional level.  Accordingly students who have fair background in statistics can choose to jump to the practical part of the course to learn building regression models in detail. 

In this course you will learn descriptive and inference statistics, such as central and variability measures, visualize data, calculate confidence intervals and test hypotheses. Furthermore,  you will learn to build different types of regression models and use them in data analysis. You will start first with Simple Linear Regression. After that Multiple Linear Regression when you use several independent variables to predict target values. After that you will learn Logistic Regression for classification. You will learn step by step how to understand a business problem from data observations and determine the variables you need to include in the regression analysis.

You will also learn how to interpret model coefficients from business point of view and assess regression model’s prediction power using several indicators, such as: R-squared and p-value. After that you will be able  to prepare your business recommendations that can be used by decision makers.  You will learn using important data analysis applications like Microsoft Excel, Gretl and R.

Introduction to Statistics

1
Introduction to the Course
2
Control the Pace of a Lesson
3
What is Statistics
4
Sample And Population
5
Sample and population
6
Descriptive and Inferential Statistics
7
Descriptive and Inferential Statistics
8
Descriptive and Inferential Statistics
9
Data Types
10
Data Types
11
Data Types
12
Visualize Data
13
Histogram
14
Central Tendency Measures
15
Variability Measures
16
Calculate Central and Variability Measures (Practical)
17
Symmetry and skewness in Data
18
Symmetry and skewness in Data
19
Symmetry and skewness in Data
20
Correlation and Covariance
21
Correlation and Covariance
22
Course Rating

Inferential Statistics

1
Introduction to Inferential Statistics
2
Discrete Probability Distributions
3
Normal Distribution
4
Normal Distribution
5
Variable standardization Demo

Link to Interactive Mathematics Website:

https://www.intmath.com/counting-probability/normal-distribution-graph-interactive.php

6
Normal Distribution
7
Variable standardization
8
Variable standardization
9
Link to the Website Demo

Central Limit Theorem

1
Introduction to Central Limit Theorem
2
Central Limit Theorem
3
Estimators
4
Estimators
5
Central Limit Theorem
6
Introduction to Confidence Interval
7
Calculate Confidence Interval for one Sample with a Known Population Variance
8
Calculate Confidence Interval
9
Introduction to the Business Problem
10
Calculate Confidence Interval in Excel
11
t - Distribution
12
Student and Normal Distributions
13
Calculate Confidence Interval for one Sample with a Unknown Population Variance
14
Reduce Margin of Error
15
Confidence Interval for two Dependent Samples
16
Calculate Confidence Interval for two Dependent Samples in Excel
17
Confidence Interval for two Independent Samples with a Known Population Variance
18
Calculate Confidence Interval for two Independent Samples Known Var in Excel
19
Confidence Interval for two Independent Samples Unknown Population Variance

Statistical Hypothesis Testing

1
What is a Statistical Hypothesis
2
Types of Hypotheses
3
P-Value
4
Link to z-value Calculator
5
Testing a Hypothesis for one Sample, Variance is Known
6
Testing the Hypothesis in Excel
7
Testing a Hypothesis for one Sample, Variance is Unknown
8
Testing a Hypothesis for two Dependent Samples
9
Link to t-value Calculator
10
Testing a Hypothesis for two Independent Samples, Variance is Known
11
Testing a Hypothesis for two Independent Samples, Variance is Unknown

Introduction to Regression Model

1
Regression Model
2
Predictors
3
Run Descriptive Simple Statistics and Understand Scatter Plot
4
Regression Slop and Residuals
5
Ordinary Least Squares
6
Verifying Significance of Predictors
7
When the predictor variable is considered significant?
8
R_Squared
9
R_Squared
10
Types of Regressions
11
Course Rating

Simple Linear Regression Analysis

1
Stats Applications
2
Install gretl
3
Build Simple Linear Regression in Gretl
4
Build Simple Linear Regression in Excel
5
Introduction to R
6
Install R
7
Install R Studio
8
Overview on R Studio
9
How to use ~ symbol
10
Build Simple Linear Regression in R
11
Get the Predicted Salaries
12
Visualize the Model

Multiple Linear Regression Analysis

1
What is Multiple Linear Regression
2
Dummy Variables
3
Assumptions of Multiple Linear Regression
4
Stepwise Approach
5
Overview on the Business Problem
6
Test Multicollinearity between Independent Variables
7
Build Multiple Linear Regression in Gretl - 1
8
Build Multiple Linear Regression in Gretl - 2
9
Coefficients Interpretation
You can view and review the lecture materials indefinitely, like an on-demand channel.
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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199 Ratings

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Includes

5 hours on-demand video
5 articles
Full lifetime access
Access on mobile and TV
Certificate of Completion
Learn Statistics and Regression Modeling for Data Science
Price:
$29.98 $24

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