Can we end hunger and poverty, halt climate change and achieve gender equality in the next 15 years? The governments of the world think we can. Meeting at the uN in September 2015, they agreed to a new set of Global Goals for the...

Today we're going to introduce one of the most flexible statistical tools - the General Linear Model (or GLM). GLMs allow us to create many different models to help describe the world - you see them a lot in science, economics, and...

Today we’re going to talk about data relationships and what we can learn from them. We’ll focus on correlation, which is a measure of how two variables move together, and we’ll also introduce some useful statistical terms you’ve probably...

Here, we will understand dependent and independent variables and learn how to predict values using linear regression.

This video will look at logistic regression in detail, mainly used for classification problems with one or multiple independent variables.

In this video, we will explore overfitting, which is very commonly used in machine learning.

After learning about simple linear regression with two variables, we will now look at multiple linear regression using multiple variables.

In this lecture, you will learn another important metric to determine the quality of our regression using the root mean square error method.

Let's learn more about one significant measure to determine how well our regressions work using the coefficient of determination.

This lesson will teach us an intuitively understandable matrix for how our regression works.

This is a solution to the practice exercise on linear regression analysis.

After learning about linear regression and how to calculate the formula for our regression lines, we will now look at the correlation coefficient or Pearson's coefficient.

In this video, we will understand what machine learning is and get a clear idea about ML (machine learning).
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This clip is from the chapter "Machine Learning and Neurons" of the series "Deep Learning - Artificial Neural...

This video explains geometrical representation.<br<br/>/>

This clip is from the chapter "Linear Regression Analysis" of the series "R Programming for Statistics and Data Science".This section explains linear regression analysis.

In this video, you will learn a practical example of reinforced learning.
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This clip is from the chapter "The Fundamentals of Regression Analysis" of the series "Statistics for Data Science and Business Analysis".This...

This video explains working of the regression model.
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This clip is from the chapter "Machine Learning with Python" of the series "Python in Practice - 15 Projects to Master Python".This section focuses on machine learning with...

This video explains what the course outcomes are.
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This clip is from the chapter "Matplotlib and Seaborn – Libraries and Techniques" of the series "Data Analytics Using Python Visualizations".This section introduces you to...

In this video, the teacher explains how to calculate the line of best fit for a scatter plot using the method of least squares. They discuss different types of functions that can fit scatter plots, such as linear, quadratic, and...

This video discusses how to determine the best statistical regression model to approximate data within a scatter plot and make predictions through interpolation and extrapolation. It covers the process of inputting data into a graphing...

In this video, you will learn about ordinary least squares setting and its practical applications.
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This clip is from the chapter "Subtleties of Regression Analysis" of the series "Statistics for Data Science and Business...

In this video, the geometrical representation of linear regression model is shown.
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This clip is from the chapter "The Fundamentals of Regression Analysis" of the series "Statistics for Data Science and Business...

This video explains the connection between the slope of a regression line and the correlation coefficient by examining standardized variables. It demonstrates how the slope of the regression line quantifies an inexact relationship...

Describes the working principle of a simple linear regression algorithm with an example.

The video teaches how to draw a scatter diagram and make conclusions based on the correlation from that corresponding scatter diagram. Exploratory and response variables are introduced and various types of correlations are explained,...