The linear regression model

preview_player
Показать описание

It is time for the actual introduction of regressions! Let's start with some dry theory. A linear regression is a linear approximation of a causal relationship between two or more variables. Regressions models are highly valuable as they are one of the most common ways to make inferences and predictions. The process goes like this: you get sample data, come up with a model that explains the data and then make predictions for the whole population based on the model you have developed. There is a dependent variable labeled Y being predicted and an independent variable labeled x1 x2 and so forth these are the predictors Y is a function of the X variables and the regression model is a linear approximation of this function. The easiest regression model is the simple linear regression y is equal to beta 0 plus beta 1 times X plus Epsilon. Let's see what these values mean. Y is the variable we are trying to predict and is called the dependent. Variable X is the independent variable. When using regression analysis we want to predict the value of y provided. We have the value of x but to have a regression Y must depend on X in some causal way. Whenever there is a change in X such change must translate into a change in Y.

365 Data Science is an online educational career website that offers the incredible opportunity to find your way into the data science world no matter your previous knowledge and experience. We have prepared numerous courses that suit the needs of aspiring BI analysts, Data analysts and Data scientists.

We at 365 Data Science are committed educators who believe that curiosity should not be hindered by inability to access good learning resources. This is why we focus all our efforts on creating high-quality educational content which anyone can access online.

#LinearRegression #Regression #Statistics
Рекомендации по теме
Комментарии
Автор

Man, this is one of the most beautiful videos about statistics I ever saw in my life, I have been studying and working with statistics for years.
Thank you 😊😊

mosama
Автор

This is a great video if you are revising the Linear Regression concept. I wish it were in depth.

vishaljhaveri
Автор

Great video and explanation, unfortunately the references to "causal" relationships is misleading at the least. Just because two variables appear to be related and a regression model can be derived, does not mean either one variable "causes" the other.

danielsirvent
Автор

Working a recommendation system and deciding on the model is so stress.
Linear regression could be my try after gaining the understanding.
Thank

ladyadda
Автор

We take the estimates to cancel out the Error term right

bluebottle
Автор

Why error term is part of regression model??

shahidaziz
Автор

If this was my presentation what will be the title?

pawanjadhav