FIEL DIARIES #11

 Date: 12-03-2021

Topic:  Correlation Coefficient

Objective: Analyze the formulas, techniques and strategies to make decisions with the correlation coefficient.

Shared resources

Book

Excel and the floating point problem

Determination coefficient

In statistics, the coefficient of determination, called R² and pronounced R squared, is a statistic used in the context of a statistical model whose main objective is to predict future results or test a hypothesis.

The coefficient of determination is the proportion of the total variance of the variable explained by the regression. It is also called R squared and it serves to reflect the goodness of fit of a model to the variable that it is intended to explain.

Correlation coefficient

In statistics, Pearson's correlation coefficient is a measure of linear dependence between two quantitative random variables. Unlike the covariance, the Pearson correlation is independent of the measurement scale of the variables.

The correlation coefficient is the specific measure that quantifies the intensity of the linear relationship between two variables in a correlation analysis.

The correlation coefficient is a measure that allows knowing the degree of linear association between two quantitative variables (X, Y). In the next.

Personal conclusions:

In conclusion, today's class learned about the coefficient of determination and the correlation coefficient to know the proportion of the total variance of the variable explained by the regression.

Task:

Watch the movie and make ten thoughts on how this could happen to decision-making in the context of hospitality and tourism.