An important step is to identify relationships among input variables. To measure this relationship, we use the correlation coefficient. Correlation coefficient is a number between +1 and -1. When two variables have a correlation coefficient close to +1, they have a strong positive correlation. A coefficient of exactly +1 indicates a perfect positive fit. A positive correlation between two variables means that both variables increase and decrease their values simultaneously. A correlation coefficient between two variables close to -1 shows that both variables have strong negative correlation. When two variables have a negative correlation, the value of one of the variables increases when the value of the other variable decreases. A correlation coefficient close to 0 or a weak correlation between two variables means that there is no linear relationship between those variables.

Coming back to the Titanic passenger list, I've selected the Explore tab, the Correlation...