# How to interpret negative correlations on a heatmap (or in general)?

I'm currently running some rudimentary exploratory data analysis on the common Kaggle Titanic survival rate competition, and would like to know how to interpret the following heatmap correlation plot I have made below.

I understand positive correlation (relating to pearsons r-coefficient) - in that as X increases Y also increases and the closer to +1 indicating a strong positive linear relationship.

But for negative correlation values I am quite perplexed as from my understanding (which may be wrong please correct me if so) that the relationship is inverted - so as X increases Y tends to decrease implying if a value has close to -1 then that is a strong negative linear relationship.

I'm struggling with how to interpret this from the heatmap below. The feature that contains the binary outcome I am trying to predict is the feature Survived The rest of the columns are numeric columns that are used for the prediction.

Here we can see that Age/Survived = -0.06 and SibSp/Survived = -0.03

How do i interpret this? Am i correct in saying the following:

• As Age Decreases, Survival Rate Increases (weak negative correlation)
• As SibSp Decreases, Survival Rate Increases (weak negative correlation)

As a side note if the values were -0.90 so close to -1 - how do I word the explanation correctly, would it be as for example: Age decreases then Survival rate increases?