$3)$ Problem Statement: You are required to explore statistical relationships within a dataset by calculating covariance and correlation coefficients. You will use Python to manipulate the data, understand the spread of individual variables, and examine the linear relationships between them. Visual representations of these statistics will be created to provide insights into the data's structure and the nature of the relationships between different pairs of variables. This will provide insights into how different iris characteristics are interrelated, which is crucial for tasks such as feature selection and predictive modeling.

Questions to be answered against the problem statement:

Create Array list of your choice for X and Y with $8$ values.

$1.$ Write the code to calculate and print the variance of a dataset.

$2.$ How do you interpret positive, negative, and zero covariance in a dataset?

$3.$ Describe how to calculate the covariance between two variables and visualize it using a scatter plot.

$4.$ Provide the code to calculate and interpret a perfect positive, a perfect negative, and zero correlation

$5.$ Create a heat map to visualize the Covariance matrix of X and Y$.$