Python programming - Machine Learning using Matplotlib etc.

Use Jupyter notebook or google colab please!

i. Create arrays that represent the values of the x and y axes:

x	y
5	99
7	86
8	87
7	88
2	111
17	86

ii. Execute a method that returns important key values of linear regression: slope, Intercept, r, R, standard error iii. Create a function that uses slope and intercept values to return a new value of y given x. iv. Run each value of the x-array through the function. v. Draw the original scatter plot. vi. Draw the line of regression. vii. Display the scatterplot. 8. Display the histogram. 9. How well does the data fit in a linear regression? 10. Use the function created in (3) to predict future values of y for three (3) x values not given. 11. Display the scatterplot to include the predicted values; highlight the predicted values (use a different legend/colour).