Question

10		A)	What is the best regression to forecast salary?
10		C)	Are  all variables statistically significant? Did you drop any
	Final	Math Pre req	Hours	Work experience
	94	92	5	Y
	74	90	3	Y
	74	87	4	Y
	76	84	3	N
	66	87	2	N
	80	49	4	Y
	74	42	3	N
	71	61	4	N
	84	81	5	N
	76	67	5	Y
	95	93	4	N
	78	56	5	N
	71	54	3	Y
	82	96	2	N
	65	50	3	N
	77	86	2	N
	78	88	2	Y
	63	78	2	Y
	76	55	5	Y
	71	44	4	Y
	70	80	1	Y
	73	80	4	Y
	62	41	2	Y
	70	69	4	N
	60	51	2	N
	76	79	4	Y
	70	54	2	N
	55	53	1	N
	77	58	5	N
	81	97	2	Y
	59	42	1	N
	95	76	5	N
	59	57	2	Y
	64	57	2	N
	61	80	2	N
	74	65	3	N
	75	87	3	N
	76	42	4	N
	75	67	3	Y
	71	89	3	N
	72	71	3	N
	84	53	5	N
	73	68	2	Y
	83	83	4	N
	57	54	1	N
	79	88	4	Y
	88	90	4	N
	69	93	2	N
	82	76	5	N
	52	46	3	Y
	71	61	2	Y
	66	47	4	N
	69	60	3	N
	74	56	5	N
	62	83	1	Y
	62	41	2	Y
	78	80	4	Y
	66	43	2	Y
	78	41	5	Y
	63	64	2	Y

Answer 1

Dear student, please comment in the case of any doubt and I would love to clarify it.  

A)

Linear regression is the right regression algorithm to forecast salaries.

In Supervised Machine Learning, Regression algorithms help us to build a model by which we can predict the values of a dependent variable from the values of one or more independent variables. For example, predicting future demand for a product based on previous demand.

C)

We know the fact that machine only understands numerical data, we do have numerical data for all the columns except work experience, we will convert it into numbers, we can take Y as 1 and N as 0 here and create the model.

All the variables are relevant here and will be included in the model creation.