Please answer parts a, b, and c.

Read https://www.statisticshowto.datasciencecentral.com/experimental-design/confounding-variable/

a.) What is confounding variable? Can you give an example?

b.) Why should we control confounding variables in regression? Do you think we should control as many as we can?

c.) Read https://en.wikipedia.org/wiki/Berkson%27s_paradox and http://www.the100.ci/2017/03/14/that-one-weird-third-variable-problem-nobody-ever-mentions-conditioning-on-a-collider/

Now what do you think?