the dataset is from:

https://www.princeton.edu/~mwatson/Stock-Watson_4E/Stock-Watson-Resources-4e.html

its the CPS2015 (Used in EE 8.2) dataset

1. Create a table with summary statistics for all variables in the dataset.
2. Run a regression of average hourly earnings (AHE) on age (Age), sex (Female), and education (Bachelor). If Age increases from 25 to 26, how are earnings expected to change? If Age increases from 33 to 34, how are earnings expected to change? (
3. Run a regression of the logarithm of average hourly earnings, ln(AHE), on Age, Female, and Bachelor. If Age increases from 25 to 26, how are earnings expected to change? If Age increases from 33 to 34, how are earnings expected to change?
4. Run a regression of the logarithm of average hourly earnings, ln(AHE), on ln(Age), Female, and Bachelor. If Age increases from 25 to 26, how are earnings expected to change? If Age increases from 33 to 34, how are earnings expected to change?
5. Run a regression of the logarithm of average hourly earnings, ln(AHE), on Age, Age2, Female, and Bachelor. If Age increases from 25 to 26, how are earnings expected to change? If Age increases from 33 to 34, how are earnings expected to change?
6. Create a table with all four models, including robust standard errors.

I need help with these questions and how I can run them in R studio.