Documentation for CPS Data Used in Chapter 8
Each month the Bureau of Labor Statistics in the U.S. Department of Labor conducts the “Current Population Survey” (CPS), which provides data on labor force characteristics of the population, including the level of employment, unemployment, and earnings. Approximately 65,000 randomly selected U.S. households are surveyed each month. The sample is chosen by randomly selecting addresses from a database comprised of addresses from the most recent decennial census augmented with data on new housing units constructed after the last census. The exact random sampling scheme is rather complicated (first small geographical areas are randomly selected, then housing units within these areas randomly selected); details can be found in the Handbook of Labor Statistics and is described on the Bureau of Labor Statistics website (www.bls.gov).
The survey conducted each March is more detailed than in other months and asks questions about earnings during the previous year. These data are from the March 2009 survey.
Series in Data Set:

Female

1 if female; 0 if male

Age

Age (in Years)

Ahe

Average Hourly Earnings in 2004

Yrseduc

Years of Education

Northeast

1 if from the Northeast, 0 otherwise

Midwest

1 if from the Midwest, 0 otherwise

South

1 if from the South, 0 otherwise

West

1 if from the West, 0 otherwiseEcon 390-03
Assignment 8 (this is the 7th assignment but refers to Module 8)
Due date is Sunday Oct 18th 11:59 PM. Late submissions are not accepted.

YOU SHOULD ONLY AND ONLY WORK WITH RSTUDIO. IF YOU CORRECTLY ANSWER WITH EXCEL IT DOES NOT COUNT.

1. Open the data “ch8_cps” in RStudio
2. Read the description of the data uploaded on Canvas
3. How many variables and how many observations do we have in the data?
4. What is “ahe” and “yrseduc”
5. What are the mean and variance of “yrseduc”.
6. Plot ahe over yrseduc
7. Run a regression of ahe on yrseduc
8. What is the model/population equation here?
9. What is the regression/predicted equation here?
10. What is the effect of yrseduc on ahe?
11. What is the value of predicted ahe for Bob who has 13 yrseduc.
12. What percentage of variation in earnings is explained by years of education (Rsquared)? Why?
13. Is the slope significant? (please provide the null and alternative, the formula of the zscore, and find the conclusion from both approaches, you should also provide the interpretation of the result and what a “significant” or “insignificant” coefficient means.)
14. Provide graph and the regression line in your submission

Please save your r-script and submit it as an attachment on canvas the way you submit other files. You can also save and attach the plot as a PDF file.
I explained all the steps for this assignment in the lecture videos, I just used the Caschool data instead .Data

ahe yrseduc female age northeast midwest south west

13.0769233704 13 1 56 1 0 0 0

38.4615402222 18 0 59 1 0 0 0

62.3931617737 12 0 52 1 0 0 0

21.367521286 18 0 38 1 0 0 0

15.6862745285 14 0 38 1 0 0 0

22.5961532593 13 1 41 1 0 0 0

62.125 13 0 42 1 0 0 0

12.1794872284 12 0 48 1 0 0 0

24.0384616852 14 1 42 1 0 0 0

16.1713294983 16 0 51 1 0 0 0

16.1713294983 16 1 49 1 0 0 0

38.4615402222 16 0 33 1 0 0 0

15.3846149445 14 1 52 1 0 0 0

22.1153850555 14 0 55 1 0 0 0

29.8076915741 12 0 51 1 0 0 0

26.4423084259 12 0 59 1 0 0 0

14.102563858 11 0 52 1 0 0 0

12.5192308426 13 0 44 1 0 0 0

14.4230766296 19 1 37 1 0 0 0

11.2179489136 16 0 59 1 0 0 0

25.6410255432 14 1 35 1 0 0 0

12.5 16 0 31 1 0 0 0

38.4615402222 14 0 44 1 0 0 0

24.0384616852 14 1 41 1 0 0 0

34.1880340576 16 0 46 1 0 0 0

38.4615402222 14 1 45 1 0 0 0

10.2564105988 13 0 24 1 0 0 0

14.4230766296 12 1 59 1 0 0 0

15.3846149445 12 0 57 1 0 0 0

34.1346168518 14 1 33 1 0 0 0

10.8173074722 14 1 41 1 0 0 0

10.096154213 12 0 44 1 0 0 0

22.5961532593 19 0 39 1 0 0 0

9.3406591415 12 1 52 1 0 0 0

12.5 14 0 52 1 0 0 0

10 13 1 34 1 0 0 0

10.5 13 0 37 1 0 0 0

14.890171051 13 1 37 1 0 0 0

60.0961532593 13 1 43 1 0 0 0

11.2179489136 12 1 42 1 0 0 0

24.0384616852 12 0 43 1 0 0 0

11.6230773926 12 1 64 1 0 0 0

12.9355773926 16 0 56 1 0 0 0

21.5705127716 18 0 51 1 0 0 0

24.6153850555 16 0 54 1 0 0 0

19.7916660309 13 0 36 1 0 0 0

21.1538467407 16 1 49 1 0 0 0

19.059135437 12 1 50 1 0 0 0

23.5576915741 16 1 50 1 0 0 0

19.5804195404 18 0 41 1 0 0 0

25 12 0 21 1 0 0 0

12.0192308426 13 0 30 1 0 0 0

16.3461532593 13 1 43 1 0 0 0

7.5128207207 16 1 62 1 0 0 0

7.6923074722 12 0 23 1 0 0 0

14.6853151321 16 1 53 1 0 0 0

2.4038462639 12 0 58 1 0 0 0

4.5673074722 13 0 27 1 0 0 0

14.4230766296 18 1 25 1 0 0 0

55.3846168518 14 0 41 1 0 0 0

11.1888113022 13 0 56 1 0 0 0

12.0192308426 13 1 35 1 0 0 0

6.4497041702 12 0 38 1 0 0 0

13.9423074722 12 0 43 1 0 0 0

9.8571424484 12 0 30 1 0 0 0

5.7692308426 12 1 38 1 0 0 0

4.2735042572 12 0 40 1 0 0 0

22.5961532593 18 1 41 1 0 0 0

8.2417583466 12 0 30 1 0 0 0

26.4957256317 12 0 46 1 0 0 0

17.7884616852 12 0 31 1 0 0 0

10.096154213 12 1 29 1 0 0 0

14.4230766296 12 0 47 1 0 0 0

2.7472527027 12 1 38 1 0 0 0

11.5384616852 14 0 36 1 0 0 0

26.2136745453 12 0 41 1 0 0 0

20.0485572815 16 0 52 1 0 0 0

79.2185287476 18 1 51 1 0 0 0

18.2692298889 12 0 45 1 0 0 0

13.6752138138 12 1 45 1 0 0 0

19.2307701111 12 0 47 1 0 0 0

9.3406591415 12 1 23 1 0 0 0

26.1706733704 16 1 38 1 0 0 0

16.8269233704 13 1 51 1 0 0 0

23.0769233704 14 1 60 1 0 0 0

23.0769233704 14 1 54 1 0 0 0

10.5769233704 12 0 55 1 0 0 0

19.2307701111 12 0 59 1 0 0 0

12.5 9 1 44 1 0 0 0

12.0192308426 13 0 59 1 0 0 0

17.7884616852 16 0 26 1 0 0 0

32.0512809753 16 1 38 1 0 0 0

27.8846149445 12 0 45 1 0 0 0

30.3846149445 16 0 28 1 0 0 0

38.4615402222




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