class 1

---------------------------------------------------------------------------------------

name: <unnamed>

log: C:\Users\Michael\Documents\newer web pages\soc_meth_proj3\fall_2012_381_logs\class1.log

log type: text

opened on: 25 Sep 2012, 13:03:14

* The first thing you should Always do is start a log, in text or “.log” form.

. use "C:\Users\Michael\Documents\newer web pages\soc_meth_proj3\cps_mar_2000_new.dta",clear

* Then open the dataset

. use "C:\Users\Michael\Desktop\cps_mar_2000_new_unchanged.dta", clear

. memory

bytes

--------------------------------------------------------------------

Details of set memory usage

overhead (pointers) 534,840 1.02%

data 14,574,390 27.80%

----------------------------

data + overhead 15,109,230 28.82%

free 37,319,562 71.18%

----------------------------

Total allocated 52,428,792 100.00%

--------------------------------------------------------------------

Other memory usage

set maxvar usage 2,041,738

set matsize usage 1,315,200

programs, saved results, etc. 53,673

---------------

Total 3,410,611

-------------------------------------------------------

Grand total 55,839,403

. describe

Contains data from C:\Users\Michael\Desktop\cps_mar_2000_new_unchanged.dta

obs: 133,710

vars: 55 1 Feb 2009 13:36

size: 15,109,230 (71.2% of memory free)

-------------------------------------------------------------------------------------------------

storage display value

variable name type format label variable label

-------------------------------------------------------------------------------------------------

year int %8.0g yearlbl Survey year

serial long %12.0g seriallbl

Household serial number

hhwt float %9.0g hhwtlbl Household weight

region byte %27.0g regionlbl

Region and division

statefip byte %57.0g statefiplbl

State (FIPS code)

metro byte %27.0g metrolbl Metropolitan central city status

metarea int %50.0g metarealbl

Metropolitan area

ownershp byte %21.0g ownershplbl

Ownership of dwelling

hhincome long %12.0g hhincomelbl

Total household income

pubhous byte %8.0g pubhouslbl

Living in public housing

foodstmp byte %8.0g foodstmplbl

Food stamp recipiency

pernum byte %8.0g pernumlbl

Person number in sample unit

perwt float %9.0g perwtlbl Person weight

momloc byte %8.0g momloclbl

Mother's location in the household

poploc byte %8.0g poploclbl

Father's location in the household

sploc byte %8.0g sploclbl Spouse's location in household

famsize byte %25.0g famsizelbl

Number of own family members in hh

nchild byte %18.0g nchildlbl

Number of own children in household

nchlt5 byte %23.0g nchlt5lbl

Number of own children under age 5 in hh

nsibs byte %18.0g nsibslbl Number of own siblings in household

relate int %34.0g relatelbl

Relationship to household head

age byte %19.0g agelbl Age

sex byte %8.0g sexlbl Sex

race int %37.0g racelbl Race

marst byte %23.0g marstlbl Marital status

popstat byte %14.0g popstatlbl

Adult civilian, armed forces, or child

bpl long %27.0g bpllbl Birthplace

yrimmig int %11.0g yrimmiglbl

Year of immigration

citizen byte %31.0g citizenlbl

Citizenship status

mbpl long %27.0g mbpllbl Mother's birthplace

fbpl long %27.0g fbpllbl Father's birthplace

hispan int %29.0g hispanlbl

Hispanic origin

educ99 byte %38.0g educ99lbl

Educational attainment, 1990

educrec byte %23.0g educreclbl

Educational attainment recode

schlcoll byte %45.0g schlcolllbl

School or college attendance

empstat byte %30.0g empstatlbl

Employment status

occ1990 int %78.0g occ1990lbl

Occupation, 1990 basis

wkswork1 byte %8.0g wkswork1lbl

Weeks worked last year

hrswork byte %8.0g hrsworklbl

Hours worked last week

uhrswork byte %13.0g uhrsworklbl

Usual hours worked per week (last yr)

hourwage int %8.0g hourwagelbl

Hourly wage

union byte %33.0g unionlbl Union membership

inctot long %12.0g Total personal income

incwage long %12.0g Wage and salary income

incss long %12.0g Social Security income

incwelfr long %12.0g Welfare (public assistance) income

vetstat byte %10.0g vetstatlbl

Veteran status

vetlast byte %26.0g vetlastlbl

Veteran's most recent period of service

disabwrk byte %34.0g disabwrklbl

Work disability

health byte %9.0g healthlbl

Health status

inclugh byte %8.0g inclughlbl

Included in employer group health plan last year

himcaid byte %8.0g himcaidlbl

Covered by Medicaid last year

ftotval double %10.0g ftotvallbl

Total family income

perwt_rounded float %9.0g integer perwt, negative values recoded to 0

yrsed float %9.0g based on educrec

-------------------------------------------------------------------------------------------------

Sorted by: race

. tabulate race

Race | Freq. Percent Cum.

--------------------------------------+-----------------------------------

White | 113,475 84.87 84.87

Black/Negro | 13,626 10.19 95.06

American Indian/Aleut/Eskimo | 1,894 1.42 96.47

Asian or Pacific Islander | 4,715 3.53 100.00

--------------------------------------+-----------------------------------

Total | 133,710 100.00

. tabulate race [fweight= perwt_rounded]

Race | Freq. Percent Cum.

--------------------------------------+-----------------------------------

White |224,806,952 82.02 82.02

Black/Negro | 35,508,668 12.96 94.98

American Indian/Aleut/Eskimo | 2,847,473 1.04 96.01

Asian or Pacific Islander | 10,924,728 3.99 100.00

--------------------------------------+-----------------------------------

Total |274,087,821 100.00

* Note that there are 133,710 cases in the dataset (see the top of the describe command, above). And all 133,710 cases have a race. Why? It must be that people who didn’t answer the race question had an answer attributed to them by the Census Bureau.

. summarize perwt_rounded

Variable | Obs Mean Std. Dev. Min Max

-------------+--------------------------------------------------------

perwt_roun~d | 133710 2049.868 1083.244 93 14281

* The CPS is roughly a 1-in-2000 survey.

. tabulate race, nolab

Race | Freq. Percent Cum.

------------+-----------------------------------

100 | 113,475 84.87 84.87

200 | 13,626 10.19 95.06

300 | 1,894 1.42 96.47

650 | 4,715 3.53 100.00

------------+-----------------------------------

Total | 133,710 100.00

* Note that race, like every other variable, is stored numerically. The “white” is just a label put onto the category 100. But also note that you have to know the difference between variables that are numerical but where the numbers just stand in for categories (like race and sex), versus variables whose numbers have units and therefore you can take the average of, like income (dollars) and yrsed (years of education).

. sort sex

. by sex: summarize yrsed

---------------------------------------------------------------------------

-> sex = Male

Variable | Obs Mean Std. Dev. Min Max

-------------+--------------------------------------------------------

yrsed | 49353 12.79632 3.217925 0 17

---------------------------------------------------------------------------

-> sex = Female

Variable | Obs Mean Std. Dev. Min Max

-------------+--------------------------------------------------------

yrsed | 53873 12.75218 3.098084 0 17

. by sex: summarize yrsed if age>=25 & age<=34

---------------------------------------------------------------------------

-> sex = Male

Variable | Obs Mean Std. Dev. Min Max

-------------+--------------------------------------------------------

yrsed | 9027 13.31212 2.967666 0 17

---------------------------------------------------------------------------

-> sex = Female

Variable | Obs Mean Std. Dev. Min Max

-------------+--------------------------------------------------------

yrsed | 9511 13.55657 2.854472 0 17

* If we ask the question: what is the probability that women age 25-34 in the CPS have higher education than men of the same age in the CPS, the answer is: 100%. It is not a statistics question. There are no unknowns. If we ask the question, is this CPS distribution of men’s and women’s education consistent with a null hypothesis that men and women in the US as a whole have equal education, the answer (slightly surprisingly) is NO. The 0.24 years of education difference between men and women in this age group of the CPS is statistically significant. We will talk more about what this means.

. ttest yrsed if age>=25 & age<=34, by(sex)

Two-sample t test with equal variances

------------------------------------------------------------------------------

Group | Obs Mean Std. Err. Std. Dev. [95% Conf. Interval]

---------+--------------------------------------------------------------------

Male | 9027 13.31212 .0312351 2.967666 13.25089 13.37335

Female | 9511 13.55657 .0292693 2.854472 13.49919 13.61394

---------+--------------------------------------------------------------------

combined | 18538 13.43753 .0213921 2.912627 13.3956 13.47946

---------+--------------------------------------------------------------------

diff | -.2444469 .0427623 -.3282649 -.1606289

------------------------------------------------------------------------------

diff = mean(Male) - mean(Female) t = -5.7164

Ho: diff = 0 degrees of freedom = 18536

Ha: diff < 0 Ha: diff != 0 Ha: diff > 0

Pr(T < t) = 0.0000 Pr(|T| > |t|) = 0.0000 Pr(T > t) = 1.0000

. display ttail(18000, 5.716)

5.539e-09