StatCrunch logo (home)

Data sets shared by StatCrunch members
Showing 1 to 15 of 45 data sets matching LABOR
Data Set/Description Owner Last edited Size Views
US Workforce Participation
This data primarily comes from two sources: Federal Reserve Bank of St. Louis and the US Bureau of Labor Statistics .
ColumnDescription
YearThe calendar year for each value
Annual Average Workforce ParticipationDefined by the Bureau of Labor Statistics as "the percentage of the population [16 years and older] that is either employed or unemployed (that is, either working or actively seeking work). Note that 2015's Annual Average is calculated using the first 11 months."
Male Workforce Participation RateAnnual workforce participation rate for males.
Female Workforce Participation RateAnnual workforce participation rate for females.
Male Inactivity Rate Aged 25-54Defined as the proportion of the male population aged 25-54 that is not in the labour force. Common reasons for leaving labour force: college, retirement, stay at home, can't find work and no longer try.
Change in Rate (Male Inactivity Rate Aged 25-54)The change in the inactivity rate calculated as the current year minus the previous year.
Female Inactivity Rate Aged 25-54Defined as the proportion of the female population aged 25-54 that is not in the labour force.
Change in Rate (Female Inactivity Rate Aged 25-54)The change in the inactivity rate calculated as the current year minus the previous year.
Presidential ControlPolitical party of president.
Senate ControlPolitical party of the Senate majority
House ControlPolitical party of the House of Representatives majority.
Legislative Branch (House and Senate)Combined control of Senate and House of Representativs
statcrunch_featuredJun 27, 201710KB2194
USDA Nutrition Data
This dataset has the nutritional values per serving size for a large variety of foods as calculated by the USDA.

US Department of Agriculture, Agricultural Research Service, Nutrient Data Laboratory. USDA National Nutrient Database for Standard Reference, Release 28. Version Current: September 2015. Internet: http://www.ars.usda.gov/nea/bhnrc/ndl
statcrunchhelpJan 13, 2016832KB1590
Federal Food Assistance Participation
This primarily comes from the following source: United States Department of Agriculture: Food and Nutrition Service . This dataset also incorporates data from another StatCrunch dataset: US Workforce Participation

ColumnDescription
YearThe year for each data value
Average Federal Food Assistance Participation in ThousandsNumber of individuals in the US who took part in SNAP (Supplemental Nutrition Assistance Program) during the given year.
% US Population on Federal Food Assitance% of US population that is currently in the SNAP program and is receiving aid with food.
Change of % (US Population on Federal Food Assistance)The change in the percentage of the US population that is receiving food assistance from SNAP.
Presidential ControlPolitical party of president.
Senate ControlPolitical party of the Senate majority
House ControlPolitical party of the House of Representatives majority.
Legislative Branch (House and Senate)Combined control of Senate and House of Representativs
Male Inactivity Rate Aged 25-54Defined as the proportion of the male population aged 25-54 that is not in the labour force. Common reasons for leaving labour force: college, retirement, stay at home, can't find work and no longer try.
Change of Rate (Male Inactivity Rate Aged 25-54)The change in the inactivity rate calculated as the current year minus the previous year.
Female Inactivity Rate Aged 25-54Defined as the proportion of the female population aged 25-54 that is not in the labour force.
Change of Rate (Female Inactivity Rate Aged 25-54)The change in the inactivity rate calculated as the current year minus the previous year.
Annual Average Workforce Participation RateDefined by the Bureau of Labor Statistics as "the percentage of the population [16 years and older] that is either employed or unemployed (that is, either working or actively seeking work). Note that 2015's Annual Average is calculated using the first 11 months."
Change of Rate (Annual Workforce Participation Rate)The change in the workforce participation rate calculated as the current year minus the previous year.
statcrunchhelpJan 8, 201610KB1673
Top Rated Jobs 2014
This data is gathered from careercast.com and is available in it's original form at the source listed above. The dataset originally was created by Keisha Brown from Georgia Perimeter College.

ColumnDescription
Ranking Ranking from 0 to 200 based on the combined “Overall Rating”
JobTitle for the job.
Median Annual IncomeBased on Bureau of Labor Statistics
Overall RatingCombined rating based on income, stress, hiring outlook, and work environment. The lower the rating the better rated the job.
Stress RatingA rating from 1 to 200 estimating the overall stress level from the job. This essentially is a ranking with 1 being the least stressful job and 200 being the most stressful job.
Hiring Outlook Rating A rating from 1 to 200 estimating the overall stress level from the job. This essentially is a ranking with 1 being the best hiring outlook and 200 being the worst hiring outlook.
Work Environment Rating A rating from 1 to 200 estimating the overall stress level from the job. This essentially is a ranking with 1 being the best work environment and 200 being the worst work environment.
statcrunchhelpMar 14, 20169KB2594
Economics and Policy.xls
Growth RGDP: RGDP is real gross domestic product. The growth in real gross domestic product is the common measure of a country's economic health. Unemployment Rate: The number of unemployed people divided by the number of people in the labor force. The labor force includes only those who have a job or who are seeking a job. Employment Rate: The number of employed people divided by the working age population. The working age population includes all people from age 15 to 64, regardless of whether or not they are in the labor force. Federal Revenue per GDP: The total amount of money the Federal government receives expressed as a fraction of the size of the economy (GDP). Federal Spending per GDP: The total amount of money the Federal government spends expressed as a fraction of the size of the economy (GDP). Federal Debt per GDP: The total Federal debt expressed as a fraction of the size of the economy (GDP). Here, Federal debt includes both public debt outstanding (money the Federal government has borrowed from people, companies, and foreign governments) and intergovernmental debt (money the Federal government has borrowed from the Social Security trust fund). Top Federal Income Tax Rate: The Federal income tax rate paid by those in the highest tax bracket. Recession: This variable is 1 if the country was in recession in the indicated year and 0 otherwise. Democratic President: This variable is 1 if the President was a Democrat, 0 if the President was a Republican. Seats in House Held by Democrats: The number of Democrats in the House of Representative as a fraction of the total number of Representatives. Due to a small number of independents, the fraction of seats held by Republicans is approximately (but not exactly) one minus the fraction of seats held by Democrats. Seats in Senate Held by Democrats: The number of Democrats in the Senate as a fraction of the total number of Senators. Due to a small number of independents, the fraction of seats held by Republicans is approximately (but not exactly) one minus the fraction of seats held by Democrats. War: This variable is 1 if the country was at war, 0 otherwise.
adaviesNov 2, 20108KB1387
Low Birth Weight Study
SOURCE: Hosmer and Lemeshow (2000) Applied Logistic Regression: Second Edition Data were collected at Baystate Medical Center, Springfield, Massachusetts during 1986. DESCRIPTIVE ABSTRACT: The goal of this study was to identify risk factors associated with giving birth to a low birth weight baby (weighing less than 2500 grams). Data were collected on 189 women, 59 of which had low birth weight babies and 130 of which had normal birth weight babies. Four variables which were thought to be of importance were age, weight of the subject at her last menstrual period, race, and the number of physician visits during the first trimester of pregnancy. LIST OF VARIABLES: Columns Variable Abbreviation ----------------------------------------------------------------------------- 2-4 Identification Code ID 10 Low Birth Weight (0 = Birth Weight >= 2500g, LOW 1 = Birth Weight < 2500g) 17-18 Age of the Mother in Years AGE 23-25 Weight in Pounds at the Last Menstrual Period LWT 32 Race (1 = White, 2 = Black, 3 = Other) RACE 40 Smoking Status During Pregnancy (1 = Yes, 0 = No) SMOKE 48 History of Premature Labor (0 = None 1 = One, etc.) PTL 55 History of Hypertension (1 = Yes, 0 = No) HT 61 Presence of Uterine Irritability (1 = Yes, 0 = No) UI 67 Number of Physician Visits During the First Trimester FTV (0 = None, 1 = One, 2 = Two, etc.) 73-76 Birth Weight in Grams BWT ----------------------------------------------------------------------------- PEDAGOGICAL NOTES: These data have been used as an example of fitting a multiple logistic regression model. STORY BEHIND THE DATA: Low birth weight is an outcome that has been of concern to physicians for years. This is due to the fact that infant mortality rates and birth defect rates are very high for low birth weight babies. A woman's behavior during pregnancy (including diet, smoking habits, and receiving prenatal care) can greatly alter the chances of carrying the baby to term and, consequently, of delivering a baby of normal birth weight. The variables identified in the code sheet given in the table have been shown to be associated with low birth weight in the obstetrical literature. The goal of the current study was to ascertain if these variables were important in the population being served by the medical center where the data were collected. References: 1. Hosmer and Lemeshow, Applied Logistic Regression, Wiley, (1989).
wikipetersonJul 23, 20126KB7199
US Workforce Participation
This data primarily comes from two sources: Federal Reserve Bank of St. Louis and the US Bureau of Labor Statistics .
ColumnDescription
YearThe calendar year for each value
Annual Average Workforce ParticipationDefined by the Bureau of Labor Statistics as "the percentage of the population [16 years and older] that is either employed or unemployed (that is, either working or actively seeking work). Note that 2015's Annual Average is calculated using the first 11 months."
Male Workforce Participation RateAnnual workforce participation rate for males.
Female Workforce Participation RateAnnual workforce participation rate for females.
Male Inactivity Rate Aged 25-54Defined as the proportion of the male population aged 25-54 that is not in the labour force. Common reasons for leaving labour force: college, retirement, stay at home, can't find work and no longer try.
Change in Rate (Male Inactivity Rate Aged 25-54)The change in the inactivity rate calculated as the current year minus the previous year.
Female Inactivity Rate Aged 25-54Defined as the proportion of the female population aged 25-54 that is not in the labour force.
Change in Rate (Female Inactivity Rate Aged 25-54)The change in the inactivity rate calculated as the current year minus the previous year.
Presidential ControlPolitical party of president.
Senate ControlPolitical party of the Senate majority
House ControlPolitical party of the House of Representatives majority.
Legislative Branch (House and Senate)Combined control of Senate and House of Representativs
statcrunchhelpJan 7, 201610KB742
atus.csv
Large random sample of people asked to keep a time-use diary on a randomly chosen day of the year; First few columns are demographic variables, after which are variables that provide the number of minutes that person spent on a given activity during the day. Only a few activities from the complete survey (done by the Bureau of Labor Statistics) are provided.
rgouldJun 17, 20144MB506
CPI
6-14-2012 U.S. Department Of Labor Bureau of Labor Statistics Washington, D.C. 20212 Consumer Price Index All Urban Consumers - (CPI-U) U.S. city average All items 1982-84=100
sbroadJul 16, 20128KB255
edit#gid=0
As part of the Math Leadership Corp (MLC) collaborative process, Teachers continually use student formative and summative data to improve their instructional practice and influence their colleagues through research informed coaching, co-planning, classroom observations, demonstrations and critical reflection of practice. Being part of the MLC program, Ms. Garcia’s has researched the role that questioning plays in the classroom from a students’ perspective. Using research she read from Make One Change, teach students to ask questions, she has decided to teach “students, rather than teachers, assume responsibility for posing questions”. She will gather categorical data to see if 80% of 8th grade students feel that asking questions in a math classroom is helpful and whether their is a relationship between asking questions and higher performance on math assessments. The first and second column: I found that posing and asking questions is helpful Helpful (1) just another thing to do (2) not helpful (0) I found that taking notes after discussing the questions with my peers was... Helpful (1) just another thing to do (2) not helpful (0) Third column are Interim scores Fourth column Interim scale Fifth column-- students who asked questions on Interim Sixth column-- students grades on in class assessment Seventh column -- students who asked questions on class assessment
ninibb1Jun 21, 201662KB258
Responses to IV fluid survey2
All raw data, cleaned up, from IV fluids in labor survey
kacarmackNov 8, 201457KB200
US Crime
These data are crime-related and demographic statistics for 47 US states in 1960. The data were collected from the FBI's Uniform Crime Report and other government agencies to determine how the variable crime rate depends on the other variables measured in the study. Number of cases: 47 Reference:Vandaele, W. (1978) Participation in illegitimate activities: Erlich revisited. In Deterrence and incapacitation, Blumstein, A., Cohen, J. and Nagin, D., eds., Washington, D.C.: National Academy of Sciences, 270-335. Methods: A Primer, New York: Chapman & Hall, 11. Also found in: Hand, D.J., et al. (1994) A Handbook of Small Data Sets, London: Chapman & Hall, 101-103. [Collinearity , Correlation , Causation , Lurking variable , Regression]
VariableDescription
R Crime rate # of offenses reported to police per million population
Age The number of males of age 14-24 per 1000 population
S Indicator variable for Southern states (0 = No, 1 = Yes)
Ed Mean # of years of schooling x 10 for persons of age 25 or older
Ex0 1960 per capita expenditure on police by state and local government
Ex1 1959 per capita expenditure on police by state and local government
LF Labor force participation rate per 1000 civilian urban males age 14-24
MThe number of males per 1000 females
NState population size in hundred thousands
NW The number of non-whites per 1000 population
U1Unemployment rate of urban males per 1000 of age 14-24
U2 Unemployment rate of urban males per 1000 of age 35-39
W Median value of transferable goods and assets or family income in tens of $
X The number of families per 1000 earning below 1/2 the median income
ds-231%scAug 11, 20082KB2077
Wages and Hours
The data are from a national sample of 6000 households with a male head earning less than $15,000 annually in 1966. The data were clasified into 39 demographic groups for analysis. The study was undertaken in the context of proposals for a guaranteed annual wage (negative income tax). At issue was the response of labor supply (average hours) to increasing hourly wages. The study was undertaken to estimate this response from available data [ Regression , Outlier , Collinearity , Assumptions, regression]
VariableDescription
HRSAverage hours worked during the year
WAGE Average hourly wage ($)
ERSP Average yearly earnings of spouse ($)
ERNO Average yearly earnings of other family members ($)
NEIN Average yearly non-earned income
ASSET Average family asset holdings (Bank account, etc.) ($)
AGE Average age of respondent
DEP Average number of dependents
RACEPercent of white respondents
SCHOOL Average highest grade of school completed
ds-231%scAug 11, 20082KB1458
Female LFPR by city, 1968 and 1972
Labor force participation rate (LFPR) for U.S. women in 1968 and 1972
benprytherchOct 11, 2014760B1627
Low Birth Weight Study
OURCE: Hosmer and Lemeshow (2000) Applied Logistic Regression: Second Edition Data were collected at Baystate Medical Center, Springfield, Massachusetts during 1986. DESCRIPTIVE ABSTRACT: The goal of this study was to identify risk factors associated with giving birth to a low birth weight baby (weighing less than 2500 grams). Data were collected on 189 women, 59 of which had low birth weight babies and 130 of which had normal birth weight babies. Four variables which were thought to be of importance were age, weight of the subject at her last menstrual period, race, and the number of physician visits during the first trimester of pregnancy. LIST OF VARIABLES: Columns Variable Abbreviation ----------------------------------------------------------------------------- 2-4 Identification Code ID 10 Low Birth Weight (0 = Birth Weight >= 2500g, LOW 1 = Birth Weight < 2500g) 17-18 Age of the Mother in Years AGE 23-25 Weight in Pounds at the Last Menstrual Period LWT 32 Race (1 = White, 2 = Black, 3 = Other) RACE 40 Smoking Status During Pregnancy (1 = Yes, 0 = No) SMOKE 48 History of Premature Labor (0 = None 1 = One, etc.) PTL 55 History of Hypertension (1 = Yes, 0 = No) HT 61 Presence of Uterine Irritability (1 = Yes, 0 = No) UI 67 Number of Physician Visits During the First Trimester FTV (0 = None, 1 = One, 2 = Two, etc.) 73-76 Birth Weight in Grams BWT ----------------------------------------------------------------------------- PEDAGOGICAL NOTES: These data have been used as an example of fitting a multiple logistic regression model. STORY BEHIND THE DATA: Low birth weight is an outcome that has been of concern to physicians for years. This is due to the fact that infant mortality rates and birth defect rates are very high for low birth weight babies. A woman's behavior during pregnancy (including diet, smoking habits, and receiving prenatal care) can greatly alter the chances of carrying the baby to term and, consequently, of delivering a baby of normal birth weight. The variables identified in the code sheet given in the table have been shown to be associated with low birth weight in the obstetrical literature. The goal of the current study was to ascertain if these variables were important in the population being served by the medical center where the data were collected. References: 1. Hosmer and Lemeshow, Applied Logistic Regression, Wiley, (1989).
lauren.bartschMar 24, 20156KB841

1 2 3   >

Always Learning