Proceed
as indicated below to open the dataset you desire.
Ecological
Data Sets
In "Ecological Data
Sets," the unit of analysis is geographical: a societies, states, cities,
colonies, regions, etc.
Archive à Ecological
à Cross-cultural (pre-Industrial) àxcafrica
(Pre-Industrial Societies of Africa, includes 111 Sub-Saharan societies),
xcasia (Pre-Industrial Societies of Asia, includes 81 East Asian societies),
xccirmed (Pre-Industrial Societies of Circum-Mediterranean Region includes
65 Mediterranean societies),
xcnoamer (Pre-Industrial Societies of
North America, includes 124 North American societies),
xcsoamer (Pre-Industrial
Societies of South America, includes 81 South American societies),
xcsopac
(Pre-Industrial Societies of South Pacific, includes 101 South Pacific societies)
The
datasets listed above each contain 99 variables. Within these datasets each set
contains an enormous amount of information surrounding these societies. Some of
the most common topics in these datasets include agriculture, jobs, family, religion,
and judicial systems.
Variables pertaining to agriculture include; the level
of agricultural development in these societies (i.e., gardening, slash/burn, developed
or none), the principle crop grown, the possibility of growing cereal crops, the
type and intensity of agriculture and whether their agriculture is developed or
non-developed. Other variables regarding agriculture or farming involve the question
of whether these societies own domesticated animals, and if so, whether those
animals are larger that a dog, cat, pig or fowl. Another variable pertain to whether
these individuals own herd, milk these animals or produce dairy products.
Job
or employment variables take up a big part of these datasets, as well. The main
jobs in question consist of gathering, hunting, fishing, herding, farming, metal
working, weaving and pottery. Variables question the amount and percentage of
dependence that may be placed on these jobs for subsistence. These datasets also
touch on who performs these jobs, if they are present in the society.
Variables
dealing with the family pertain to the fixity of the residence and marriage rules.
Some of these rules include where these couples begin residence, what type of
marriage it become (i.e. monogamy, polygyny, exogamy, endogamy or neither), the
type of exchanges made through marital bonds (i.e. bride price, dowry, etc.) and
the family size and structure are classified.
Religion is a small section
in these datasets. The three variables touch on the presence and activity of high
Gods, the clarification of an actual active God and whether the high God is treated
as present or absent in these societies.
The judicial section consists of
a variety of different variables. Levels of the development of the state and the
degree of social stratification are questioned. Other variables question the succession
of the office being hereditary, the number of local levels of jurisdictional hierarchy
above and beyond the local level, the number of sovereign groups or extra-local
jurisdictional levels and the amount and importance of slavery in their culture.
Finally, the question of whether the state has emerged can be answered.
Lastly,
the datasets contain supplementary codes to some of the previous variables. Including
family organization, marriage, rules of succession, slavery, etc.
Archive
à Ecologicalà Cross-cultural
(pre-Industrial) à xcstndrd (Standard Cross-cultural
sample - 186 Pre-Industrial societies)
This particular dataset contains
203 variables. It is similar in comparison to previous Preindustrial society's
database, in that it contains much of the same variables pertaining to agriculture,
employment, judicial systems, religion, and families. However, this dataset analyzes
family roles with more emphasis. The variables pertain to whether arranged marriages
still exist in these societies, is consent by bride, groom and parent needed for
these arranged marriages, and do couples need to marry within kinship ties, etc.
Other variables consist of the possibility of wedding night customs being followed
and the availability of divorce or remarriage among these societies. The dataset
also focuses on the roles of parent and child. Emphasis is placed whether males
and females receive different types of treatment at certain ages. Are these children
encouraged or discouraged to express their sexuality and engage in sexual behavior.
Is competitiveness, aggression, self-reliance, and achievement preferred in these
societies. Additionally, variables regarding the differences between men and women
are analyzed. The main focus falling on whether a high value is placed on males
to be aggressive, strong, and sexually potent. Do women feel inferior to men,
which individual participates in community activities, who controls the family
property and money, what type of value is placed on the lives of women, the degree
of segregation between men and women, etc. are among some of the variables in
this dataset. Finally, some additional variables include the population size,
degree of written language, the exchange rate for food and valuables, quality
of travel by land and sea, and whether homosexuality, wife-beating and rape occur
in these societies.
Archive à Ecological à
Cross-cultural (pre-Industrial) à xcworld (
Atlas of World Cultures - 563 Pre-Industrial societies)
This dataset contains
100 variables. It accommodates the exact same variables as the Pre-Industrial
societies of Africa, Asia, Circum-Mediterranean region, North America, South America
and South Pacific with the exception of a variable pertaining to the major regional
subgroups (i.e. Sub-Sahara, Circum-Mediterranean, East Asia, Pacific, North or
South America)
Archive à Ecological à
Historical à Cities.mc4 (American Cities
1900-1906)
The following dataset contains 112 variables.
This dataset is a typical dataset for analyzing a city. It contains variables
pertaining to the population, crimes, expenditures, employment, religion, and
schooling. Population variables pertain to the amount of individuals living in
l890, l900, l902, l903, and l906. Another variable focuses on the population growth
during l890-l906 and the number of males vs. females during each period in time.
Secondly, crime variables question the rate of suicides, homicides, assaults,
larceny, burglary, drinking, disturbing the peace, vagrancy, and miscellaneous
crimes among these individuals. Expenditure variables pertain to the amount of
money spent on new building, remolded buildings, police officers, courts, jails,
fire department, streets, public health, sanitation, public education and teachers
salaries. Additionally, employment variables contain information about the percentage
of women (age l0 and over) obtaining jobs and the various types of employment
(i.e. professional services, domestic personal services, trade, transportation
and manufacturing mechanical jobs). Religion variables focuses on the percentage
of population that belongs to a variety of different congregations (i.e. Roman
Catholic, Baptist, Methodist, Presbyterian, Lutheran, Episcopalian and other denominations).
Finally, the number of Sunday schools, teachers and students were accounted for.
Lastly, schooling variables pertained to the number of students enrolled in public/high
school, the percentage of whites vs. blacks attending school, literacy over the
age of nine and the amount of public library books used and bought in past years.
Archive
à Ecological à Historical
à Colonial.mc4 ( 15 Original Colonies of
America)
The dataset contains 53 variables. The variables pertain to the
environment and the society surrounding it. Variables included the percentage
of blacks, whites, and slaves. The dataset also focuses on religion and the percentage
of the population that attended congregations ranging from Roman Catholic to Quakers.
Additionally, variables contained information about the area of coastal shorelines
and the amount of land miles in the surrounding area.
Archive à
Ecological à Historical à
England.mc4 (England and Wales 1840s through 1860s)
This dataset
contains 60 variable, most of which pertain to the people of these societies and
crime rates. Variables pertaining to people, involve the population and population
growth in l84l-l861. The variables also specify the average number of people per
household and the number of people attending Roman Catholic, Protestant, Mormon,
or Unitarian churches on March 30, l851. Additionally, measurements of the amount
of deposits in a person's savings account, the annual number of marriages, and
the percentage of population enrolled in public weekday school are accounted for.
The majority of variables in this dataset, however, pertain to crime and crime
rates. The dataset looks at the annual percentage of people arrested and the number
of conviction rates by assaults. Other crime variable focus on the rate of offenses
against a person as well as the number of convictions for larceny, property crimes,
malicious offenses, forgery, rape, prostitution, etc. Similarly, the annual percentages
of female and male criminals are measured. Lastly, the dataset looks at the average
percentage of people bought to trial and form those how many proceeded in court
before justices.
Archive à Ecological à
Historical à USA 20-80 (USA from the 1920s
to the 1980s)
This dataset contains 565 variable and an enormous amount
of information. The dataset includes different variable pertaining to different
years, but overall it covers a vast amount of information. The main topics in
this dataset are the land, people/families, employment, crime rates, social issues,
sports, education, judicial/political issues, and expenditures for these societies.
Land
variables pertain to the percentage of population during different time periods
and the percentage of blacks, Hispanics, Asian and people of other ethnic backgrounds.
Other variables contain the average temperature, elevation, area, miles of coastal
shoreline, and the year these societies were admitted to the union.
People
and family variables contain information about the amount of females to males,
the amount of single men and women, and the percentage of households containing
married couples. The question of employment of women with children is measured
as well as the amount of divorces that occur during the different genres. Family
variables focus on the family's income, the amount of aid these families receive
and the percentage of families below the official poverty line. Finally, the variables
look at the amount of infant rates and deaths for black verse whites.
Employment
variables consist of variables about travel time and the type of positions these
individuals held. Variables question the percentage of employees that work in
agriculture, prosecution/ legal services, correctional facilities, law firms,
forestry, transportation, wholesale trade, retail, finance, service occupation,
or as scientists, engineers, computer operators, and police officers. Other variables
focus on means of transportation (i.e.: walk, carpool, or use public transportation),
and also the time it takes these individuals to arrive at work.
Crime variables
involve the number or percent of different crimes people engage in (i.e.: robbery,
homicide, assault, rape, burglary, larceny, auto-theft, etc.). Variables also
include the number and ratio of arrests for black and white individuals. Lastly,
the ratio of inmates to staff is measured.
Social issue variables revolve
around suicide rates, consumption of alcohol, abortion rates, and religion. The
number of active psychologists and the number of members the American Psychological
Association is considered. The percentage of alcoholic beverages consumed (i.e.:
spirits, wine, or beer) was measured in association with deaths from cirrhosis
of the liver. The numbers of bars in these areas were taken into account. Finally,
the types of churches and their members were also determined.
Sport variables
included the percentage of the population buying hunting or fishing licenses and
the number of registered boats. The amount of golf courses, the number of bowlers
in the American Bowling Congress league, and the sales of sporting goods were
taken into account. Lastly, the circulation of the vast amount of magazines varying
from sports to beauty consisted of a considerable section of this dataset.
Educational
variables pertained to the percentage of individuals with college education and
master's degrees. Educational spending and the average salary of public school
teachers were measured, taking into account the ratio of students to teachers.
Other variables focused on the life of college students attending college out-of-state
and their living choice of dormitories.
Voting variables involved the percentage
of state legislators who are black or female. The percentage of voting preference
for different presidential candidates was also determined.
Finally, expenditure
variables were focused upon the money spent for count systems, and the money spent
by individuals for home appliances as well as other expenses (i.e. washers, dryers,
range, refrigerators, furniture, grocery stores, restaurants, newspapers, records,
florists, jewelry, interior decorators, etc.)
Archive à
Ecological à International à
Africa.mc4 (Nations of Africa)
Asia.mc4 (Nations of Asia)
Europe.mc4 (Nations of Europe)
Global.mc4 (174 Nations of World
with Population of 200,000 or more)
Latin.mc4 (Nations of Latin America)
Each
of these datasets contains 238 variables. The dataset focuses upon issues that
form a nation. The topics range from land size, to everyday home life. These datasets
give background information about the land and its population. It contains variable
about the number of children in these areas, the annual number of births, as well
as deaths and the question of abortion (i.e. legalization and favoritism for abortion).
Other variables included the number of doctors in these areas, the amount of money
spent on health care and the average life expectancy for women and men. Additional
variables focused on the consumption of drugs, alcohol, meat, cigarettes, etc.
The number of assaults, murders, rape, burglary, etc. were measured. Economic
variables consisted of industrial production growth rates, annual inflation rates,
and unemployment rates. Percentage of GDP (Gross Domestic Product) that are accounted
for by agriculture, industry, etc. were measured. Variables accounted for the
number of radios, televisions, newspapers, cell phones and movie tickets being
purchased. Additionally, variables question the amount of money spent for national
defense and education. Travel, school enrollment, and a women's professional occupation,
as well as government positions, were among the variables in this dataset. Finally,
variables pertaining to the importance of family live; friendships, leisure time,
and a satisfying sex life were questioned. Trust and pride in one's work was also
determined. Additionally, peoples ideals about specific social issues are include
in these datasets.
Archive--> Ecological--> International--> China
(Provinces of China)
This dataset consists of 146 variables. Most variables
pertain to the population as a whole as well as their agriculture. Population
variables involve the total number of households, average number of people per
household, and the percentage of population living in cities/towns and urban/rural
areas. Additionally, variables question birth rates, fertility rates, death rates,
levels of schooling (i.e. college graduates, some college, high school, junior
high, elementary, etc.), illiteracy rates, and life expectancy for men and women.
Other variables list the amount of hospital beds, doctors of western medicine,
assistant doctors, and traditional medicine health career personnel that are available
in these areas. Variables pertaining to the household are also looked upon. For
example, the amount of rural and urban households in poverty status, the number
of couple households composed of two or more generations compared to the amount
of one person households with two or more generations. Agricultural variables
consist of the total crop land, total area of grain crops, area of cash crops,
total yield, etc. Others include the expenditure on food, average temperature,
amount of rainfall, humidity rates, and high/low temperatures. Finally, variables
pertain to the type of transportation (i.e. bikes, buses, etc.), and the percentage
of increase in the amount of television sets, tape recorders, bikes, and electrical
use in rural areas.
Archive--> Ecological--> International--> Canada
(Canadian Provinces & Territories)
This data set contains 123 variables.
Its variables concentrate on the people and issues surrounding this area. Some
variables pertain to the total population as well as the population on farms,
urban residence, the percentage of people of different ages, and the population
growth during 1951-1961 and 1971-1981. Others involve variables about social rank.
For example, the average family per capita income, unemployment rates, annual
teachers' salaries and the average percentage of college graduates, percentage
enrolled in school and those with less than nine years of schooling. Additionally,
variables include information about individuals and their social status. The amount
of marriage rates and divorce rates are measured. Child births, percentage of
birth to unwed mothers and abortion rates are variables in this dataset. The percentage
and ratios of males and females in the work force as well as maintaining a managerial
position are viewed. Other variables pertain to different types of violent and
non-violent crimes, percentage of people claiming a specific religious group or
affiliation and the amount of money spent on a variety of different items (i.e.
freezers, television sets, restaurants, books, dishwashers, etc.)
Archive
--> Ecological --> International --> Cancity (Largest Canadian
Cities)
This particular dataset contains 119 variables. Most of the variables
pertain to certain percentages of different issues surrounding the population.
For example, whether English, French, or Spanish is spoken in the home, type of
ancestry, and the amount of males to females. Like most of the other datasets
variables question the amount of married/divorced couples, the number of children
born to wed or unwed mothers, type of religious preference, type or amount of
men and women working, amount of education within different age groups, etc. Specifically,
variable pertain to the type of occupation of these individuals. For example,
the amount of men and women employed in national sciences, medicine and health,
artistic, engineering and math, religion, etc. Additionally, unemployment rates
are calculated. Along with the question of occupation involves the amount of schooling
and household income of certain individuals. Finally, variables pertaining to
the amount of occupants in each household, type of dwelling, crime rates, and
amount of money spent on retail sales are measured in this dataset.
Archive
--> Ecological--> International-->India (22 States & 9 Union
Territories of India)
IndiaR (22 States & 9 Union Territories
of India: Raw Data)
Although these datasets contain different amounts of
variables their general focus is the same. The India dataset contains 194 variables
while, the IndiaR data contains 291 variables. These datasets pertain to the different
factors that effect people. For example, the total number of suicides, the percentage
of contraception used (i.e. sterilization, IUD, conventional contraception, etc.),
injury rates, the number of mental patients, and the percentage of crimes, etc.
are considered. Other variables pertain to the population as a whole (i.e. the
number of males per females, state rank by population, urban and rural population,
percentage of workers, literacy rate, religious preferences, percentage of those
in scheduled tribes or caste, etc.). Additionally, variables also pertain to the
schooling of these individuals. For example, the total number of recognized teachers,
amount of money spent on college/ high-school professors, the number of women
educators teaching all levels, and the number of male and female pupils are measured.
Lastly, other variables involve a variety of different topics, some pertaining
to the number of dwellings, registered factories, and others pertaining to the
number of valid voters and the surplus or deficit in the budget.
Archive-->
Ecological--> International-->
Mexico (States of Mexico)
MexicoR (States of Mexico: Raw Data)
Again, these two datasets contain
different amounts of variables, however, their general focus is the same. The
Mexico data contains 112 variables, and the MexicoR dataset contains 276 variables.
The majority of this dataset pertains to the population as well as their surrounding
environment. Variables consist of general information about the people of these
communities. For example, the number of privately owned houses, religious preferences,
literacy rates, amounts of school education, birth/death/infant death rates of
men and women, marriage/divorce rates, etc. Other variables pertain specifically
to the schools (i.e. number of students in preschool, primary school, private
school, science based schools, universities, prep schools, etc.) Employment status
are also among the variables in this dataset. It questions the total number of
people employed, the number of professional/technical/business/social workers,
and the minimum salary earned. Additionally, other variables include the total
amount of corn, bean, egg, sugar, milk, etc. produced. Finally, variables involve
the number of books in their library, the number of arrests, community offenses,
etc. are taken into account.
Archiveà Ecologicalà
States, Cities & Countiesà Citiesà
Chicago (Chicago Neighborhoods)
Losangel (Cities of Los Angeles)
Msa90 (U.S. Metropolitan Statistical areas)
Stlouis (Census Tracts
of Saint Louis)
Stloarea (Counties of Greater St. Louis area)
Yorkadel (Counties of New York City & Philadelphia)
Seattle (Census
Tracts of Seattle)
These datasets contain much of the same information but
differ in variable amounts. Below is simply an overview of all the datasets and
is then followed by specifics pertinent to the different datasets.
These
datasets revolve around the contents of the city and the individuals who reside
within them. A majority of each dataset is focused on the year 1990 and 1980.
It contains variables about population, schooling, employment, and housing.
Population
variables consist of the percentage of males to females and the percentage of
people that are of different age groups. Other variables question the nationality
(i.e. American Indian, Asian, Thai, Korean, etc.) as well as the ancestry (Austrian,
Belgian, Greek, Irish, Scottish, etc.). The state of residency and the percentage
of individuals foreign born is also questioned. Lastly, the percentage of the
population in correctional institutions, nursing homes, mental hospitals, juvenile
institutions, military quarters, etc. are measured.
Schooling variables
focus mainly on the percentage of the population that is currently enrolled in
school and in some cases the amount of people enrolled in private institutions
(i.e. nursery school, elementary, high school, college). Additional variables
measure the amount of people 25 and over who have completed less than ninth grade,
high school graduates, some college, associates degree, bachelor's degree, etc.
Employment
variables pertain to the ages of workers, type of occupation, and income rates.
Some variables discuss the age of workers, male and female. Others question their
type of occupation (i.e. manufacturing non-durable goods, durable goods, wholesale
trade, retail, etc.), the per capital income for whites, blacks, american indians,
asians and hispanics. Finally, the percentage of children and adults below poverty
level is measured. Additional variables measure the type of transportation and
time traveled by employees to their designated working place (i.e. drive alone,
carpool, bus, subway, walk, work at home, etc.).
Lastly, information pertaining
to the household in general is looked upon. Variables consist of the amount of
individuals per household (i.e. only 1 person, 7 or more, married couples, male-headed
households, women-headed households, households involving children, etc.), percent
of occupied housing during different time frames, average number of rooms in housing
units, price of rent, average social security per household for retirement, welfare,
etc. and the housing income.
Chicago: (Chicago Neighborhoods)
The
dataset contains 344 variables. In addition to the above information this dataset
gives a more focused look on age groups, schooling, occupation, hospitalization,
and housing units. Some of the variables measure the amounts of the population
under different age groups (i.e. percentage of population 25-34, 44-80, 6-13,
etc.). Other variables focus on the amount of mental hospital admissions pertaining
to a variety of different causes or diseases. For example, syphilis, alcoholism,
etc. Additionally, variables involving occupation simply provides more choices
of employment (i.e. government, technicians, etc.) in addition the dataset measures
the amount of individuals unemployed, disabled, working within the city or the
outskirts of the city, etc. Housing variables simply focus on the amount of bedrooms,
kitchens, floors, etc. in each unit and whether the unit is heated by gas, electricity,
oil or coal. Other variables question the percentage of radios as well as the
amount of juveniles referred to court.
Losangel: (Cities of Los
Angeles)
This dataset contains 150 variables. The only difference or additional
variables to speak of in this dataset revolve around crime rates. The amount of
murders, homicides, rapes, assaults, burglaries, car thefts, arson, etc. are measured.
Other variables involve the amount of police officers and employees within the
city.
Stlouis (Census Tracts of Saint Louis)
This particular
dataset contains 339 variables. Additional variables in this dataset pertain to
the population, expenditures, and housing. Population variables consist of the
percentage of single males and females, the percentage of veterans, and the percentage
of individuals employed. Other pertain to the amount of abortions, psychologists,
reported cases of sexually transmitted diseases, etc. Expenditure variables involve
the amount of cars (i.e. Audis, Jeeps, etc.) and restaurants or bars (i.e. taverns,
liquor stores, McDonalds, pizza parlors, sporting good store, etc.) in this area.
Lastly, housing variables include the type of family in the home (i.e. family
members, non-family members, traditional, non-traditional, men with children,
etc.), the amount of new housing with and without mortgages, percentage of houses
for sale, and the type of entities in each home (i.e. no bathtubs, air conditioning,
kitchen, etc.).
Msa90 (U.S. Metropolitan Statistical areas)
This
dataset contains 291 variables. Within the dataset it contains more specific variables
about the population, deaths, crime, income, voting preferences (i.e. democratic,
republican, etc.), expenditures, and the land area. Population variables pertain
to the percentage of males and females over the age of fifteen who are single,
married, separated, widowed, or divorced. Others measure the amount of people
below the poverty level by age as well as race (i.e. whites, blacks, american
indians, asians, and hispanics). Additionally, the percentage of the population
who are veterans male and female are measured. Causes of deaths and birth rates
are also viewed. Types of crimes (i.e. robberies, larceny, car theft, etc.) are
variables within this dataset. Income variables involve the average pay in private
nonfarm employment, construction, manufacturing, etc. and the percentage of earnings
from agriculture services, forestry, mining, etc. Lastly, the percentage of local
government expenditures for health and hospitals, welfare, highway, fire, police,
etc. can be viewed.
Yorkadel (Counties of NYC and Philadelphia)
Stloarea (Counties of Greater St. Louis area)
These datasets contain
458 variables. They are very similar to the US Metropolitan Statistical areas
(Msa 90), in that they include variables pertaining to voting preferences, crime
rates, percentages of earnings from retail stores, average pay for different occupations,
government expenditures, and the percentage of veterans of this areas. Additionally,
variables pertaining to poverty levels, infant death rates, causes of deaths (i.e.
cardiovascular disease, motor vehicles, etc.) and birth rates are measured. Lastly,
other variables include the percentage of votes cast for leading party, local
government finances, property taxes, the amount of hospital beds available, etc.
are all part of this dataset.
Seattle (Census Tracts of Seattle)
This
dataset contains 213 variables. Additional variables consist of school, population,
and household data. Like some of the other datasets the percentage of kids attending
private schools is measured. Population variables include crime rates, the median
age of males and females, and the marital status of males and females. Household
data includes the percentages of households with kitchens, baths, etc., the cost
or rent of housing and the number of families per household.
Archiveà
Ecologicalà States, Cities & Countiesà
Citiesà
Chicagor (Chicago Neighborhoods:
Raw Data)
Losangelr (Cities of Los Angeles: Raw Data)
Stlouisr
(Census Tracts of Saint Louis: Raw Data)
Seattler (Census Tracts
of Seattle: Raw Data)
The above datasets contain 3348 variables; however,
the variable data are not recoded and are raw data. For most purposes, the
previous group of datasets will be more useful.
Archive à
Ecological à States, Cities, & Counties à
Individual States à
(All 50 States listed)
These
datasets contain 458 variables. Like most other datasets, the variables revolve
around population, housing, farming, employment, and income. Population variables
measure different age groups, different ethnicity and different ancestry. Other
population variables look at the percentage of urban and rural populations, as
well as the amount of males and females or sex ratio of the population. Additionally,
they view the status of these males and females (i.e. married, single, divorced,
widower, etc.). Moreover, they measure the percentage of births to women under
15 and 20 years of age, and the number deaths that occur due to certain misfortunes
(i.e. heart disease, motor vehicle, infant, etc.).
Housing variables again,
are similar to past datasets. Variables pertain to who heads these households,
amount of children, number of different housing units, value or rent of each unit,
and the percentage of units built during a variety of years. In addition, the
percentage of telephones, cars, and type of heat used (i.e. gas, electric, oil,
coal, wood, none) is measured. Additionally, variables pertaining to the longevity
and area of people living in these houses are viewed.
Farming variables
consist of the ownership of the land, percent irrigated, average age of farm operators,
and the sizing of the land. Also, variables question the amount of stores per
population (i.e. garden suppliers, department stores, automotive dealers, gas
stations, eateries, etc.) as well as the percentage of earnings come from agriculture,
retail, federal military, etc.
Employment variables contain the amount of
males and females over age 16 working within the country or out of the country
and the percentage of them employed in agriculture, mining, construction, etc.
Other variables look at the unemployment rate, average amount of pay, and the
time and way of transportation to and from work.
Finally, income variables
include the median family income and the per capita income of those with different
ethnic backgrounds. Additionally, the average monthly payment of supplemental
security income for a widower, disabled, etc. is measured.
Other variables
range from the percentage of local government or federal expenditures to the percentage
of people voting, amount of physicians and hospital bed available, amount of education,
and the percentage of the population born in state or foreign born.
Archive
à Ecological à States,
Cities, & Counties à à
USCounty (Counties of the United States)
This dataset contains 470
variables. It is identical to the datasets above (the 50 states), with the addition
of a few variables pertaining to census regions and different coding system for
each state.
Archive à Ecological à
States, Cities, & Counties à States 99 (The
50 States of the United States)
This dataset consists of 791 variables.
Within this dataset contains variables pertaining to the population, land area,
households, communities and expenditures. Population variables consist of the
percentage of the population of different ages and the population per square mile.
Other variables question the percentage of males versus females, percentage of
the population with different ethnic backgrounds, and ancestry. Additional variables
include the number of marriages and divorces as well as the percentage of individuals
over age 15 who are single, divorced, married, etc. The number of expected children
to be born is also measured. Variables that are more general look at the percentage
of individuals born within the state verses foreign-born and the percentage of
urban and rural populations.
Land area variables include information about
the are in general. Variables measure the mean elevation, average amount of tornadoes,
and the average temperature in January. Other variables look at the amount of
state parks, amount of visitors to these parks, and the amount used or needed
to maintain the parks.
Household variables are very similar to other datasets.
Variables measure the number of housing units, number of rooms, the value or rent
for the units and construction contracts, etc. Other variables pertain to when
the unit was built and the amenities of the home (i.e. type of heat, number of
baths, telephones, etc.). Additional variables consist of the percentage of households
with more than 1.01 persons per room, and the percentage of people living in group
quarters (i.e. prison, college dorms, streets, etc.).
Community variables
cover a wide range of this dataset. Variables pertaining to employment, schooling,
transportation, income, crime, religion, etc. are measured. Other variables include
the amount of new age religious groups, amount of newspaper articles about UFO's,
amount of astrological studios, number of Heaven's gate recruitment meetings per
state and the number of scientology offices. Additional variables look at the
amount of deaths (suicide, infant, AIDs, heart disease, etc.), percent of Ritalin
use, cocaine addicts, amount of liquor consumed and abortions. Moreover, the number
of different occupations for males and females is measured. Data pertaining to
farms, transportation, and income (i.e. median, per capita, and individuals below
poverty line) is looked at. Finally, variables consist of the amount of circulation
for a variety of magazines, number of satellite dishes, percentage of children
watching six or more hours of television, voting preferences, amount of veterans,
and the average cost of cigarettes is measured.
Expenditure variables contain
variables about how much money is spent for schooling (i.e. elementary, secondary,
drug education, computers, lunches, etc.) per pupil.
Archive à
Ecological à States, Cities, & Counties à
STF1-90 (STF1 File from 1990 Census)
This dataset contains 686 variables.
Similarly, the dataset has variables geared towards population, housing, and family.
However, this dataset is more of a comparison of individuals of different gender
and ethnic backgrounds (i.e. black, white, American Indian, Asian, Hispanic or
other, and males or females).
The dataset begins with variables pertaining
to the population of different ethnic groups and genders for a number of different
ages. Variables following consist of information pertaining to children. They
measure the number of children of different ages, living with their own family,
living with other relatives, non-relatives, other group quarters or if these children
are institutionalized. Other variables consist of the status of males and females
over age 15 and the number of these individuals living in correctional institutions,
nursing homes, hospitals, military quarters, etc. Lastly, variables pertaining
to the number of families and households are measured. These variables measure
the amount of households with persons who are homeowners, spouses, grandchildren,
non-relative, etc. living in a family household. Others look at the number of
persons living alone, with children, no related children, etc. Additionally, the
amount of male headed versus female headed households with different ethnic backgrounds,
are measured. Moreover, the total number of housing units' occupied, vacant, owner
occupied, etc. is looked at. Finally, variables containing information to the
median value or rent of these units and the number of vacant housing for sale,
rent, etc. is measured.
Archive à Ecological
à States, Cities, & Counties à
SFT3-90 (STF3 File from 1990 Census)
This dataset contains 1607 variables.
This dataset is similar to the SFT1-90 dataset with the exception of more data
(i.e. more age variables). Like the SFT1-90 dataset variables pertain to the population,
children, family, and housing. The only additional variables consist of education
and employment variables. These variables measure the level of education for individuals
of different age groups, gender and ethnic backgrounds. Similarly, employment
variables measure the amount of males and females holding a variety of occupations
as well as the amount of disabled workers in this census.
Other
Data Sets
Archive à Other à
Congress à House 103.mc4 (Representatives
in the 103rd Congress)
This dataset contains 53 variables of a more general
nature. The variables give information about the representatives in the 103 Congress.
Some of the more basic variables include the race, religion, party membership,
age, amount of education, marital status, veteran, lawyer, and religion lived
by the representative. Other variables pertain to the percentage of votes the
representative received, number of terms served in the House, whether the member
holds a leadership position and the percentage of Hispanic and African American
population that voted in their favor. The remaining variables pertain to how the
member voted on certain bills, whether those particular bills were passed and
finally the percentage of funds raised or contributed for the member. The last
variable in this dataset asks whether the representative was re-elected to serve
in the 104th congress.
Survey
Data Sets
Archive à Survey à
International à Canadian Political Studies à1983psc
(Canadian Election Study)
8384psc (Political Support in Canada)
Cnecp88 (1988 Canadian National Election Study - Campaign Period Survey)
Cnepe88 (1988 Canadian National Election Study - Post Election Survey)
Cnes84 (1984 Canadian National Election Study)
Cnesq88 (1988
Canadian National Election Study - Self Administered Questionnaire)
Cnewt88
(1988 Canadian National Election Study - Weights)
Pre88psc (1988
Canadian Pre-Election Study)
Pst88psc (1988 Canadian Post-Election
Study)
No description available
Archive à
Survey à International à
Issp à
Issp 1992 (1992 Issp Social
Inequity)
Issp 1993 (1993 Issp Environment)
Issp 1994
(1994 Family and Changing Gender Roles)
Issp 1995 (1995 Issp national
Identity)
Each dataset contains a different number of variables. The survey
questions range over a variety of topics. Some are concerned with families, sexual
orientation, religion, race, etc. Others are concerned with education, employment,
politics and the environment.
Archive à
Survey à US à GSS
These
datasets, based on the almost-annual General Social Survey, are divided into two
types. The ones with the suffix "r" are the original research
version and contain raw data. Most students will want to use the "enhanced
instructional versions," which are the ones without "r" as a suffix.
The enhanced instructional version includes fewer variables, but these have been
recoded into fewer response categories and are more easily used in analysis.
The datasets date back to 1972. Some questions are used every year; others
vary, with some years emphasizing one topic or another.
Trend
Data Sets
Archive à Trend à
International à CNHSTGRP (Cross-National Historical
Trends, 1815-2010, Representative Group Subset)
This dataset contains 144
variables. The variables are a mix of demographic, economic and political factors.
The years for which data are available vary considerably.
Archive
à Trend à International
à Remainder of datasets in this category (i.e.
Cross National Historical Trends 1815-2010 Afghanistan/ Bosnia/ Liberia, etc.
Subsets)
These datasets all differ in the amount of variables. This summary
provides variables that may appear in each datasets. Variables pertain to the
population per square mile and the percentage of the population in cities with
one hundred thousand, fifty thousand, ten thousand, etc. people. Others include
the national government revenue and per capita in US dollar equivalents, percentage
of total expenditure for defense, and the percentage of gross domestic product
originating in industrial activity. The proportion of world trade as well as the
amount of imports and exports is measured. Employment data pertains to the amount
and percent of individuals working in agriculture, industry and military. Additionally,
the amount of vehicles, telephones, radios, television sets, books, etc. are looked
at. Education and voting data are also among the variables in this dataset. Finally,
variables consist of the exchange rates and the number of assassination strikes,
major government crises, etc. that has occurred.
Archive à
Trend à US à USTrend
(Trends in the United States from 1789 to 2010)
This dataset contains 236
variables. The variables revolve around topics of population, voting preferences,
community, and employment. Population variables measure the population of different
age groups, median age of the population, and percentage of baby boomers. Other
variables look at the marriage/ divorce rate, expected birth rate, and the number
individuals with different ethic and gender backgrounds. Additional variables
pertain to the total number of households (farming or non-farming), the percentage
of rural and urban populations, and the percentage of individuals who are foreign
born. Voting data involves information on how many eligible people voted for the
president, cost of an election, and the number of Republicans/Democrats/Senate
members, etc. Electoral college votes and presidential vetoes were also measured.
Community variables question the amount of televisions, radios, etc. that are
used within the home as well as how many hours are used for each. Other variables
ask what percentage of the population would vote for a black or female president,
put a great deal of confidence in the press, Congress, military, etc., or allow
a racist or gay individual to speak or teach. Additional variables pertain to
crime and education data. Finally, employment data measures the type of profession
for different genders, average earnings per hour, and the unemployment rates during
this period.
