One of the most remarkable traits that August Comte mandated for
Sociology was a core of scientific rigor. He proposed the concept
of Positivism is the scientifically-based
sociological research that uses scientific tools such as survey,
sampling, objective measurement, and cultural and historical
analysis to study and understand society. Although the
current definition of positivism expands far beyond Comte's
original vision, Sociological scientific methodology is used
through government and industry researchers and across higher
education and the private sector. Comte was originally interested
in why societies remain the same (social statics) and why societies
change (social dynamics). Most sociological research today falls
within these broad categories. Sociologists strive for
Objectivity is the ability to study and
observe without distortion or bias, especially personal
bias. Bias-free research is an ideal that, if not present,
will open the door to extreme misinterpretation of research
findings.
Sociological science is both different and similar to other
scientific principles. It differs from Chemistry, Biology, and
Physics in that sociology does not manipulate the physical
environment using established natural science theories and
principles. It's similar to Chemistry, Biology, and Physics in that
statistical principles guide the discovery and confirmation of data
findings. Yet, Sociology has no universally social laws that
resemble: gravity (E=MC2) or the speed of light. This is
because Chemistry, Biology, and Physics have the luxury of studying
phenomenon which are acted upon by laws of nature. Sociologist
study people, groups, communities, and societies which are
comprised of Agents are people who use
their agency to make choices based on their varied
motivations (Google Anthony Giddens-human agency, January
18, 1938 British Sociologist).
Sociologists study people who chose, decide, succeed, fail, harm
others, harm themselves, and behave in rational and irrational
ways. I've often explained to my students that if I took an ounce
of gasoline and placed a burning match upon it, the gas would have
to burn. The gas has no choice just as the flame has no choice.
But, if someone placed a burning match on your arm, or the arm of
your classmate, you or they might respond in any number of ways.
Most would find the experience to be painful. Some might enjoy it,
others might retaliate with violence, and yet others might feel an
emotional bond to the one who burned them. Sociologist must focus
on the subjective definitions and perceptions that people place in
their choices and motivations. In fact, sociologists account for
human subjectivity very well in their research studies. The most
common form of Sociological research is survey research.
Surveys are research instruments designed
to obtain information from individuals who belong to a larger
group, organization, or society. The information gathered
is used to describe, explain, and at times predict attitudes,
behaviors, aspirations, and intended behaviors. Types of surveys
include: political polls, opinion surveys, national Censuses, paper
surveys, verbal interviews, online surveys, and audience voting-
call in (American Idol votes), and polls. Polls are
typically surveys which collect opinions (such as who one
might vote for in an election, how one feels about the outcome of a
controversial issue, or how one evaluates a public official or
organization. The Census Bureau (http://www.census.gov/) by the
Constitutional mandate must count its entire population every 10
years. A Population is the entire
membership of a country, organization, group, or category of people
to be surveyed (IE: US population=305,000,000). A
Sample is some portion of the population
but not all of it (IE: a US Census Bureau's American
Community Survey of 35,000 US Citizens. See http://www.census.gov/acs/www/).
Surveys can ask a certain category of people on a one-time basis; a
Cross-Sectional Survey is a survey given once to a group of
people. Surveys can also ask the same people to fill out a
survey over an extended number of years. A Longitudinal
Survey is a survey given to the same people more
than once and typically over a set of years or
decades.
Table 1. Hypothetical University Student Body Population ABC
University with 10,000 students
Females= 5,000/50% |
Males=5,000/50% |
African American=1,000/10% |
African American=1,000/10% |
Hispanic=1,000/10% |
Hispanic=1,000/10% |
Asian=1,000/10% |
Asian=1,000/10% |
Caucasian=1,000/10% |
Caucasian=1,000/10% |
Other Races=1,000/10% |
Other Races=1,000/10 |
Look above at the box and we'll use this hypothetical ABC
university student body population to better understand sampling.
One of the most important issues when doing survey research is to
ensure a good scientific sample. A Random Sample
is a portion of the population that is drawn in such a way that
every member of the population has an equal chance of being
selected for the survey. (IE: ABC University Registrar's office
uses their computer software to randomly select 1 out of every 10
students for a survey about student opinions in favor of or against
getting a football team). A Representative Sample
is a sample drawn from the population, the composition of which
very much resembles that of the population. Typically this is
obtained via a stratified random sample. A Stratified
Random Sample is a portion of the population is drawn in
such a way that every member of the population and important
sub-categories of the population have an equal chance of being
selected for the survey, yielding a sample that is demographically
similar to population (IE: using the demographic table above, ABC
U. would sample 1 out of 10 students or 1,000. They would also want
half of those students to be female and half male. They would also
want to select for the racial groups. The easiest strategy to do
this would be for the Registrar to program the computer to select
only the female student's files. Then they would have the computer
select only the African American files and select 1 out of 10
students until they have 100 selected. They would repeat this for
all other racial groups and then do the same for the males.
Ideally, every student would respond to the request to take the
survey and they would have a 1,000 student sample that was ½ female
and ½ male; with all 5 racial groups represented equally (see box
below for example). This is both ideal and hypothetical, but it's
typical of the goal sample takers have of a stratified random and
representative sample and the closer they get to this ideal the
better the sample)
Table 2. The Hypothetical ABC U.Sample Composition of 10,000
students (this never happens in the real world)
Total Student Body Numbers/Proportions |
Sample Student Body Numbers |
Sample Student Body Proportions |
Percentage Comparison of Population and Sample Proportions |
Females 5,000/50% |
500 |
50% |
100% representative |
Males 5,000/50% |
500 |
50% |
100% representative |
African American=2,000/20% |
100 Females/100 Males |
10% Females/ 10% Males |
100% representative |
Hispanic=2,000/20% |
100 Females/100 Males |
10% Females/ 10% Males |
100% representative |
Asian=2,000/20% |
100 Females/100 Males |
10% Females/ 10% Males |
100% representative |
Caucasian=2,000/20% |
100 Females/100 Males |
10% Females/ 10% Males |
100% representative |
Other Races=2,000/20% |
100 Females/100 Males |
10% Females/ 10% Males |
100% representative |
A Convenience Sample is a portion of
the population that is NOT scientifically drawn, but is collected
because they are easy to access (IE: a group of ABC U.
students waiting at a bus stop; a group of ABC U. students who
respond to a radio talk show web poll; or a group of ABC U.
students walking around the Student Center). Convenience samples
yield weak results. Or as one of my Mentors, Dr. Tim Heaton, BYU
once said, "If you start the presentation of your research results
with we didn't really do good science, but here's what we
found...then few will stick around or care about what you
found."
It is also important to consider a few other scientific
principles when conducting survey research. You need an adequate
number of respondents or Sample Size, which
is the number of respondents who are designated to take the
survey (30 minimum in order to establish statistical
confidence in the findings).You also have to obtain a relatively
high Response Rate, which is the
percentage of the original sample who successfully completed the
survey. For example, at ABC university if we set out to
survey 1,000 out of the student body of 10,000 students, but only
got 200 to take the survey then our response rate risk being too
low. One would say that 200/1,000=20 percent response rate. While
750/1,000=75 percent response rate. A sample of only 200 would
likely not yield enough diversity in responses to get a broad
understanding of the entire student body's reaction to the football
team issue.
With a high enough response rate and a good scientific sample,
one could feel comfortable comparing the sample's results to what
the entire student body population might have said, had they all
been surveyed. Generalizability means that
the results from the sample can be assumed to apply to the
population with confidence (as though the population
itself had been studied). Also important is the quality of the
survey itself as a scientific instrument. Valid Survey
Questions are questions that are accurate and
measure what they claim they'll measure (IE: If the
football survey asked "Every campus needs a football team" versus
"This campus would benefit from a football team." The first lacks
validity because it isn't really getting the answer needed for the
study, it's seeking an opinion about campuses and football teams in
general). Reliable Survey Questions are
survey questions that are relatively free from bias errors which
might taint the findings. In other words, reliable survey
questions are consistent.
Components of Good Surveys
There are 2 types of survey questions. Open Survey
Questions are questions designed to get
respondents to answer in their own words (IE: "what might
be the benefits of having a football
team?"________________________________ or "what might be a negative
consequence of having a football
team?"________________________________). Closed Survey
Questions are questions designed to get
respondents to choose from a list of responses you provide to
them (IE: About how many college football games have you
ever attended? __1 __2 __3 __4 __5 __6 __7 __8 __9 __10+).
Likert Scale Questions are the most common
response scale used in surveys and questionnaires.
These questions are statements which respondents are asked
to agree or disagree with (IE: Our campus would be deeply
hurt by a football team). The respondents choose from the scale
below for their answer:
1. Strongly disagree 2. Disagree 3. Neither agree nor disagree
4. Agree 5. Strongly agree
Demographic Questions are questions
which provide the basic categorical information about your
respondent including: age, sex, race, education level, marital
status, birth date, birth place, income, etc. In order to
run statistical analysis on survey results, one must enter the data
into Excel, Statistical Packages for the Social Science (SPSS), or
Statistical Analysis Software (SAS) in order to run analysis. Most
statistics are run on numbers. By converting responses into
numbers, most results can be analyzed. For example on the
Disagree...Agree scale above one would use the number 1 in lieu of
Strongly Disagree. Words can be analyzed using content analysis
software. Content Analysis is the counting
and tabulating of words, sentences, and themes from written, audio,
video, and other forms of communication. The goal of
content analysis is to find common themes among the words. For
example if an open ended question such as this were asked, "what
might be a negative consequence of having a football team?" then
the results would be carefully read with tabulations of common
responses. When we asked this question to our university students
in a random sample, the worry about the high expenses required to
fund the team and program was one of the most common negative
consequence reported.
There are a few specific types of data that can be analyzed
using statistical measures. Nominal Data
is data with no standard numerical values. This is
often referred to as categorical data (IE: what is your favorite
type of pet? __Reptile __Canine __Feline __Bird __Other). There is
no numerical value associated with reptile that makes it more or
less valuable than a canine or other type pet. Other examples
include favorite color, street addresses, town you grew up in, or
ice cream flavor. Ordinal Data is rank
ordered data which has standard numerical values. This is
often referred to as numerical data. (IE: How many movies have you
seen in the last two weeks? __0 __1 __2 __3 __4 __5). Ordinal data
has the assumption that seeing 2 movies took twice as much effort
than seeing just 1 movie and seeing 4 movies was twice the effort
of seeing just 2. The values are equally weighted. The same could
be said about how many A's you earned last semester, how much you
get paid per hour at work, or how many cars your family drives;
they are numerical values that can be compared and contrasted.
Ratio Data is data that is shown in
comparison to other data. For example, the Sex
Ratio is the number of males per 100 females in a
society. The sex ratio in the US is reported as follows on
5 February, 2009: Alaska 107/100; US Total 97.1/100; Rhode Island
93.6/100 (these were 2006 estimates from
factfinder.census.gov/servlet/GRTTable?_bm=y&-_box_head_nbr=R0102&-ds_name=ACS_2005_EST_G00_&-_lang=en&-format=US-30)
Ratios provide comparative information and we can see that in 2006
Alaska had more males than females, 7 extra per 100 females. Rhode
Island had nearly 7 fewer males per 100 females.
All of the examples above of football team related questions are
considered variables. Variables are survey
questions that measure some characteristic of the
population (IE: if married students were more financially
strapped than single students, one might find that they were more
or less supportive of a football team based on their perception of
how adding a football team might hinder or support their personal
needs. Marital status as a consideration when comparing the
findings of the survey becomes a variable in its own right). Two
types of variables are measured: dependent and independent
variables. Dependent Variables are survey
variables that change in response to the influence of independent
variables. The dependent variable would be desire or
opposition for a football team and Independent
Variables are survey variables that when
manipulated will stimulate a change upon the dependent
variables (IE: by considering married, widowed, divorced,
separated, cohabiting, and never married students, one might find
differing support/opposition to an ABC U. football team).
When basic statistics are performed on data, we often call theme
measures of central tendency (Mean, Median, or Mode). Consider this
list of numbers which represents the number of movies that 9
separate ABC U. students had seen in the last 2 weeks:
0
1
1
1
3
4
4
5
8
9
The Mean is the arithmetic score of all
the numbers divided by the total number of students (IE:
27÷9=3). The Median is the exact mid-point
value in the ranked list of scores (IE:0, 1, 1, & 1
fall below and 4, 4, 5, & 8 fall above the number 3 thus 3 is
the median). The Mode is the number which
occurs the most in a list of numbers (IE:1 occurs the
most, so the mode is 1). The Extreme Value
is the especially low or high number in the series
(IE: 8 movies in 2 weeks takes an inordinate amount of time for an
average student). Notice that if you removed the 9th
student's score and averaged only the remaining scores the
mean=2.375. Extreme values can throw the mean way off. If you'd
like to learn more about survey research, then take a research
methods class. Chances are you will enjoy taking on the role of
statistical detective. Here is an overview of simple questions to
see if you are building a good survey.
- What do you want to accomplish in this survey?
- Who will your survey serve?
- Who is the target audience for the survey?
- How will the survey be designed?
- How will you obtain a sample for the survey?
- How will the survey be administered?
- How big should your response rate be to give your results
credibility?
- How will the data be analyzed?
- How will the results be presented?
- Are humans or animals going to be at risk of harm in the
survey?
Components of a good survey include: clear
purpose for taking the survey; clear understanding of desired
outcomes of survey; good research supporting development and design
of survey; appropriate sampling technique when collecting survey;
reliability and validity in survey and its question and design; and
clear and accurate presentation of survey findings that are
appropriate for the type of survey used.
- Have you ever attended a college football or basketball game?
__Yes __No
- Are you in favor of spending all of ABC U's money on an
expensive football program? __Yes __No
- Are you not opposed to supporting a football program? __Yes
__No
- I think the ABC U's administration pays too much attention to
community service.
1 Strongly Disagree 2 Disagree 3 Donít know 4 Agree 5 Strongly
Agree
- It would be fiducially incompetent to initiate the
cost-to-benefit ratio projections for a football team.
1 Strongly Disagree 2 Disagree 3 Donít know 4 Agree 5 Strongly
Agree
- Double barreled question...it asks two questions in one and you
canít clearly answer.
- Biased question...uses emotionally laden language which might
change the response.
- Double negative...creates confusion.
- Irrelevant question for the survey about student interest in a
football team.
- Too many technical words that the average person would not
understand...creates confusion.
Better Versions of the Same Questions
- Have you ever attended a college football game? __Yes __No
- Have you ever attended a college basketball game? __Yes
__No
- Are you in favor of ABC U. spending student fees on a football
program? __Yes __No
- Are you in favor of a football program? __Yes __No
- I think the ABC U.'s administration should hold forums with
students about the issue of a future football program.
1 Strongly Disagree 2 Disagree 3 Don't know 4 Agree 5 Strongly
Agree
- I am concerned about a new football program being too
expensive.
1 Strongly Disagree 2 Disagree 3 Don't know 4 Agree 5 Strongly
Agree
Which Responses Categories Are Useful For Which Survey
Question?
It Depends on the Question!
- 1 ___Yes 0___No
- 4 Excellent 3 Good
2 Fair 1 Poor
- 5 Very Likely 4 Somewhat
Likely 3 No Preference 2 Unlikely
1 Very Unlikely
- 0 Never 1 Seldom
2 Often 3 Regularly
- 1 Strongly Disagree 2
Disagree 3 Don't know 4 Agree
5 Strongly Agree
- 1 Strongly Disapprove 2
Disapprove 3 Don't know 4 Approve
5 Strongly Approve
- 3 Better 2 About the Same
1 Worse
When doing sociological research it helps if you understand the
SMART Paradigm
- Samples
- Methods
- Attitude of skepticism
- Researcher bias
- Thorough understanding of literature
Samples have to be random and representative.
If not the results are fairly worthless. Remember that you
shouldn't start a conversation about your data by saying "We didn't
really do good scientific sampling, but here's what we've found..."
Most people won't care about your findings after they know your
science was weak. I compare it to this hypothetical incident. Your
car is broken down late at night in a dangerous part of town. A
passerby stops to help and says, "I don't know how to fix cars, but
I'll go ask those people hanging out at the bus stop. He returns 10
minutes later and explains that 3 of the people there once had
their cars break down and every time it was their spark plugs. So
I'd recommend you change your spark plugs." Believe me, I know this
is a cheesy example, but it conveys the point. Asking three people
at a bus stop is a convenience sample of people (not even
mechanics). True, it does look and feel like a survey, but it is a
terrible sample.
I watch this all the time on TV news stories where a few people
on the street give their opinions; Internet polls where people who
visit certain Websites give their opinions; and radio talk shows
where votes are counted among those who are selected to comment on
the air are treated as though they somehow represent all people
everywhere. Smart people always check the sample for
representativeness and random selection.
Methods typically include: experiments,
participant observations, non-participant observations, surveys,
and secondary analysis. Experiments are
studies in which researchers can observe phenomena while holding
other variables constant or controlling them. In
experiments, the experimental group gets the treatment and the
Control group does not get the treatment. Even though Sociologists
rarely perform experimental surveys, it is important to understand
the rigors required to execute this type of research. In this
example let's assume that researchers are testing the affect of a
drug called XYZ. Among Herpes sufferers, XYZ may help to completely
repel an outbreak. But, how can you discern if it was the medicine
or simply that patient improvement came because they were in the
study? We'd need some form of control/controls. In the diagram
below you can see how scientists might administer an experimental
study. If they took 300 patients and randomly assign them to: Group
A which was an inert gum-only control; Group B which was the gum
and sugar control (yes, sometimes 2 control groups are needed); or
Group B which is the experimental XYZ laced gum.
Figure 1. Experimental Research Design
© 2005 Ron J. Hammond, Ph.D.
Let's assume that the patients chewed their respective chewing
gums for 11 months then the medical results were gathered. Look at
the next diagram below to see a set of hypothetical results. Group
A was the control-gum only group and they showed a 5 percent
improvement. Group B was the control-gum and sugar group and they
showed a 7 percent improvement. Group C was the
experimental/treatment group and they showed a whopping 27 percent
improvement. Now one study like this does not an FDA approved drug
make. But, the results are promising. Interestingly, this is a
pharmaceutical, medical study...not a sociology study. Almost all
experiments are very tightly controlled and many transpire in
laboratories or under professional clinical supervision.
Sociologists rarely study in laboratories. Scientists who do
perform experiments can make causal conclusions. In order to
establish cause there must be 3 criteria that are met: a
correlation, time ordering (one preceded the other); and no
spurious correlations. In the case of education and crime these 3
are not met. Causation means that a change
in one variable leads to or causes a change in another variable, or
XYZ chewing gum causes less Herpes outbreaks.
Figure 2. Example of a Drug-Related Experimental Research
Design
© 2005 Ron J. Hammond, Ph.D.
Sociologists do perform studies that allow for correlation
research conclusions. There are three types of correlations.
Direct Correlation means that the
variables change in the same direction (IE: the more
education you have the more money you make). Inverse
Correlation means that the variables change in
opposite directions (IE: the more education you have the
less criminal activity you get caught doing). Spurious
Correlation is an apparent relationship between
two variables which indicates their relationship to a third
variable and not to each other (IE: the more education you
have, the higher your family's standard of living and the lower
your likelihood of participating in criminal activities). In other
words, there are other correlated factors that influence criminal
behavior which are simultaneously at play.
Sometimes Sociologists perform Field Experiments
- studies which utilize experimental design but are
initiated in everyday settings and non-laboratory environments. For
example, a sociologist might manipulate the levels of lighting to
study how factory work performance is impacted (Google Hawthorn
Effect). A few other methods are sometimes used by Sociologists.
Participant Observation=a research method where the researcher
participates in activities and more or less assumes membership in
the group she studies. Content Analysis is when
the researcher systematically and quantitatively describes the
contents of some form of media. Secondary Analysis= the analysis of
data that have already been gathered by others.
Just for fun I've added an interesting survey my students and I
developed to study dating patterns here at UVU in 2006. Some of my
students were interested in why we are drawn to those we date and
which factors lead us toward staying together or breaking up. In
this survey we are trying to establish some of the top reasons
people are breaking off their relationships. We have established
three influential categories: safety, economics, and
attractiveness. This focus group will help us to organize our
concerns about why individuals and their partners are "breaking
up." Please take a few moments to answer the questions below and
please be ready to discuss some of your comments or concerns.
Please respond to the questions below using this response
scale:
1 Strongly Disagree 2 Disagree 3 Don't know 4 Agree 5 Strongly
Agree or __1 __2 __3 __4 __5
- Safety
- I consider sexual security more important than Emotional
security __1 __2 __3 __4 __5
- I have a fear of date rape when I am out on a date __1 __2 __3
__4 __5
- I feel that while on a date I am aware of the other person's
safety __1 __2 __3 __4 __5
- When confronted with a potentially dangerous situation in a
date setting I am likely to suggest a safer alternative __1 __2 __3
__4 __5
- Adventure is more important to me then safety __1 __2 __3 __4
__5
- Abstinence before marriage is an important attribute to me __1
__2 __3 __4 __5
- Economics
- Love is more important to me then money __1 __2 __3 __4
__5
- Education in someone I am dating is important to me in my
economic security __1 __2 __3 __4 __5
- I am attracted to the leader type __1 __2 __3 __4 __5
- It is important in my future for the other person to be
financially supportive __1 __2 __3 __4 __5
- I expect my date to be willing to pay for my dating expenses
__1 __2 __3 __4 __5
- At the end of the date I expect some sort of physical assurance
__1 __2 __3 __4 __5
- I am more attracted to physical appearance then I am to money
__1 __2 __3 __4 __5
- Attraction
- I am more drawn to physical appearance then I am to personality
__1 __2 __3 __4 __5
- I am more drawn to a potential girlfriend/boyfriend if they
express the same interests as me __1 __2 __3 __4 __5
- I am more drawn to a potential girlfriend/boyfriend if they
express the same spiritual interests as me __1 __2 __3 __4 __5
- I am attracted to skill over charm __1 __2 __3 __4 __5
- I am drawn to someone in control over someone who is sensitive
__1 __2 __3 __4 __5
- I am drawn to someone who is capable over someone who is needy
__1 __2 __3 __4 __5
- I prefer to date someone my age or younger. __1 __2 __3 __4
__5
- I agree with the statement: "Once a cheater, always a cheater?"
__1 __2 __3 __4 __5
- I feel that my chances of potential marriage are diminished
after ages __19-22 __23-25 __26-29 ____30+
- My age in years:____
- My sex: __Female __Male
- My class standing: __Freshmen __Sophomore __Junior
__Senior
- My Marital Status: __Never Married __Live with someone
(cohabit) __Divorced/Sep. __Widowed __Married
- My race: __Native American __Asian __Hispanic __African
American __Caucasian __Mixed
- I consider the home I grew up in to be: __Upper class __Middle
class __Lower class __Working poor
- I'd like to find someone with whom I can live: __Upper class
__Middle class __Lower class __Working poor
- About how many dates have you had to this point in your life:
___Lots __Average __Few __None