A person who provides data for analysis by responding to a survey questionnaire
-A document containing questions and other types of items designed to solicit information appropriate for analysis
-Questionnaires are used primarily in survey research but also in experiments, field research, and other modes of observation
self administered questionnaire
the respondent is asked to complete the survey themselves
That quality of measurement device that tends to result in a misrepresentation of what is being measured in a particular direction
A data-collection encounter in which one person (an interviewer) asks questions of another (a respondent)
computer-assisted telephone interviewing
A data collection technique in which a telephone-survey questionnaire is stored in a computer, permitting the interviewer to read the questions from the monitor and enter the answers on the computer keyboard
A form of research in which the data collected and processed by one researcher are reanalyzed-often for a different purpose-by another
open ended questions
Questions for which the respondent is asked to provide his or her own answers
- in depth, qualitative interviewing relies almost exclusively on open-ended questions
close ended questions
Survey questions in which the respondent is asked to select an answer form among a list provided by the researcher
-Popular in survey research because they provide a greater uniformity of responses and are more easily processed than open-ended questions
A survey question intended for only some respondents, determined by their responses to some other question
A technique employed in interviewing to solicit a more complete answer to a question
random digit dialing
A sampling technique in which random numbers are selected from within the ranges of numbers assigned to active telephone
the number of people participating in a survey divided by the number selected in the sample. It appears as a percentage. Also called the completion rate or for self-administered survey it's called the return rate- the % of surveys that are returned.
what are the guidelines for asking questions?
choose appropriate questions, avoid double barreled questions, make items clear, Rs must be competent to answer, questions are relevant, short items are best, avoid negative items, avid biased items
Factors that affect questionnaire format
contingency questions, matrix questions, order of items, instructing and pretesting
3 main methods of questionnaires
1) self administered 2) administered by interviewers face to face 3) surveys administered by phone
what to do for self administered
mail distribution and return, monitoring returns, follow up mailings
General guidelines for interviewing
appropriate appearance, familiarity with the questionnaire, following question wording exactly, recording responses exactly, probing for responses.
Strengths of survey research
describing the characteristics of a large population, make large samples feasible, flexible (let you develop definitions from actual observations), standardized questionnaires have an important strength in regard to measurement, save money
weaknesses of survey research
questions may not fit all populations, can appear superficial or artificial in covering a topic, seldom deal with the contexts of social life, inflexible (initial study design remains constant)
weak on validity and strong on reliability.
the process of transforming raw data into standardized form
w? content analysis- underlying meaning of communications
w/content analysis- concrete terms contained in a communication
the study of recorded human communications
methods of studying social behavior without affecting it.
unit of analysis
the individual units that we make descriptive and explanatory statements about (what we are studying)
strengths of content analysis
cheap, allows for correction of errors, safe, used to study processes over a long period of time or at one pint in time
weaknesses of content analysis
limited to recorded communication, raise issues of validity and reliability
ethical considerations of using unobtrusive measures
confidentiality and protecting privacy, report findings honestly, report what you fond insured of supporting hypothesis
describing a measure that accurately reflects the concept it is inter to measure
problems of validity
Often the existing data does not cover exactly what you are interested in, The measurements used may not be altogether valid representations of the variables and concepts we want to make conclusions about, can't use replication
The quality of measurement method that suggests the same data would have been collected each time in repeated observations of the same phenomenon,
problems of reliability
Overall quality or changes in quality of the record keeping system can affect reliability
factors to consider when analyzing existing statistics
When was the data collected?
Who collected the data?
How was the data collected?
Over what time period was the data collected?
What was the agenda of the group or organization that collected the data?
Are these existing statistics representative of an entire population?
when do social scientists use comparative and historical research?
When they want to trace a concept or phenomena over time
To set the context of a particular concept or issue
When they want to study a concept or issue that occurred at particular point in time (back in history)
the numerical representation and manipulation of observations for the purpose of describing and explaining the phenomena that those observations reflect.
the document used in data processing and analysis that tells the location of different data items in a data file.
the analysis of a single variable, for purposes of description
a description of the number of times the various attributes of a variable are observed in a sample.
a format for presenting the relationship among variables as percentage distributions.
a measure of central tendency
an average computed by summing the values of several observations and dividing by the number of observations.
an average representing the most frequently observed value or attribute.
an average representing the value of the "middle" case in a rank-ordered set of observations.
refers to the way that values are distributed around some central value, such as an average.
a measure of dispersion around the mean, calculated so that approximately 68 percent of the cases will lie within plus or minus one standard deviation from the mean, 95 percent within two, and 99.9 percent within three standard deviations.
a variable whose attributes form a steady progression, such as age of income.
a variable whose attributes are separate from one another, such as gender or political affiliation.
the analysis of two variables simultaneously, for the purpose of determining the empirical relationship between them.
What does the quantification of data involve?
It involves coding data into categories that are given numerical representations.
Much data is already numerical
Coding Scheme- researchers can use an existing coding scheme, as the U.S. Census Bureau's categorization of occupation OR they can develop their own.
Codebook is the document that describes (1) your codes or identifiers assigned to different variables and 2) the codes assigned to the attributes
What is the value of subgroup comparisons?
Subgroup comparisons can be used to describe similarities and differences among subgroups with respect to some variables.
How does ethics relate to Quantitative Data Analysis?
Unibased analysis and reporting is as much an ethical concern in quantitative analysis as in qualitative analysis.
Subject's privacy must be protected in quantitative data analysis and reporting.
statistical computations describing either the characteristics of a sample or the relationships among variables in a sample. Descriptive statistics merely summarize a set of sample observations.
proportionate reduction of error
a logical model for assessing the strength of a relationship by asking how much knowing values on one variable would reduce our errors in guessing values on another variable.
Nominal measures merely offer names or labels for characteristics
Examples would be gender,, religious group, political party. birthplace., college major or hair color
Ordinal variables are variables we can logically rank order. In other words, the numbers assigned to the attributes of the variable mean something.
a level of measure describing a variable whose attributes are rank-ordered and have equal distances between adjacent attributes.
E.g. inches, feet, degrees, age, income
a level of measurement describing a variable with attributes that have all the qualities of nominal, ordinal and interval measures AND IN ADDITION ARE BASED ON A TRUE ZERO point. AGE is an example of a ratio measure.
the likelihood that the relationship observed in a sample could be attributed to sampling error alone.
geographic information systems
analytic technique in which researchers map quantitative data that describe geographic units in a graphic display.
a method of data analysis in which the relationships among variables are represented in the form of an equation, called a regression equation.
linear regression analysis
a form of statistical analysis that seeks the equation for the straight line that best describes the relationship between two ratio variables.
a form of statistical analysis that seeks the equation representing the impact of two or more independent variables on a single dependent variable.
a form of regression analysis in which the effects of one or more variables are held constant, similar to the logic of the elaboration model.
a form of regression analysis that allows relationships among variables to be expressed with curved geometric lines instead of straight ones.
A frequently used test of significance for use with nominal variables
assist researchers in drawing conclusions about their observations, make inferences about the larger population from which the sample observations are draw.
Applies the logic of statistical significance.
Used for examining
Can be used when the dependent variable is interval or ratio and the independent variable is nominal or ordinal
Measure for judging the statistical significance of differences between groups
tests of statistical significance
a class of statistical computations that indicate the likelihood that the relationship observed between variables in a sample can be attributed to sampling error alone.
level of significance
the degree of likelihood that an observed, empirical relationship could be attributed to sampling error.
What is the purpose of regression analysis?
allows you to predict values for a population based on a sample if the sample is randomly selected.
enables the researcher to examine the effect of multiple independent variables on a dependent variable simultaneously.
What is the purpose of bivariate anlaysis?
to examine the relationship between two variables and to see if this is a statistically significant relationship.
What are things to keep in mind when you analyze existing statistics?
How to evaluate quality of internet sights
who is the author, is it advocating a particular point of view, give complete and accurare references, is data up to date, is the data official, university, data is consistent