Research Flashcards
Qualitative
Concerned with understanding human behavior from the informant’s perspective, Assumes a dynamic and negotiated reality. Data are collected through participant observation and interviews. Data are analyzed by themes from descriptions by informants. Data are reported in the language of the informant.
Quantitative
Concerned with discovering facts about social phenomena. Assumes a fixed and measurable reality. Data are collected through measuring things. Data are analyzed through numerical comparisons and statistical inferences. Data are reported through statistical analyzed.
Validity
Refers to the extent to which a measure reflects the true characteristics of what the researcher is trying to measure.
Reliability
Refers to the consistency in the measurement of a variable. EX: measuring the same subjects under the same conditions at a later time should yield the same results.
Causality
is what connects one process (the cause) with another process or state (the effect), where the first is partly responsible for the second, and the second is partly dependent on the first. In general, a process has many causes,which are said to be causal factors for it, and all lie in its past. An effect can in turn be a cause of, or causal factor for, many other effects, which all lie in its future. Is metaphysically prior to notions of time and space.
Control Group
In a research experiment, the group that is treated exactly like the experimental group except for not experiencing the independent variable being studied,
Quasi-Experiment
Is designed a lot like a true experiment except that in the quasi-experimental design, the participants are not randomly assigned to experimental groups. EX:
Dr. Jones is a personality expert who studies the impact that personality traits have on intelligence. For the purposes of her current research project, she is interested in examining the IQ scores of people who score highly in each of the five ‘Big Five’ personality factors. Each of the five personality factors are a quasi-independent variable. Personality traits are inherent to each person, so random assignment cannot be used. Participants would initially be assigned to groups based on their personality assessment score across each of the five personality factors.
Formative Research
is exploratory and is done at the beginning of the design project to guide the entire process. It is used to gain insight into the subject the project deals with and helps in problem identification and solving.
Summative Research
(conclusion research) is done at the end of a project and is used to determine its success. It can also gauge customer satisfaction or aid in the development of future projects. Summative research is used to frame the outcome of an investigative process
Hypothesis
Statement about a relationship between 2 or more variables that can be tested w/ an outcome that one may confirm, fail to confirm or refute.
Null Hypothesis
Asserts there is no significant relationship between two variables.
Variable
A characteristic possessed by everyone in the population in varying amounts or kinds.
Variable Include: Independent Variable
Variable believed to cause some variation in another variable. Ex: A treatment that may generate change.
Variable Include: Dependent variable
Variable whose variation must be explained. EX: Particular behavior such as alcohol abuse.
Variable Include: Intervening and Extraneous Variable
- Variable that comes between the independent and dependent variables.
- It modifies the variation of dependent variable that was thought to result from the effects of independent variable.
- Researcher may be unaware or unable to control the effects of these variables.
Research Design: Exploratory Studies
Used to explore an area of knowledge where little is known and to gain familiarity with real life settings, problems, or phenomena.
Research Design: Descriptive Studies
Generally used when there is more knowledge than in exploratory studies: - concerned with facts- studies small representative sample to infer broader population- may be used to describe the characteristics of a population.
Research Design: Experimental Studies
The most rigorous of all studies. The always involve testing a prediction by manipulating an independent variable and measuring the effect on a dependent variable. The purpose is to TEST FOR CAUSALITY.
Types of Experimental Studies: Field Experiment
Conducted in a concrete, natural environment. The researcher doesn’t have tight control over the experiment Ex. Nutrition test during which the subject has access to all kinds of foods other than those mandated by the experiment.
Types of Experimental Studies: Laboratory Experiment
Tests conducted under tightly controlled laboratory conditions. Might not be so conducive since its not the real world. Ex. Testing drugs on lab mice for humans.
Types of Experimental Studies: Ex Post Facto
Seeks the cause of change in the dependent variable. Here one looks at the relationship between the independent v. and dependent v. under various conditions of a third variable.
Placebo:
Treatment given to a control group to convince them they are being exposed to the experimental variable.
Hawthorne or Test-Taking Effect:
The act of being studied may in itself produce some changes in the subjects. Ex. You might get more work done if your Director is in the same room.
Measurement Problems
The basic problem in evaluation measurement results is defining true differences and distinguishing these variations that result from measurement errors.
Tests of Reliability: Test-Retest
Provides evidence of stable scores. The test is administered once then again.
Tests of Reliability: Split Half
Each item in a test is randomly assigned a place in the test. The test is then split into two halves, each half considered comparable to the other. Then the degree of correlation between the scores is taken as a measure of the reliability of the total test.
Tests of Validity: Concurrent Validity
The measure used in a study is compared with another instrument presumed to measure the same variable. High correlation results indicates concurrent validity of the instrument.
Tests of Validity: Content Validity
If the experts judge the test to be a good measurement of what is being studied, the test has content validity.
Tests of Validity: Predictive Validity
A measure is used in a study is compared with some predicted future outcome.
Tests of Validity: Construct Validity
The degree to which a measure relates to other variables expected within a system of theoretical relationship.
Scales of Measurements:
Research is also concerned with appropriate msmt. Scale.
Scales of Measurements: Nominal
Two or more of the same categories ( pass/fail, male/female).
Scales of Measurements: Ordinal
The score show each subject’s position with respect to a particular characteristic. Example: who scores first, second, etc.
Scales of Measurements: Interval
The higher-level scale shows ordinal positions with equal intervals btwn scores.examples: scores on licensing exam, height, weight.
Scales of Measurements: Ratio
An interval scale with an absolute zero.
Types of Samples: Simple random sample
Subjects are drawn randomly each subject has an equal chance of inclusion in the sample.
Types of Samples: Stratified Random Sample
Subjects are first grouped into strata of interest( age, sex, ethnicity) and then drawn randomly from each group.
Types of Samples: Cluster Random Sampling
Multiple stage sampling in which successive random samples are drawn from natural groups (clusters) this is not possible/too expensive.
Statistics
Statistics are numerical facts or data that provide descriptive or analytical information about a given subject.
Descriptive Statistics:
Computations that Describe some characteristics of a group or sample. Types: *Mean- the average *Median: midpoint of a series of scores *Mode: most frequent score.
Measure of Variability: Measures of dispersion
To determine dispersion or spread of scores around the central tendency (central tendency: measure the degree to which findings cluster together ex. Normal bell curve.)
Measures of dispersion:
- Range: lowest to highest.
- Standard deviation: the most stable measure of variability.
- Normal Bell curve: see diagram in text book.
Statistical Tests of significance: Null Hypothesis
The hypothesis that there is “no difference” that is actually subjected to statistical testing.
Statistical Tests of significance: Type 1 Error
The chance rejecting the null hypothesis when it should be accepted.
Statistical Tests of significance: Type II Error
The chance of rejecting the null hypothesis when is should be rejected.
Correlation Coefficient:
The symbol “r” represents the correlation coefficient. If the “r” equals 1 then the correlation coefficient is perfect. The closer the “r” gets to 1, the stronger the association r = .80 is stronger than r = .30
