Research

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Basic Research

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research for the sake of research, more exploratory.

Ex.) Is there a difference in microbial makeup of urban trees v. rural trees?

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Applied Research

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research aimed at producing or applying a theory, procedure, or technology to solve a problem

Ex.) Developing drones for the use of more accurate and less invasive deer counts at Wild Basin

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Exploratory Research

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examines a new area to formulate that he or she can address more specifically in future research. Addresses the “what” question, what is the social activity really about? Tends to rely on qualitative data and is less likely to use a specific theory.

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Descriptive Research

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When you have basic information on a subject and are ready to describe it in greater depth. Focuses on “how” and “who”. Descriptive research uses data-gathering techniques. Results show who holds a particular view or engages in specific behavior.

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Explanatory Research

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identifies the source of social behavior, beliefs, conditions, and events, documents causes, tests, theories, and provides reasons. Often asks the question “why?” Tests theories or examines whether a theory can explain new situations or hypothesis’.

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(Time Dimension) Cross-Section

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examine a single point in time

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(Time Dimension) Longitudinal Research

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examine features of people or other units at more than one time

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(Longitudinal Research) Time series study

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researchers gathers same type of information across two or more series of times

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(Longitudinal Research) Panel study

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when the researcher observes exactly the same people across multiple time points

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(Longitudinal Research) Cohort Study

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like panel study but the study focuses on on a category of people who share a similar life experience.

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(Longitudinal Research) Case study

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examines the features if any people or units, or an entire population.

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Experimental Study

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involves at least one manipulation (independent variable) while holding all other variables constant

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(Experimental) Case Study

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normally just an observation with no purposeful manipulation--researcher will have to try and separate variables after observing.

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Types of Harm

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Physical harm (rare)

Psychological abuse, stress, or less of self-esteem( Standford experiment)

Legal harm

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Informed Consent

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an agreement by participants stating that they are willing to be in a study and know something about what the procedure will involve.

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Quantitative Research

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get quantifiable data (you get numbers)

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Qualitative Research

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(no numbers) - is primarily exploratory research. It is used to gain an understanding of underlying reasons, opinions, and motivations. It provides insights into the problem or helps to develop ideas or hypotheses for potential quantitative research.

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Independent Variables

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Y, affects the dependent

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Dependent Variables

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X affected by the independent

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Null Hyopthesis

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hypothesis that states no relation. For every hypothesis you need a null hypothesis.

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Alternative Hypothesis

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AKA research hypothesis

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Spuriousness

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A statement that appears to be a causal explanation, but not because of initially unseen variable

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Reliability and Validity

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(think of the bullseye and the darts)

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Reliability

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being able to consistently get the same results. Test and retest!

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Validity

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Having accurate results.

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Indicators

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the kinds of observations used to measure the concept

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Levels of Measurement

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level determines the analysis that you can do with your results

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Indexes and Scale

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quantifying qualitative information

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Likert Scale

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When responding to a Likert questionnaire item, respondents specify their level of agreement or disagreement on a symmetric agree-disagree scale for a series of statements. Thus, the range captures the intensity of their feelings for a given item

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Probability Sampling

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any method of sampling that utilizes some form of random selection. In order to have a random selection method, you must set up some process or procedure that assures that the different units in your population have equal probabilities of being chosen.

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(Probability) Stratified Random Sampling

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also sometimes called proportional or quota random sampling, involves dividing your population into homogeneous subgroups and then taking a simple random sample in each subgroup. In more formal terms:

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(Probability) Systematic Random Sampling

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pick every 10th name

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(Probability) Cluster Sampling

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sample everyone in cluster

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(Probability) Systematic Sampling

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pick every 10th name

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(Non Probability) Sampling

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Non-probability sampling is a sampling technique where the samples are gathered in a process that does not give all the individuals in the population equal chances of being selected.

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Convenience Sampling

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is probably the most common of all sampling techniques. With convenience sampling, the samples are selected because they are accessible to the researcher. Subjects are chosen simply because they are easy to recruit. This technique is considered easiest, cheapest and least time consuming.

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Consecutive Sampling

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very similar to convenience sampling except that it seeks to include ALL accessible subjects as part of the sample. This non-probability sampling technique can be considered as the best of all non-probability samples because it includes all subjects that are available that makes the sample a better representation of the entire population.

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Quota Sampling

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is a non-probability sampling technique wherein the researcher ensures equal or proportionate representation of subjects depending on which trait is considered as basis of the quota.

For example, if basis of the quota is college year level and the researcher needs equal representation, with a sample size of 100, he must select 25 1st year students, another 25 2nd year students, 25 3rd year and 25 4th year students. The bases of the quota are usually age, gender, education, race, religion and socioeconomic status.

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Snowball Sampling

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usually done when there is a very small population size. In this type of sampling, the researcher asks the initial subject to identify another potential subject who also meets the criteria of the research. The downside of using a snowball sample is that it is hardly representative of the population.

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Purposive Sampling

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based on previous studies

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Inferential Statistics

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a branch of applied mathematical or statistics based on a random sample. It lets a researcher make precise statements about the level of confidence he or she has in the results of a sample being equal to the population parameter.

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Pitfalls of Survey Questions

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Question Wording: & Response Problems

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Question Wording

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-Ambiguous questions

-inappropriate or technical vocabulary

-double-barreled questions

-emotionally laden words

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Response Problems

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-1 Memory Distortions

-2 Response Bias -Social desirability answers

-desire to please interviewer

-ordinal or position bias

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Open Questions

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qualitative & wide range of answers, hard to generalize; gives insight for other possible variables

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Closed questions

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quantitative, statistical analysis, have to be well written, generalizable

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Experimental Design

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has pretest/post-test, control group, randomization

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Quasi-Experimental Design

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same as experimental design but lack the randomization of the control group or treatment group

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Internal Validity

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having complete control over your experiment/experimental design. Accuracy of your measures

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Testing Effect

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when people become aware that they are being tested so act differently

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Selection Bias

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when you choose subjects to be tested on not randomized

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External Validity

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having the ability to “generalize” or apply your findings to the “real world”. Or generalizability of your measures to the concept you are trying to measure

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Reliability

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consistency of your mesures

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Double Blind Experiment

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Where the the administrators of the experiment do not know which group is the control and which group is the experimental.

Helps to control bias and promotes internal validity

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Placebo Effect

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When individuals have an experience an effect after taking a placebo. Typically due to the placebo recipients expectations of certain effects.

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History Effect

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events that happen in the environment that change the conditions of a study, affecting its outcome. Such a history event can happen before the start of an experiment, or between the pre-test and post-test.

To affect the outcome of an experiment in a way that threatens its internal validity, a history effect must

(a) change the scores on the independent and dependent variables, and

(b) change the scores of one group more than another (e.g., increase the scores of the treatment group compared with the control group or a second treatment group)