Final

Front 1

Miss Evers' Boys

Back 1

-Aged black nurse testifies before the 1973 Senate hearings into the Tuskegee study
-Flashbacks, testimony evokes 1932 origin&four-decade study but not treat syphilis in the black men of Macon County, Alabama
-nurse attached to patients
-Dixie band named Evers' Boys
-doctor supervisor wanted to end, 10 years
-intelligent lover Caleb rebelled, took penicillin and enlisted, project continues
-refuses to leave alabama with Caleb
-one by one all die

Front 2

Kinsey

Back 2

-1940s
-Mac
-Over 18000 US men and women
-Denounced repressive social attitudes
-Oral & premarital sex

-Sample was not random. Instead, it consisted largely of well-educated, white city dwellers.

-___ and his colleagues used questionable methods to gather their data, especially asking leading questions when interviewing subjects.

-May have let his own beliefs influence his results.

Front 3

APA Guidelines

Back 3

Your essay should include four major sections:
-Title Page, Abstract, Main Body, and References.

Front 4

Action Research Design

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(aims to contribute both to the practical concerns of people in an immediate problematic situation and to the goals of social science by joint collaboration within a mutually acceptable ethical framework. )

WHAT THEY TELL YOU
1) Collaborative & adaptive research design, use in work or community
2)Design focuses on pragmatic & solution-driven rather than testing theories
3) When practitioners use, potential to increase amount they learn consciously (learning cycle)
4) Direct and obvious relevance to practice
5) No hidden controls or preemption of direction

WHAT DON'T TELL YOU
1) Harder than conducting conventional studies (encourage change and research)
2) Harder to write b/c can't use standard format to report
3) Personal over-involvement may bias
4) Cyclic nature to achieve twin outcomes of action and research is time-consuming and complex

Front 5

Case Study Design

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( -in-depth study of a particular research problem rather than a sweeping statistical survey.
-used to narrow down a very broad field of research into one or a few easily researchable examples.
-useful for testing whether a specific theory and model applies

WHAT TELLS YOU

1) Excels at bringing to understanding of complex issue through detailed contextual analysis of limited number of events or conditions and relationships
2) Apply variety of methodologies, rely on variety of sources
3) Extend exp/ add strength to what known
4) Social scientists wide use to examine contemporary real-life
5) Provide detailed descriptions of specific and rare cases

WHAT DON''T TELL YOU
1) Single/small # cases = little basis establish reliability or generalize findings
2) Intense exposure = bias
3) Design not facilitate cause and effect relationships
4) Vital info missing
5) Case not rep/typical of larger problem
6) If criteria unusual, interpretation only apply to that particular case

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Casual Design

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-understanding a phenomenon in terms of conditional statements in the form,
x “If X, then Y.”
-used to measure what impact a specific change will have on existing norms and assumptions.

WHAT TELL YOU
1) Helps understand why world works the way it does casual link b/w variables and eliminating other possibilities
2) Replication
3) Greater confidence of internal validity bc systematic subject selection and equity of groups

WHAT DON'T TELL YOU
1) Not all relationships casual
2) Conclusions difficult to determine bc variety of variables in social env
3) If 2 variables correlated, cause must come before effect. Sometimes hard to determine

Front 7

Cohort Design

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-Medical science, social
-study over long time
-open: pop defined by state of being part of study question, size not constant
-closed: enter study at one point in time and no new can enter

What do these studies tell you?

-cohorts mandatory because a randomized control study may be unethical.
-measure potential causes before the outcome has occurred, can demonstrate “causes” preceded the outcome
-highly flexible, can provide insight into effects over time, related to a variety of different types of changes [e.g., social, cultural, political, economic, etc.].
-Either original data or secondary data can be used in this design.

What these studies don't tell you?

-comparative analysis of two cohorts, a researcher cannot control other factors : confounding variables.
-can end up taking a long time to complete, increases the chance that key variables change
-lack of randominization, external validity lower than study designs where the researcher randomly assigns participants.

Front 8

Cross-Sectional Design

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(no time dimension, a reliance on existing differences rather than change following intervention; and, groups are selected based on existing differences rather than random allocation.)

WHAT TELL YOU
-'snapshot' of the outcome and the characteristics, at a specific point in time.
-Unlike experimental design(active intervention by the researcher to produce and measure change or to create differences) focus on studying inferences from dif bw people, subjects, or phenomena.
-collecting data at and concerning one point in time. (longitudinal studies involve taking multiple measures over an extended period of time,)
-Groups purposely selected based upon existing differences in the sample
-capable of using data from a large number of subjects , unlike observational studies, not geographically bound.
-estimate prevalence of an outcome of interest bc the sample taken from population.
-generally use survey techniques to gather data, relatively inexpensive and take up little time to conduct.

What these studies don't tell you?

-Finding people, subjects, or phenomena to study similar one specific variable can be difficult.
-Results are static and time bound ,give no indication of a sequence of events/reveal historical contexts.
-cannot be utilized to establish cause and effect relationships.
-snapshot of analysis ,possibility differing results if another time-frame had been chosen.
-No follow up to findings

Front 9

Descriptive Design

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(provide answers to the questions of who, what, when, where, and how associated with a particular research problem)

WHAT DO TELL YOU

-Subject observed in natural&unchanged natural environment. True experiment often adversely influence the normal behavior of the subject.
-often used as a pre-cursor to more quantitatively research designs, valuable pointers to variables are worth testing quantitatively.
-If the limitations are understood, useful developing focused study.
- rich data that lead to important recommendations.
-collects a large amount of data for detailed analysis.

What these studies don't tell you?

1) Results not be used to discover a definitive answer or to disprove a hypothesis.
2)utilize observational methods [as opposed to quantitative methods], the results cannot be replicated.
3) heavily dependent on instrumentation for measurement and observation.

Front 10

Experimental Design

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(blueprint of the procedure that enables the researcher to maintain control over all factors that may affect the result of an experiment)

WHAT DO TELL

1) allows researcher control the situation, answer the question, “what causes something to occur?”
2) identify cause and effect relationships between variables and to distinguish placebo effects from treatment effects.
3) support ability to limit alternative explanations and to infer direct causal relationships in the study.
4) highest level of evidence for single studies.

What these studies don't tell you?

1) Design is artificial, and results may not generalize well to the real world.
2) The artificial settings alter subject behaviors or responses.
3) costly if special equipment or facilities are needed.
4) problems cannot be studied bc of ethical or technical reasons.
5) Difficult apply ethnographic & qualitative methods

Front 11

Exploratory Design

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(conducted about a research problem when there are few or no earlier studies to refer to)

GOALS
- Familiarity with basic details, settings and concerns.
- Well grounded picture of the situation being developed.
- Generation of new ideas and assumption, development of tentative theories or hypotheses.
- Determination about whether a study is feasible in the future.
- Issues get refined for more systematic investigation and formulation of new research questions.
- Direction for future research and techniques get developed.

WHAT TELL YOU

1) useful approach for gaining background information on a particular topic.
2) flexible and can address research questions of all types (what, why, how).
3) opportunity to define new terms and clarify existing concepts.
4) generate formal hypotheses and develop more precise research problems.
5) Establish research priorities.
What these studies don't tell you?

1) utilizes small sample sizes, findings are not generalizable to the population at large.
2) inhibits an ability to make definitive conclusions about the findings.
3) flexible but often unstructured, leading to only tentative results that have limited value in decision-making.
4) Design lacks standards applied to methods of data gathering and analysis (one areas for exploration could be to determine what method or methodologies best fit problem

Front 12

Historical Design

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(collect, verify, and synthesize evidence from the past to establish facts that defend or refute your hypothesis)

WHAT TELL YOU

1) unobtrusive; not affect the results of the study.
2) well suited for trend analysis.
3) records can add important contextual background ,understand and interpret a research problem.
4) no possibility of researcher-subject interaction that could affect the findings.
5) sources can be used over and over to study different research problems or to replicate a previous study.

What these studies don't tell you?

1) fulfill the aims of your research directly related to amount & quality of documentation available to understand the research problem.
2) no way to manipulate it to control for contemporary contexts.
3) time consuming, sources must be archived consistentally to ensure access.
4) own perspectives and biases to past events (Biases difficult to ascertain)
5) lack of control over external variables, weak with regard to the demands of internal validity.
6) rare that entirety of documentation needed is available for interpretation, therefore, gaps need to be

Front 13

Longitudinal Design

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(follows the same sample over time and makes repeated observations)

What do these studies tell you?

1) allow the analysis of duration of a particular phenomenon.
2) Enables survey get causal explanations usually attainable only with experiments.
3) permits the measurement of differences /change in a variable from one period to another [i.e., the description of patterns of change over time].
4) facilitate the prediction of future outcomes based upon earlier factors.

What these studies don't tell you?

1) The data collection method may change over time.
2) Maintaining original sample difficult over an extended period of time.
3) difficult to show more than one variable at a time.
4) needs qualitative research to explain fluctuations in the data.
5) assumes present trends will continue unchanged.
6) It can take a long period of time to gather results.
7) There is a need to have a large sample size and accurate sampling to reach representativness.

Front 14

Observational Design

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( draws a conclusion by comparing subjects against a control group, in cases where the researcher has no control over the experiment)

WHAT DO TELL YOU

1) Flexible,not need to be structured around hypothesis about what you expect to observe (data is emergent rather than pre-existing).
2) collect a depth of information about a particular behavior.
3) reveal interrelationships among multifaceted dimensions of group interactions.
4) generalize your results to real life situations.
5) discovering what variables may be important before applying other methods like experiments.
6) account for the complexity of group behaviors.

What these studies don't tell you?

1) Reliability low ,seeing behaviors occur over and over again may be a time consuming task and difficult to replicate.
2) findings only unique sample population ,can't be generalized to other groups.
3) problems with bias , researcher may only "see what they want to see."
4) no possiblility to determine "cause and effect" relationships ,nothing is manipulated.
5) Sources or subjects may not all be equally credible.
6) Any group studied =altered( presence of the researcher,) skewing to some degree any data collected (the Heisenburg Uncertainty Principle).

Front 15

Philosophical Design

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(broad approach to examining a research problem than a methodological design, philosophical analysis and argumentation is intended to challenge deeply embedded, often intractable, assumptions underpinning an area of study)

x Ontology -- the study that describes the nature of reality; for example, what is real and what is not, what is fundamental and what is derivative?
x Epistemology -- the study that explores the nature of knowledge; for example, on what does knowledge and understanding depend upon and how can we be certain of what we know?
x Axiology -- the study of values; for example, what values does an individual or group hold and why? How are values related to interest, desire, will, experience, and means-to-end? And, what is the difference between a matter of fact and a matter of value?

WHAT TELL YOU

1) provide basis applying ethical decision-making to practice.
2) means of gaining greater self-understanding and self-knowledge about the purposes of research.
3) clarity to general guiding practices and principles of an individual or group.
4) informs methodology.
5) Refine concepts invoked in unreflectivethought and discourse.
6) informs critical thinking about epistemology and the structure of reality (metaphysics).
7) clarity and definition to practical and theoretical uses of terms, concepts, and ideas.

What these studies don't tell you?

1) Limited application to specific research problems [answering the "So What?" question in social science research].
2) Analysis abstract, argumentative, and limited in its practical application to real-life issues.
3) writing can be dense and subject to unnecessary jargon, overstatement, and/or excessive quotation and documentation.
4) limitations use of metaphor as a vehicle of philosophical analysis.
5) analytical difficulties (philosophy to advocacy/ abstract thought and application to the phenomenal world.)

Front 16

Sequential Design

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(carried out in a deliberate, staged approach [i.e. serially] where one stage will be completed, followed by another, then another, and so on, with the aim that each stage will build upon the previous one until enough data is gathered over an interval of time to test your hypothesis)

WHAT TELL YOU

What do these studies tell you?

1) Limitless option when it comes to sample size and the sampling schedule.
2) minor changes and adjustments during the initial to correct and hone the research method. Useful design for exploratory studies.
3) little effort, not expensive, time consuming, or workforce extensive.
4) conducted serially, the results 1 sample known b4 next sample is taken and analyzed.

What these studies don't tell you?

1) not representative of the entire population. only possibility of representativeness when researcher use large sample size (represent a significant portion of the entire population) (moving on to study a second or more sample can be difficult.)
2) not randomized, design cannot be used create conclusions and interpretations of entire population. (Generalizability limited.)
3) Difficult to account for and interpret variation from one sample to another over time, particularly when using qualitative methods of data collection.

Front 17

TYPE 1 ERROR

Back 17

-Rejecting the NULL hypothesis when it is TRUE

α (alpha) (significance level) : people decide, before hypothesis test, on max p-value reject null hypothesis.
x This value is often denoted and is also called the significance level.


- Statistically Significant: hypothesis test results in a p-value<than the significance level

-Common mistake: Confusing statistical significance and practical significance.

-The larger the sample size, the more likely a hypothesis test will detect a small difference. Thus it is especially important to consider practical significance when sample size is large.

The significance level α is the probability of making the wrong decision when the null hypothesis is true.

Front 18

Pros and Cons of Setting a Significance Level

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x Setting a significance level (before doing inference) has the advantage that the analyst is not tempted to chose a cut-off on the basis of what he or she hopes is true.
x It has the disadvantage that it neglects that some p-values might best be considered borderline. This is one reason2 why it is important to report p-values when reporting results of hypothesis tests. It is also good practice to include confidence intervals corresponding to the hypothesis test. (For example, if a hypothesis test for the difference of two means is performed, also give a confidence interval for the difference of those means. If the significance level for the hypothesis test is .05, then use confidence level 95% for the confidence interval.)

Front 19

TYPE 2 ERROR

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-NOT rejecting the null hypothesis when alternate hypothesis TRUE

Example: In a t-test for a sample mean µ, with null hypothesis ""µ = 0" and alternate hypothesis "µ > 0", we may talk about the Type II error relative to the general alternate hypothesis "µ > 0", or may talk about the Type II error relative to the specific alternate hypothesis "µ > 1". Note that the specific alternate hypothesis is a special case of the general alternate hypothesis.

- β is the probability of making the wrong decision when the specific alternate hypothesis is true.