inta 295 final

population

all the cases or observation covered by a hypothesis; all units of analysis to which a hypothesis applies

sample

a subset of observations or cases drawn from a specific population

sample bias

the bias that occurs whenever some elements of a population are systematically excluded from a sample. It is usually due to an incomplete sampling frame or a nonprobability method of selecting elements

element

particular case or entity about which information is collected; unit of analysis

estimator

a statistic based on sample observations that is used to estimate the numerical value of unknown population paramete

expected value

the mean or average value of a sample statistic based on repeated samples from a populaion

population parameter

a characteristic or attribute in a population that can be quantified (NOT A SAMPLE)

sample statistic

the estimator of a population characteristic or attribute that is calculated from sample data

sampling distribution

A theoretical distribution of sample statistics calculated on samples of size N that, if known, permits the calculation of confidence intervals and the test of statistical hypotheses ;l nonobserved

__**Sampling Frame**__

The population from which a sample is drawn. Ideally, it is the same as the total population of interest to a study.

__**Sampling Unit**__

The entity listed in a sampling frame. It may be the same as an element, or it may be a group or cluster of elements.

__**Probability Samples**__

a sample for which each element in the total population has a known probability of being selected

**Simple Random Samples**

A probability sample in which each element has an equal chance of being selected.

**Systematic Samples**

A probability sample in which elements are selected from a list at predetermined intervals.

**Stratified Samples**

A probability sample in which elements sharing one or more characteristics are grouped and elements are selected from each group in proportion to the group’s representation in the total population

**Proportionate**

a probability sample that draws elements from a stratified population at a rate proportional to the size of the samples

**Disproportionate**

A stratified sample in which elements sharing a characteristic are underrepresented or overrepresented in the sample.

**Cluster Samples**

A probability sample that is used when no list of elements exists. The sampling frame initially consists of clusters of elements.

__**Nonprobability Samples**__

A sample for which each element in the total population has an unknown probability of being selected.

**Purposive Samples**

a nonprobability sample in which a researcher uses discretion in selecting elements for observation

**Convenience Samples**

A nonprobability sample in which the selection of elements is determined by the researcher’s convenience.

**Quota Samples**

A nonprobability sample in which elements are sampled in proportion to their representation in the population.

**Snowball Samples**

A nonprobability sample in which potential respondents are identified by respondents already participating in the sample.

__**Informed Consent:**__

Procedures that inform potential research subjects about the proposed research in which they are being asked to participate; the principle that researchers must obtain the freely given consent of human subjects before they participate in a research project.

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important so participants are aware of the full extent of an experiment and can leave when they please

__**Institutional Review Board**__

**Panel to which researchers must submit descriptions of proposed research involving human subjects for the purpose of ethics review.**

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cost benefit analysis; upholds ethics of experiments

**Pre-Experiement**

*  **informed consent**
* **Subjects are made aware of procedures and any risk**

pre - experiment tradeoffs

results may be compromised

**During Experiment**

**subjects can withdraw at ANY time**

**Post-Experiment**

 full debriefing

**Plagiarism**

**not giving credit where its due (e.g. stealing someone’s work without given them credit)**

**Fraud**

wasting grant money, falsifying data

Breuning Case

Research funded by NIMH

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Published studies on psychoactive drugs on mentally slow patients 

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His findings affected treatment practices; only a few experimental subjects are actually studied

Tuskegee Syphilis Study

Subjects were not informed of purpose/risks 

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In order to track the disease's full progression, researchers provided no effective care as the study's African American participants experienced severe health problems including blindness, mental impairment—or death.

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intent of the study was to record the natural history of syphilis in Black people

Stanford Prison Experiment

a two-week simulation of a prison environment that examined the effects of situational variables on participants' reactions and behaviors.

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psychological abuse of the prisoners by the "guards" became increasingly brutal.

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Prisoners were kept in unsafe, unsanitary, and dehumanizing facilities. Several of them told guards they wanted to leave, but they were refused. The three men who were removed from the study were only allowed to when researchers thought they were too traumatized to safely continue.

Milgram Obedience

Psychological damage 

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Social psychologist Stanley Milgram researched the effect of authority on obedience. He concluded people obey either out of fear or out of a desire to appear cooperative

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the people who were the participants were led to believe that they were administering a shock to real people. The individuals were unaware the learners were individuals associated with Milligram.

**Direct Observation**

Actual observation of behavior.

**Indirect Observation**

Observation of physical traces of behavior.

**Covert Observation**

**Observation in which the observer’s presence or purpose is kept secret from those being observed.**

**Overt Observation**

**Observation in which those being observed are informed of the observer’s presence and purpose.**

**Structured Observation**

**Systematic observation and recording of the incidence of specific behaviors.**

**Unstructured Observation**

Observation in which all behavior and activities are recorded.

**Participant Observation**

**observation in which the observer becomes a regular participant in the activities of those being observed**

**The Episodic Record (written material)**

the portion of the written record that is not part of a regular, ongoing record-keeping enterprise

**The Running Record**

the portion of the written record that is enduring and covers an extensive period of time

advantages of running record

Cost

Accessibility

Extensive time period covered

disadvantages of running record

Data collection procedures determined by others

These procedures may not be explicit/reliable/consistent

Raw data often not available (only summaries)

advantages of written record

* Allows access to distant subjects
* Raw data are USUALLY nonreactive
* May allow analysis over time
* Allows larger sample sizes
* Cost borne by record-keepers

Disadvantages of written record

* Selective survival of data
* Content may be biased
* Some key material unavailable
* May lack standard format

__**Content Analysis**__

**a procedure by which verbal, nonquantitative records are transformed into quantitative data**

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EX: coding President Biden’s inaugural speech for self confidence

**Nonprobability Samples**

Purposive Samples

Convenience Samples

Quota Samples

Snowball Samples

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want to avoid

__**Reliability**__

the *consistency* of results from a procedure or measure in repeated tests or trials

**Intercoder Reliability**

between researcher reliability, multiple researchers come of the same results, are the results consistently reliable (have the same results)

**Reliability Over Time**

Is the measure consistent overtime

__**Validity**__

refers to the degree of correspondence between the measure and the concept it is thought to measure

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are you measuring what you think you're measuring?

**Face Validity**

when a measure appears to accurately measure the concept it is supposed to measure.

may only be asserted, rather than empirically demonstrated, because face validity is *essentially a matter of judgement*

**Content Validity**

involves determining the full domain or meaning of a particular concept and then making sure that all components of the meaning are included in the measure

*an overall improvement as opposed to face validity, but ultimately, it's still a matter of judgement*

__**Construct Validity**__

validity demonstrated for a measure by showing that it is related to the measure of another concept

**Convergent Construct Validity**

when a measure of a concept is related to a measure of another concept with which the original concept is thought to be associated

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Refers to how closely the new scale is related to other variables and other measures of the same construct. Not only should the construct correlate w/ related variables, but it should not correlate w/ dissimilar, unrelated ones

**Discriminants Construct Validity**

two measures that theoretically are expected *not* to be related, and so the correlation between them is expected to be low/weak

*if the measurements do no correlate with one another, then DCV is demonstrated*

**Open-ended Questions**

**A question with no response alternatives provided for the respondent.**

**Close-ended Question**

A question with response alternatives provided.

**Double-barreled Questions**

A question that is really two questions in one.

**Leading Question**

A question that encourages the respondent to choose a particular response.

**Question Order Effect**

**The effect on responses of question placement within a questionnaire.**

**Response Set**

The pattern of responding to a series of questions in a similar fashion without careful reading of each question.

**Single-sided Questions**

A question in which the respondent is asked to agree or disagree with a single substantive statement

**Double-sided Questions**

A question that is really two questions in one.

__**Central tendency**__

The most frequent, middle, or central value in a frequency distribution.

__**Dispersion**__

The distribution of data values around the most frequent, middle, or central value.

__**Normal Distribution**__

A distribution defined by a mathematical formula and the graph of which has a symmetrical bell shape in which the mean, the mode, and the median coincide, and in which a fixed proportion of observations lies between the mean and any distance from the mean measured in terms of the standard deviation.

__**Positively Skewed Distributions:**__

A distribution of values in which fewer observations lie to the right of the middle value and those observations are fairly distant from the mean.

__**Negatively Skewed Distributions**__

A distribution of values in which fewer observations lie to the left of the middle value and those observations are fairly distant from the mean

__**Z-Score**__

The number of standard deviations by which a score deviates from the mean score.

__**Dichotomous Variable**__

A variable with only two categories—these variables are special cases as they can be used at the nominal, ordinal, or even ratio level.

__**Descriptive Statistic**__

A number that, because of its definition and formula, describes certain characteristics or properties of a batch of numbers.

__**Standard Error**__

a measure of the statistical accuracy of an estimate, equal to the standard deviation of the theoretical distribution of a large population of such estimates.

__**Central Tendency**__

what is a typical value of this variable?

__**Dispersion**__

how are the values of this variable dispersed/distributed?

nominal

 (categories, no clear/given order)

Ordinal

(there is a clear order)

Interval

range, no true 0

Ratio

range, true 0

descriptive NOMINAL

Central tendency: __Mode:__ the most common valuable for the variable

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dispersion: Proportion of observed values in modal category

descriptive ORDINAL

Central tendency:

__Median:__ the middle value

__Range:__ difference between lowest and highest values (full spread of numbers)

__Interquartile Range:__ the range (spread) for the middle 50% of the values

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dispersion:

Range

Interquartile Range (IQR)

descriptive INTERVAL/RATIO

Central tendency:

__Mean:__ the average of a set of numbers (add up all the values and divide by the total number of cases)

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dispersion:

Mean Deviation

Standard Deviation

Variance

standard deviation ^2=

variance

example of sample variance

* Four Party ID Scores: 1, 2, 2, 3
* Find Mean
* Subtract Mean from each data point, and square those deviations
* Make sure they're positive
* Add all the squared deviations together
* Divide by (n - 1) to get the sample Variance
* Take the square root to get the sample Standard Deviation

__**5 Key Questions For Examining Bivaraite Relationships:**__

existence

strength

strength

statistical significance

causality

existence

 is there is a relationship between these two variables?

**Direction**

what is the *shape* of this relationship?

**Strength**

how many values of the DV are explained by the values of the IV?

**Statistical Significance**

is this observed relationship due to chance?

**Causality**

is the IV *causing* variation in the DV?

__**Types of Relationships**__

positive

negative

positive

* A relationship in which the values of one variable increase (or decrease) as the values of another variable increase (or decrease).
* move in the SAME direction ↑↑ or ↓↓

**Negative Relationship**

*  A relationship in which high values of one variable are associated with low values of another variable or in which low values of one variable are associated with high values of another variable.
* move in the OPPOSITE direction ↑↓ or ↓↑

**Statisitical Significance (p)**

* **the probability of your findings occuring if the null hypothesis is true (*****0.05 or less*** **is the goal (aka 95% confidence))**
* **Can be affected by the strength of relationship and the number of observations**

**Substantive Significance**

x

__**what is appropriate procedures if IV and DV are nominal/ordinal**__

Contingency Tables (Crosstabs)

__**what is appropriate procedures if IV nominal/ordinal and DV interval/ratio**__

ANOVA (Difference of Means Tests)