Research in Practice terminology - Midterm (copy)

kill me.

empiricism

The use of verifiable evidence as the basis for conclusions; collecting data systematically and using it to develop, support, or challenge a theory. Also called empirical method, empirical research

quantitative method

A way of collecting empirical data in which information is converted to numbers for future statistical analysis.

qualitative method

A way of collecting empirical data that creates rich, in-depth descriptions of some phenomenon or group of people, often collected via interviews or extended observations.

reflexivity

A process in which researchers reflect on how their own values, biases, and experiences might shape the topics they study and the interpretations they make.

theory

A statement or set of statements that describes general principles about how variables relate to one another.

hypothesis

A statement of the specific result the researcher expects to observe from a particular study, if the theory is accurate. Also called prediction.

data (plural; singular datum)

A set of observations representing the values of some variable, collected from one or more research studies.

Census

A set of observations that contains all members of the population of interest.

biased sample

A sample in which some members of the population of interest are systematically left out and, therefore, the results cannot generalize to the population of interest.

unbiased sample

A sample in which all members of the population of interest are equally likely to be included (usually through some random method), and therefore the results can generalize to the population of interest.

convenience sampling

Choosing a sample based on those who are easiest to access and readily available; a biased sampling technique.

Self-selection (volunteer sample)

A form of sampling bias that occurs when a sample contains only people who volunteer to participate.

probability sampling

A category name for random sampling techniques, such as simple random sampling, stratified random sampling, and cluster sampling, in which a sample is drawn from a population of interest so each member has an equal and known chance of being included in the sample.

nonprobability sampling

A category name for nonrandom sampling techniques, such as convenience, purposive, and quota sampling, that result in a biased sample. See also biased sample, probability sampling.

simple random sampling

The most basic form of probability sampling, in which the sample is chosen completely at random from the population of interest (e.g., drawing names out of a hat).

systematic sampling

A probability sampling technique in which the researcher uses a randomly chosen number N, and counts off every Nth member of a population to achieve a sample.

cluster sampling

A probability sampling technique in which clusters of participants within the population of interest are selected at random, followed by data collection from all individuals in each cluster.

multistage sampling

A probability sampling technique involving at least two stages

stratified random sampling

A form of probability sampling; a random sampling technique in which the researcher identifies particular demographic categories, or strata, and then randomly selects individuals within each category.

Oversampling

A form of probability sampling; a variation of stratified random sampling in which the researcher intentionally overrepresents one or more groups.

purposive sampling

A biased sampling technique in which only certain kinds of people are included in a sample.

snowball sampling

A variation on purposive sampling, a biased sampling technique in which participants are asked to recommend acquaintances for the study.

quota sampling

A biased sampling technique in which a researcher identifies subsets of the population of interest, sets a target number for each category in the sample, and nonrandomly selects individuals within each category until the quotas are filled.

Properties of Scientific research

Empirical, Probabalistic, Verifyable  

Probabilistic

Findings do not explain all causes all the time but it explains what happens most of the time

Empirical

Based on Systematic observations

Verifiable:

Confirmable through the senses

Sources of Information & limitations

Experience, intuition, authorities

Intuition

Availability Heuristic, confirmation bias, Bias Blind Spot

Authorities

Which authority to consult

Experience

Comparison Group, alternative explanations

Ordinal Data

Nominal Data but there is a logical ranking (levels of education).

Interval Data

A continuous variable (where there are numbers). Furthermore, these do not have an absolute zero, even if the value is 0. AKA does not indicate an absence of this thing

Ratio Data

continuous variable but they have an absolute zero. Examples of ratio variable are height and weight. A height or weight of zero indicates that the object you are measuring does not have a height or a weight. In fact, negative weight or length cannot be measured.

Levels of Measurement

The measurement level of the variable(s) determines which statistical tools you can use

Categorical Variables

measured in groups/categories

Continuous Variables

Measured on a continuous scale

Absolute Frequency

the number of times you have observed that value. Also known as count.

Relative Frequency

the number of times you have observed a value, expressed as a percentage. In other words: relative to the total number of observations

Relative valid frequency

it happens that people taking a survey leave some of the questions blank. In that case, you can calculate the relative frequency compared to everyone you sent the survey to, or compared to those people that gave a valid answer

Falsifiable

It must be possible to disprove a theory based on gathered information

Parsimonious

If a simple theory suffices, it is not necessary to make it more complex

Properties of good scientific Theory

• Supported by data

• Falsifiable

• Parsimonious

Correlational Research

research that we study relationships between two or more characteristics of people - we start with the research questions- this is a direct result from the theory —> Identifiable from PAC

PAC

Population - Association - Concepts

Population

The group pf people the researcher wishes to study (includes both who are where)

association

The relationship

Concepts: Causality /cause and effect relationship

if when you discuss associations you realised that one characteristic causes a change in the other characteristic

Causality Conditions

• Covariance: there must be a type of relationship between the cause and effect before we can consider a casual relationship

• Temporal precedence

• internal validity: Alternative explanations for the relationship must be ruled out 

Temporal Precedence

The cause must precede the effect in time

Covariance

a scale-dependent measure of the relationship between two variables such that corresponding pairs of values of the variables are studied with regard to their relative distance from their respective means.

Concepts

the characteristics of the people that the researcher wishes to study and between which an association is expected (ex. aggression, intelligence, fun during first date, etc.)

Nominal Data

Data which consists of names, labels, or categories.

Variables

Is everything that is being measured, questioned or kept a record of in research. Can take on different values for different individuals, like age or gender.

Dataset

contains information about all participants and all variables. they looks like this: every row displays a participant. So the number of rows is equal to the number of participants in the research. Every column displays a variable. 

Frequency

How often values are observed

Mean

the mathematical average of a set of numbers, calculated by adding all the values together and dividing by the total count of numbers (formula: M=∑x/n)

Median

The middle point of the data. Can be convenient because it is less influenced by outliers.

Mode

The value that has been recurred the most

Spread

how much data values differ from each other, and for how much data values differ from the measure of centre

measure of centre

The point around which most of the data is concentrated

Mean Absolute Deviation (MAD)

Average absolute deviation from the mean/median of a dataset

Where:

• X = the value of a data point

• µ = mean

• |X – µ| = absolute deviation

• N = sample size

Measures of Spread

•   Range

• Mean absolute deviation (MAD)

• Variance

• Standard deviation 

Variance

mean squared deviation of the values with respect to the mean.

The variance is usually denoted by σ^2.

when the variance is high the spread is also high

Flaws of the variance

the unit of variance is different from the unit of the variable. he variance is denoted in squared minutes vs just minutes

Evidence based treatment

A psychotherapy technique whose effectiveness has been supported by empirical research

Organised Scepticism

One of Merton's four scientific norms states that scientists question everything, including their own theories, widely accepted ideas and 'ancient wisdom '

disinterestedness

One of Merton's four scientific norms states that scientists strive to discover the truth, whatever it is they are not swayed by conviction, idealism, politics, or profit

Communality

One of Merton's scientific norms stating that scientific knowledge is created by a community and its findings belong to the community

Universalism

One of Merton's four scientific norms states that scientific claims are evaluated according to their merit, independence of the researchers credentials or reputation

Journal

a monthly or quarterly period containing peer reviewed articles on a specific academic discipline or subdicipline written for a scholarly audience

Hypothesis

A statement of the specific result the researcher expects to observe from a particular study if the theory is accurate

preregistered

a term referring to a study in which before collecting any data, the researcher has stated publicly what the study outcome is going to be

replication

the process of conducting a study again to test whether the result is inconsistent

weight of the evidence

A conclusion drawn from reviewing scientific literature and considering the proportion of the studies that is consistent with the theory 

selfcorrecting

a process in which scientists make their research available for peer review, replication, and critique, with the goal of identifying and correcting errors in research.

applied research

research whose goal is to find a solution to a particular real world problems

basic research

research whose goal is to enhance the general body of knowledge without the regard for direct application to practical problems

comparison group

a group experiment whose levels on the independent variable differ from those of the treatment group in some intended and meaningful way

confound

a general term for a potential alternative explanation for a research finding a threat to internal validity

confederate

an actor who is directed by the researcher to play a specific role in a research study

probabilistic

describing the empirical method stating that science is intended to explain a certain proportion (but not necessarily all) of the possible cases

Lateral Reading

A critical reading technique in which, rather than reading deeper into a suspicious website, one checks its claims on alternative, legitimate news source

Click Restraint

A critical reading technique in which one deliberately pauses before accepting, sharing, or following an online link, especially when it provokes an emotional response.

Disinformation

A news story, photo, or video deliberately created to be false or misleading.

Open Access

Term referring to a peer-reviewed academic journal that anyone, even the general public, can read without paying for access.

paywalled

Term referring to a peer-reviewed academic journal that the general public must pay to access; only people who are members of subscribing institutions can access the content.

Effect Size

The magnitude, or strength, of a relationship between two or more variables.

meta-analysis

A way of mathematically averaging the effect sizes of all the studies that have tested the same variables to see what conclusion that whole body of evidence supports

review journal article

An article summarising all the studies that have been published in one research area.

Empirical Journal Article

A scholarly article that reports for the first time the results of a research study.

availability heuristic

a bias in intuition, in which people incorrectly estimate the frequency of something, relying predominantly on instances that easily come to mind rather than using all possible evidence in evaluating a conclusion

confirmation bias

the tendency to consider only the evidence that supports a hypothesis, including asking only the questions that will lead to the expected answer

bias blind spot

the tendency for people to think that compared to others they themselves are less likely to engage in biased reasoning

Coverage errors

non-participation or refusal to answer

outlier

when someone answers in a away deviant from others. Outliers cause

• The mean changes  

• The standard deviation increases 

• The median stays the same 

Scaling

When all values in the sample are multiplied or divided by a constant

Correlation coefficient (r)

Measures how closely the points resemble one straight line

• Value close to zero : weak linear relationship

• Close to -1 or +1 : strong linear relationship

• Exactly +- 1 : perfect linear relationship

Test-retest reliability

Answers the question:  “Are the measurements made with this instrument consistent when researchers use it multiple times?

Random error ( reliability)

affects measurements in different directions, cancelling out the errors in the long run.