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Research & Program Evaluation
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- 1to systemically investigate an experience either to understand what causes it, or to develop a theory about how that experience can cause a future eventresearch
- 2focuses on a specific theory and then establishes a hypothesis to methodically test the theory in order to support or discredit it. Often involves setting up experiments, trials, or data collection surveys to collect information related to the theoryDeductive Research
- 3examines info that's already available (such as US census Report) to highlight data trends and make inferences and/or projections from those patternsInductive research
- 4Non-Experimental Qualitative research that analyzes the strength of the relationship between 2 variables in one groupCorrelational designs
- 5correlational design where the researcher examines 2 existing groups and analyzes the correlation between the variables of interestex post facto studies
- 6correlational design where the researcher determines a correlation between variables and then uses it to predict other correlations, related events, or future eventsprediction studies
- 7a value between -1.0 and 1.0 that illustrates that strength of a relationship or interaction between two variables, with zero indicating no relationshipcorrelation coefficient
- 8These non-experimental qualitative designs examine data trends to determine a relationship in two groups or datasets that have already been establishedComparative designs
- 9Qualitative research with detailed and documented examples of the topic of interest. Often record data over a period of time to examine specific variable of interest. Frequently look at how people related to one another, and/or their physical or emotional environmentCase Studies
- 10Qualitative research that bring together a relatively small group of people. A facilitator guides a discussion within the group to discern info about individual or collective viewpoints about a specific issueFocus Groups
- 11Qualitative research that are more personal in nature. The interviewer asks the individual or group a series of meaningful questions related to the research topic. Can be structured or unstructuredInterviews
- 12Qualitative research where the researcher simply watches the individual or group of interest,Observation
- 13research that employs highly controlled processes with the hope of determining a causal relationship between one or more input (independent variables) and one or more outcome (dependent variables). Uses random sampling and assignment methods to make inferences for larger populations. Compares a control group (serving as a baseline) to a test group. These experiments should be able to be replicated numerous times with the same resultsExperimental quantitative research
- 14Research that often doesn't use random sampling or assignment in its studies or experiments. This research produces results that often don't apply to the population at large. The do, however, often provide meaningful results for certain subgroups of the populationQuasi-experimental quantitative research
- 15Illustrates how well inferences from a sample set can predict similar inferences in a larger pop. (i.e. can results in a controlled lab setting hold true when replicated in the real world). A researcher wants to generalize in 3 areas: population, environment, timeexternal validity
- 16Illustrates the integrity of results obtained from a sample set and indicates how reliably a specific study was conducted. Strong _____ allows researcher to confidently link a specific variable to results or outcomes of study. The strength of this study can be weakened by presences of many independent variables, where it's difficult to pinpoint what exactly is causing changes in dependent variables which is also called CONFOUNDINGInternal validity
- 17the method of collecting participants for a studysampling
- 18For this type of probability sampling, the participants are taken directly from a larger pop. with the characteristic of interest. Pros: closely represents target pop. Cons: obtaining sample can be time consuming. Use When: a highly controlled experiment setting is necessarySimple Random Sampling
- 19For this type of probability sampling, the researchers first examine the traits of the larger pop., which are often demographics like age, education, marital status, & household income. They then divide the pop. into groups (or strata) based on these traits.Stratified Random Sampling
- 20For this type of probability sampling, researchers pick a random integer (n), and then select every nth person from the target pop. Pros: simple, cost effective. Use when: researchers are on short time and need quick, cost effective method to create a random sampleSystematic Random Sampling
- 21This type of non-probability sampling where researcher select participants who are easily accessible due to factors like location, expense, or volunteer recruitment. Pros: saves time and is cost effective. Cons: highly prone to bias: Use When: researchers are simply looking for basic info about the larger pop.Convenience Sampling
- 22For this type of non-probability sampling, researchers must meet a set quota for a certain characteristic and can recruit any participant as long as they have the desired characteristic. Pros: allows for greater inclusion of a pop. that might not otherwise be represented. Cons: results won't be indicative of the actual pop. in an area. Use When: it's necessary that a group within the larger pop. needs a set level of representation within the studyAd Hoc Sample
- 23Non-probability sampling method used when researchers have a precise purpose or target pop. in mind. Pros: helps increase recruitment numbers in otherwise hard to access pops. Cons: usually unable to generalize the results to larger pops. Use When: researchers have a precise purpose for the study or specific group of participants that isn't easy to select through probability sampling methodsPurposive Sampling
- 24This measurement describes variables that are categories (gender, dominant hand, height)Nominal
- 25This measurement describes variable that can be ranked ( Likert scales, 1 to 10 rating scales)Ordinal
- 26This measurement describes variables that use equally spaced intervals (number of minutes, temperature)Interval
- 27This measurement describes anything that have a true "zero" point available (angles, dollars, cents)Ratio
- 28controlled by the researcher and usually influences the dependent variable (the factor that's typically measured and recorded by researcher)independent variable
- 29Declares there is no relationship between two variablesnull hypothesis
- 30Error that occurs when the researcher rejects the null hypothesis. Indicates that a relationship between two variables exists, when in reality, it doesn't.Type I error
- 31Error that occurs when the researcher fails to reject the null hypothesis when it's actually false. Indicates that a relationship between two variables doesn't exist, when in fact, it does.Type II Error
- 32a statistical testing method used to determine the probability that, when comparing two separate sample sets with different means, the difference in the means is statistically significant.T-test
- 33a form of hypothesis that declares a specific relationship between two variables, or simply states that the null hypothesis is rejectedAlternative hypothesis
- 34Tests that can analyze differences in sample sets where there are multiple dependent and independent variables. This test is the most efficient and most accurate way to test for statistically significant differences between three or more sample sets. These tests work by creating ratios of variance between and within the sample sets to determine whether the differences are statistically significantANOVA Tests
- 35This analysis is used to control for potential confounding variablesANCOVA
- 36a test that analyzes data between independent groups. Focus on variables that have categorical data rather than numerical dataChi-square test
- 37a basic form of analysis used when the value of an independent variable is known to predict an exact value for the dependent variable. This is most commonly illustrated by an XY plot graphBivariate Tabular Analysis
- 38usually performed after running other tests (t-test or ANOVA) where it's been determined that statistically significant differences exist between 2 or more sample sets. Researcher pick and choose specific groups to analyze similarities or differences. Some common tests are: Least Significant Different test, Tukey's Test, and confidence interval tests. Are complex and time consuming so must be performed with sophisticated statistical softwarePost hoc tests
- 39tests that are typically used when datasets don't have pre-set parameters, are skewed in distribution, include outliers, or are unconventional in some other way. Are less likely to be valid in showing strong relationships, similarities, or when differences between groups exist. Some tests are: Mood's Median Test, the Kruskal-Wallis test, and Mann-Whitney test. Easier to make a type I error with this test.Nonparametric tests
- 40an effect that occurs in an experiment or study due to the presence of an extra variable that can influence or correlate with the established independent or dependent variablesconfounding
- 41in an experiment or study, this group mirrors the qualities of the test group as much as possible, but does not receive the test or intervention in order to serve as a comparisoncontrol group
- 42the relationship or degree of interaction between two variablescorrelation
- 43the variable that changes due to manipulation of the independent variabledependent variable
- 44based on observation, experience, and/or experimentationempirical
- 45the central value of a data distributionmean
- 46sampling method that doesn't choose sample sets at randomnon-probability sampling
- 47sampling method that choices sample sets at random; generally more likely to represent the target pop.probability sampling
- 48focusing on the qualities and/or descriptors of a phenomenonqualitative
- 49focusing on the numerical, mathematical, statistical, or otherwise quantifiable aspects of a phenomenonquantitative
- 50a statistical technique to determine interactions and relationships between variables, usually to make predictionsregression analysis
- 51the probability of a relationship, result, or event occurring due to something other than chancestatistically significant
- 52a widely accepted principle or set of ideas that explain an event or eventtheory
- 53a factor that can be changedvariable
- 54One fundamental difference between probability sampling and non-probability sample is that probability sampling uses _______ while non-probability sampling does not.randomization
- 55ERIC stands for?Education Resources Information Center
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- Fichas sobre Research & Program Evaluation, creado por Natalie Schneider el 09/05/2022.
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- Natalie Schneider
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