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  2. Internal validity - Wikipedia

    en.wikipedia.org/wiki/Internal_validity

    During the selection step of the research study, if an unequal number of test subjects have similar subject-related variables there is a threat to the internal validity. For example, a researcher created two test groups, the experimental and the control groups.

  3. Quasi-experiment - Wikipedia

    en.wikipedia.org/wiki/Quasi-experiment

    The lack of random assignment in the quasi-experimental design method may allow studies to be more feasible, but this also poses many challenges for the investigator in terms of internal validity. This deficiency in randomization makes it harder to rule out confounding variables and introduces new threats to internal validity. [11]

  4. Validity (statistics) - Wikipedia

    en.wikipedia.org/wiki/Validity_(statistics)

    In other words, the relevance of external and internal validity to a research study depends on the goals of the study. Furthermore, conflating research goals with validity concerns can lead to the mutual-internal-validity problem, where theories are able to explain only phenomena in artificial laboratory settings but not the real world. [13] [14]

  5. Confounding - Wikipedia

    en.wikipedia.org/wiki/Confounding

    The major threats to internal validity are history, maturation, testing, instrumentation, statistical regression, selection, experimental mortality, and selection-history interactions. One way to minimize the influence of artifacts is to use a pretest-posttest control group design.

  6. Selection bias - Wikipedia

    en.wikipedia.org/wiki/Selection_bias

    A distinction of sampling bias (albeit not a universally accepted one) is that it undermines the external validity of a test (the ability of its results to be generalized to the rest of the population), while selection bias mainly addresses internal validity for differences or similarities found in the sample at hand. In this sense, errors ...

  7. Statistical conclusion validity - Wikipedia

    en.wikipedia.org/.../Statistical_conclusion_validity

    Statistical conclusion validity is the degree to which conclusions about the relationship among variables based on the data are correct or "reasonable". This began as being solely about whether the statistical conclusion about the relationship of the variables was correct, but now there is a movement towards moving to "reasonable" conclusions that use: quantitative, statistical, and ...

  8. Wall Street falls following Trump's tariffs, but not as badly ...

    www.aol.com/stock-market-today-asian-shares...

    The threat of a punishing trade war sent Wall Street on a roller coaster Monday. After initially falling sharply on worries about President Donald Trump’s tariffs, U.S. stocks pared their losses ...

  9. External validity - Wikipedia

    en.wikipedia.org/wiki/External_validity

    In many studies and research designs, there may be a trade-off between internal validity and external validity: [16] [17] [18] Attempts to increase internal validity may also limit the generalizability of the findings, and vice versa. This situation has led many researchers call for "ecologically valid" experiments.