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  2. Misuse of statistics - Wikipedia

    en.wikipedia.org/wiki/Misuse_of_statistics

    Statistics, when used in a misleading fashion, can trick the casual observer into believing something other than what the data shows. That is, a misuse of statistics occurs when a statistical argument asserts a falsehood. In some cases, the misuse may be accidental. In others, it is purposeful and for the gain of the perpetrator.

  3. Data dredging - Wikipedia

    en.wikipedia.org/wiki/Data_dredging

    Optional stopping is a practice where one collects data until some stopping criteria is reached. While it is a valid procedure, it is easily misused. The problem is that p-value of an optionally stopped statistical test is larger than what it seems.

  4. Multiple comparisons problem - Wikipedia

    en.wikipedia.org/wiki/Multiple_comparisons_problem

    Multiple comparisons arise when a statistical analysis involves multiple simultaneous statistical tests, each of which has a potential to produce a "discovery". A stated confidence level generally applies only to each test considered individually, but often it is desirable to have a confidence level for the whole family of simultaneous tests. [4]

  5. Statistical literacy - Wikipedia

    en.wikipedia.org/wiki/Statistical_literacy

    Statistical literacy is the ability to understand and reason with statistics and data. The abilities to understand and reason with data, or arguments that use data, are necessary for citizens to understand material presented in publications such as newspapers , television , and the Internet .

  6. Sample size determination - Wikipedia

    en.wikipedia.org/wiki/Sample_size_determination

    In practice, the sample size used in a study is usually determined based on the cost, time, or convenience of collecting the data, and the need for it to offer sufficient statistical power. In complex studies, different sample sizes may be allocated, such as in stratified surveys or experimental designs with multiple treatment groups.

  7. Design of experiments - Wikipedia

    en.wikipedia.org/wiki/Design_of_experiments

    Investigators should ensure that uncontrolled influences (e.g., source credibility perception) do not skew the findings of the study. A manipulation check is one example of a control check. Manipulation checks allow investigators to isolate the chief variables to strengthen support that these variables are operating as planned.

  8. Statistics education - Wikipedia

    en.wikipedia.org/wiki/Statistics_education

    Statistics educators have cognitive and noncognitive goals for students. For example, former American Statistical Association (ASA) President Katherine Wallman defined statistical literacy as including the cognitive abilities of understanding and critically evaluating statistical results as well as appreciating the contributions statistical thinking can make.

  9. Distributed practice - Wikipedia

    en.wikipedia.org/wiki/Distributed_Practice

    The opposite, massed practice, consists of fewer, longer training sessions and is generally a less effective method of learning. For example, when studying for an exam, dispersing your studying more frequently over a larger period of time will result in more effective learning than intense study the night before. [citation needed]