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Psychological statistics is application of formulas, theorems, numbers and laws to psychology. Statistical methods for psychology include development and application statistical theory and methods for modeling psychological data. These methods include psychometrics, factor analysis, experimental designs, and Bayesian statistics. The article ...
Methods also vary by whether they collect qualitative data, quantitative data or both. Qualitative psychological research findings are not arrived at by statistical or other quantitative procedures. Quantitative psychological research findings result from mathematical modeling and statistical estimation or statistical inference. The two types ...
Advantages of this method include clearly defined and face valid questions for each measure. Measures are also more likely to apply across populations. Additionally, it requires less statistical methodology for initial development, and will often outperform other methods while requiring fewer items. [5]
The table shown on the right can be used in a two-sample t-test to estimate the sample sizes of an experimental group and a control group that are of equal size, that is, the total number of individuals in the trial is twice that of the number given, and the desired significance level is 0.05. [4]
Quantitative psychological research is psychological research that employs quantitative research methods. [ 1 ] Quantitative research falls under the category of empirical research .
Intelligence testing has long been an important branch of quantitative psychology. The nineteenth-century English statistician Francis Galton, a pioneer in psychometrics, was the first to create a standardized test of intelligence, and he was among the first to apply statistical methods to the study of human differences and their inheritance.
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Log-linear analysis is a technique used in statistics to examine the relationship between more than two categorical variables. The technique is used for both hypothesis testing and model building. In both these uses, models are tested to find the most parsimonious (i.e., least complex) model that best accounts for the variance in the observed ...