Methods for choosing the appropriate statistical analysis for data in scientific research

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الدكتور بشار عبد العزيز الطالب

Published on Feb 18, 2021
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This lecture is a roadmap for researchers who want to analyze their data statistically and do not have sufficient experience in how to know what fits their data or assumptions from analyses or how to conduct the sampling. The lecture included the following paragraphs: 1- Descriptive statistics and inferential statistics 2- Parametric statistics and non-parametric statistics 3- Levels of measuring variables 4- Choosing the appropriate statistics according to the type of scale 5- Appropriate cases for using some graphs 6- Classification of correlation coefficients according to the type of variable 7- The most common parametric and non-parametric correlation coefficients 8- Random and non-random sampling 9- The appropriate statistical test according to the number of samples, hypothesis, type of data, and its independence or correlation 10- Parametric and non-parametric tests 11- Specifications of cases of applying parametric and non-parametric measures 12- Tests related to nominal data 13- Tests related to ordinal data 14- Tests related to measured data 15- How to optimally choose the proportions of sample units according to the degree of homogeneity of the community units and the required accuracy 16- General ideas about analyzing questionnaire data 17- Requirements of the era of big data

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