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All you need is an idea. We handle the rest.
All you need is an idea. We handle the rest.
This statistics course introduces the basics of data analysis. It starts with how to collect, organize, and interpret data, explaining the difference between a population and a sample, and the main sampling methods like stratified and convenience sampling. It then covers types of data — qualitative (nominal, ordinal) and quantitative (discrete, continuous) — and how to organize them using rules like Sturges’ formula for class intervals. The course explains measures of central tendency (mean, median, mode, and weighted mean) and measures of variability (range, variance, and standard deviation) to understand data spread. It also distinguishes sample and population formulas, using n−1 in sample variance for accuracy. Finally, it introduces skewness and kurtosis to describe the shape of data distributions. Overall, it provides a strong foundation for understanding and summarizing statistical data.
Tamer Elateeq
Data Management consultant
This statistics course introduces the basics of data analysis. It starts with how to collect, organize, and interpret data, explaining the difference between a population and a sample, and the main sampling methods like stratified and convenience sampling. It then covers types of data — qualitative (nominal, ordinal) and quantitative (discrete, continuous) — and how to organize them using rules like Sturges’ formula for class intervals. The course explains measures of central tendency (mean, median, mode, and weighted mean) and measures of variability (range, variance, and standard deviation) to understand data spread. It also distinguishes sample and population formulas, using n−1 in sample variance for accuracy. Finally, it introduces skewness and kurtosis to describe the shape of data distributions. Overall, it provides a strong foundation for understanding and summarizing statistical data.
Lessons
6
Duration
3 Hours
Skill Level
Entry level
Views
10