Excel Skills for Business by Macquarie University.Introduction to Psychology by Yale University.Business Foundations by University of Pennsylvania.IBM Data Science Professional Certificate by IBM.Python for Everybody by University of Michigan.
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Google IT Support Professional by Google.The Science of Well-Being by Yale University.AWS Fundamentals by Amazon Web Services.Epidemiology in Public Health Practice by Johns Hopkins University.Google IT Automation with Python by Google.Specialization: Genomic Data Science by Johns Hopkins University.Specialization: Software Development in R by Johns Hopkins University.Specialization: Statistics with R by Duke University.Specialization: Master Machine Learning Fundamentals by University of Washington.Courses: Build Skills for a Top Job in any Industry by Coursera.Specialization: Python for Everybody by University of Michigan.Specialization: Data Science by Johns Hopkins University.Course: Machine Learning: Master the Fundamentals by Standford.Q-Q plot draws the correlation between a given sample and the normal distribution.Ĭoursera - Online Courses and Specialization Data science Visual inspection of the data normality using Q-Q plots (quantile-quantile plots).In other words, we can assume the normality. Shapiro.test(my_data$mpg) # => p = 0.1229įrom the output, the two p-values are greater than the significance level 0.05 implying that the distribution of the data are not significantly different from normal distribution. Alternative hypothesis: the data are not normally distributed.Null hypothesis: the data are normally distributed.Shapiro-Wilk test can be performed as follow:.and look at the normality plot -> R function: ggpubr::ggqqplot().
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Preleminary test to check the test assumptions