How to Run Shapiro Wilk and Kolmogorov Smirnov Tests of Normality in SPSS - Explained Step by Step

HOW TO RUN SHAPIRO WILK AND KOLMOGOROV SMIRNOV TESTS IN SPSS? What are the Shapiro-Wilk and Kolmogorov-Smirnov tests of normality? The prerequisite for most of the statistical test is normal data distribution. We use tests of normality to asses whether data are normally distributed or not. If the data are normally distributed, we use parametric tests. If data are not normally distributed, we use nonparametric tests. We can also use plots to assess data distribution. We use the Shapiro-Wilk test when we have a small sample size (N smaller than 50) and Kolmogorov-Smirnov test when we have a large sample size (N greater than 50). Null hypothesis: Data are normally distributed. Alternative hypothesis: Data are not normally distributed. We collected data from 32 workers about their age and height in centimetres. To examine whether data for age and height are normally distributed, we used tests of normality. ► ARE YOU IN TROUBLE WITH THE SHAPIRO WILK AND KOLMOGOROV SMIRNOV TESTS? Send us your Project or Homework or Assignment or Thesis and Get quick help! https://www.onlinespss.com/submit-you... ► DO YOU NEED MORE INFORMATION ABOUT SHAPIRO WILK AND KOLMOGOROV SMIRNOV TESTS? Please click the link for more details about SHAPIRO WILK AND KOLMOGOROV SMIRNOV TESTS http://www.onlinespss.com/ ►For more Statistic follow us on social media • Website: https://onlinespss.com/ • Facebook: https://facebook.com/onlinespss • Instagram: https://www.instagram.com/onlinespss • Twitter: https://twitter.com/onlinespss • E-mail: [email protected] ► About OnlineSPSS.com! The tutors at OnlineSPSS.com are professors and scholars with high qualifications in various fields, with decades of experience in teaching. Our Assignment Experts have helped over 7,000 students over the past years achieve academic success and here, they like to pass on to you the tips & tricks on assignment writing that they have learned over many years in the industry. Keep watching, and please don't forget to post your comments!

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