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Test of Normality of Data in SPSS
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In this video, I demonstrated how you can test whether your data is normally distributed or not using:
1. Shapiro-Wilk Test
2. Kolmogorov Smirnov Test
3. Histogram
4. Q-Q Plot
5. Skewness, and
6. Kurtosis
Your data is expected to be at least approximately normally distributed for your data to produce valid results for parametric tests, such as:
1. Pearson's Correlation
2. One Sample T-Test
3. Paired Sample T-Test
4. Analysis of Variance, and
5. Regression Analysis, among others.
So, to achieve these tests, the numerical and the graphical methods and approach were demonstrated and thereafter interpreted in great details for easy comprehension. The Skewness and Kurtosis as well as the Kolmogorov Smirnov test and the Shapiro-Wilk test constituted the numerical methods that were applied to test whether the data is approximately normally distributed or not. While on the other hand, the Histogram and the Q-Q plot were also engaged as the graphical methods. See the video to the end to learn about the "How".
From the two approaches, you can make a choice of the knowledge to utilize. All the individual methods spoken about are reliable, but you have the prerogative to use all simultaneously or use the one that is most suitable to you.
To see my videos on how to load data into SPSS, please use this links:
The following videos may also be of interest to you:
Other non-analytical videos you might be interested in include:
Please, note that I publish videos every Fortnight. If you have a particular topic, you would like me to discuss, please kindly inform me via the comment section and I will do my best to develop the video and publish it for the general interest.
Please, give this video a thumbs up and please SUBSCRIBE by clicking on the red SUBSCRIBE button above now.
Thanks for your SUBSCRIPTION and I look forward to seeing you again in my next video.
1. Shapiro-Wilk Test
2. Kolmogorov Smirnov Test
3. Histogram
4. Q-Q Plot
5. Skewness, and
6. Kurtosis
Your data is expected to be at least approximately normally distributed for your data to produce valid results for parametric tests, such as:
1. Pearson's Correlation
2. One Sample T-Test
3. Paired Sample T-Test
4. Analysis of Variance, and
5. Regression Analysis, among others.
So, to achieve these tests, the numerical and the graphical methods and approach were demonstrated and thereafter interpreted in great details for easy comprehension. The Skewness and Kurtosis as well as the Kolmogorov Smirnov test and the Shapiro-Wilk test constituted the numerical methods that were applied to test whether the data is approximately normally distributed or not. While on the other hand, the Histogram and the Q-Q plot were also engaged as the graphical methods. See the video to the end to learn about the "How".
From the two approaches, you can make a choice of the knowledge to utilize. All the individual methods spoken about are reliable, but you have the prerogative to use all simultaneously or use the one that is most suitable to you.
To see my videos on how to load data into SPSS, please use this links:
The following videos may also be of interest to you:
Other non-analytical videos you might be interested in include:
Please, note that I publish videos every Fortnight. If you have a particular topic, you would like me to discuss, please kindly inform me via the comment section and I will do my best to develop the video and publish it for the general interest.
Please, give this video a thumbs up and please SUBSCRIBE by clicking on the red SUBSCRIBE button above now.
Thanks for your SUBSCRIPTION and I look forward to seeing you again in my next video.
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