I have watched a few of your tutorials and am grateful for your thorough and easily understood directions and explanations. You have helped decreased my fear and increased my confidence!
Thank you for your videos! I'm wondering what to DO about outliers? What are the options, what is usually expected from students vs. mayeb researchers, what is most common...?
This video was very informative. I found it interesting to learn how to determine the outlier (-2.68 and 2.68). It has been a few years since I have used SPSS, but I think this video did an excellent job at showing how SPSS can organize your data
This video has been really helpful, but how do I know if my distribution is normal to use the z-score of 2.68? Do I need to run a further test in SPSS?
Hi Dr. Grande. I love your explanation, but I do not understand what you mean by using Z scores for population and box plots for the sample. Isn't the box plot representing the same data? The IQRs have not changed. I would appreciate a response. Thank you :)
One definition of outliers is data that are more than 1.5 times the inter-quartile range before Q1 or after Q3. Since the quartiles for the standard normal distribution are +/-.67, the IQR = 1.34, hence 1.5 times 1.34 = 2.01, and outliers are less than -2.68 or greater than 2.68. Hence for normally distributed data, the probability of being an outlier is 2 times .0037 = .0074. This is less than 1%.
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I have watched a few of your tutorials and am grateful for your thorough and easily understood directions and explanations. You have helped decreased my fear and increased my confidence!
You have single handedly saved my degree bless up Todd
This video was explained well and I think I understood the information. The step-by-step instructions throughout the video were helpful.
Thank you for your great explanation! It has made stats a little easier to answer.
I think it is a great video. I did step by step as Dr. Grande instructed and I was able to get the outliers for my variables. Thank you.
Very helpful and informative video on identifying outliers, especially remembering to rerun Z scores after adjusting data.
Thank you for your videos! I'm wondering what to DO about outliers? What are the options, what is usually expected from students vs. mayeb researchers, what is most common...?
This video was very informative. I found it interesting to learn how to determine the outlier (-2.68 and 2.68). It has been a few years since I have used SPSS, but I think this video did an excellent job at showing how SPSS can organize your data
You are the best Dr. Grande
When I run a box-plot I usually only pick out the extreme outliers with the little star sign. What would the z-score for an extreme outlier be?
I think I remember some of this from undergrad and I think can be very useful when analyzing data.
Hi Todd, nice video but slightly complicated method. Many thanks for your help.
You're welcome - thanks for watching.
Thank you for the well-explained video. How about the outliers within the groups? What is the best test for those?
This video has been really helpful, but how do I know if my distribution is normal to use the z-score of 2.68? Do I need to run a further test in SPSS?
Thank you! I more understand after watching your video =)
I also found this video a little difficult to understand; however, I appreciated being walked step through step.
Hi Dr. Grande. I love your explanation, but I do not understand what you mean by using Z scores for population and box plots for the sample. Isn't the box plot representing the same data? The IQRs have not changed. I would appreciate a response. Thank you :)
This video is well explained, but for someone who is not a statistician it is difficult to understand.
Why any value less than -.2.65 or greater than 2.68?
One definition of outliers is data that are more than 1.5 times the inter-quartile range before Q1 or after Q3. Since the quartiles for the standard normal distribution are +/-.67, the IQR = 1.34, hence 1.5 times 1.34 = 2.01, and outliers are less than -2.68 or greater than 2.68. Hence for normally distributed data, the probability of being an outlier is 2 times .0037 = .0074. This is less than 1%.
@@journeymantraveller3338 Do you have a reference for that definition of an outlier? Thank you.
Where are you getting the numbers -2.68 and 2.68?????
The calculations are little confusingWorking the problem out step by step first will help understand outliers But this introduction was helpful.
I agree I liked the step by step, but still found it confusing.
Great, thanks! 💯
sir how do you calculate the achievement gap of a group of students after and before an intervention?
What does SPSS mean? Statistical packages for the social sciences?
Why are there these new variables z scores?
You have to put the option "Save standardised values as variables" otherwise it will not work!
How about skewed data
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