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How do one determine when a data is normally distributed? - Answers

Use the Kolmogorov Smirnoff goodness-of-fit test. A normal distribution is a bell shaped curve, which is nearly symmetrica. It looks like an upside down bell. It can be squished low (platykurtic) or pulled high and skinny (leptokurtic) but it is still bell shaped and symmetrical. A mathematical test is to use the pearson's skew. If the pearson's skew is between 0 and 0.49, then the data is a non-problematic or normally distributed. If it is greater than 0.50, then it is not a normal distribution so one cannot treat it as such. The pearson's skew equation is skew p= (3 (mean - median)) / (SD(x) SD(y))



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How do one determine when a data is normally distributed? - Answers

https://math.answers.com/math-and-arithmetic/How_do_one_determine_when_a_data_is_normally_distributed

Use the Kolmogorov Smirnoff goodness-of-fit test. A normal distribution is a bell shaped curve, which is nearly symmetrica. It looks like an upside down bell. It can be squished low (platykurtic) or pulled high and skinny (leptokurtic) but it is still bell shaped and symmetrical. A mathematical test is to use the pearson's skew. If the pearson's skew is between 0 and 0.49, then the data is a non-problematic or normally distributed. If it is greater than 0.50, then it is not a normal distribution so one cannot treat it as such. The pearson's skew equation is skew p= (3 (mean - median)) / (SD(x) SD(y))



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https://math.answers.com/math-and-arithmetic/How_do_one_determine_when_a_data_is_normally_distributed

How do one determine when a data is normally distributed? - Answers

Use the Kolmogorov Smirnoff goodness-of-fit test. A normal distribution is a bell shaped curve, which is nearly symmetrica. It looks like an upside down bell. It can be squished low (platykurtic) or pulled high and skinny (leptokurtic) but it is still bell shaped and symmetrical. A mathematical test is to use the pearson's skew. If the pearson's skew is between 0 and 0.49, then the data is a non-problematic or normally distributed. If it is greater than 0.50, then it is not a normal distribution so one cannot treat it as such. The pearson's skew equation is skew p= (3 (mean - median)) / (SD(x) SD(y))

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      Use the Kolmogorov Smirnoff goodness-of-fit test. A normal distribution is a bell shaped curve, which is nearly symmetrica. It looks like an upside down bell. It can be squished low (platykurtic) or pulled high and skinny (leptokurtic) but it is still bell shaped and symmetrical. A mathematical test is to use the pearson's skew. If the pearson's skew is between 0 and 0.49, then the data is a non-problematic or normally distributed. If it is greater than 0.50, then it is not a normal distribution so one cannot treat it as such. The pearson's skew equation is skew p= (3 (mean - median)) / (SD(x) SD(y))

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