Chi Square Test for Gaussian Distribution

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SUMMARY

The discussion centers on determining whether a given set of data points follows a Gaussian distribution using statistical methods. The Chi-Square Test is mentioned as a potential method for this analysis, but it is concluded that a Normal Probability Plot is a more suitable tool for testing normality. Participants emphasize the importance of visualizing data distribution before applying statistical tests. Free tools for creating Normal Probability Plots are recommended for users seeking to analyze their data effectively.

PREREQUISITES
  • Understanding of Gaussian distribution and normality concepts
  • Familiarity with the Chi-Square Test for goodness of fit
  • Knowledge of Normal Probability Plots and their interpretation
  • Basic statistical analysis skills
NEXT STEPS
  • Learn how to perform a Chi-Square Test for goodness of fit
  • Explore how to create and interpret Normal Probability Plots
  • Research free statistical software tools for data analysis, such as R or Python libraries
  • Study the Central Limit Theorem and its implications for normality in data sets
USEFUL FOR

Statisticians, data analysts, and researchers interested in testing data for normality and understanding Gaussian distributions.

miztaken
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Hi there,
I have very naive to statistics.

I have a set of data points. that can be like

10, 12, 13, 14 ,15 , 15, 12, 13 17, 18, 19, 12, 19, 20 ....

Now i need to know if these days points follows any gaussian distribution / normal distribution or not?

IS chi -square test the right way to test this?

If yes, what steps do i have to take to accomplish this.. also it will be good if there is any free tool that can help me do this?

if no, what do i have to do...to know the distribution my datapoints follow?/

Thank you very much for your time..
 
Physics news on Phys.org
To test for normality, a http://en.wikipedia.org/wiki/Normal_probability_plot" would be more appropriate.
 
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