Tutorial 21- Chi Square test simply Explained In Stats- Krish Naik Hindi
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- čas přidán 10. 01. 2024
- A chi-squared test (also chi-square or χ2 test) is a statistical hypothesis test used in the analysis of contingency tables when the sample sizes are large. In simpler terms, this test is primarily used to examine whether two categorical variables (two dimensions of the contingency table) are independent in influencing the test statistic (values within the table).[1] The test is valid when the test statistic is chi-squared distributed under the null hypothesis, specifically Pearson's chi-squared test and variants thereof. Pearson's chi-squared test is used to determine whether there is a statistically significant difference between the expected frequencies and the observed frequencies in one or more categories of a contingency table.
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Complex concept explained through simple problem. Fentastic
Fantastically explained!
sir u r amazing ,ur teaching style is very nice and i appreciate u for giving us this fruitfull knowledge
Yes sir bohot maza aya samaj ne mein
Thanku sir ❤❤❤
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Thank you sir so much
Thank u sir
can anyone please give link for these notes?
The data is left-skewed
Sir, in the last conclusion, I think that they want to verify the ratio or the % change in the categories rather than the cumulative population change because the Chi square test about the categorical variables, or in other words, the question is to identify that what is the change in the distribution in the dataset. Could you please correct me if I am wrong?
Sir will it be helpful for gate da.
Sir app bholte ho ki hame population bohot big hota than aapne population proportion kaise findout kiya