Note for future revision. Two Different groups. Test of homogeneity = Test whether the Distribution of those groups for certain variable are similar or not. = Test whether the elements in the two groups are from the same population. = Test whether a var in both groups varies in similar way or not. If yes, then the elements in the groups are similar (and are from the same population). Ho = No difference in subject preference for left-hand and right-hand groups. Steps are exactly the same as test of independence. But in test of independence, we test whether two variables (left/right-handed and subject preference) affect each other.
sir are test of independence and test of homogeneity are same? or not.. because as far as i concern for you to able to reject null hypothesis the X^2 or the chi square must be greater to your alpha?
Sorry, don't we fail to reject the null hypothesis if the value is less than the critical value (5.991 assuming alpha=.05, df=2)? The Chi sq should be larger, isn't it?
The test for independence is evaluating whether or not two variables are truly independent of one another, whereas the test for homogeneity is testing whether or not two samples came from the same population. The approach is virtually the same though, in that your expected values for both tests are calculated by multiplying the marginal totals and dividing by total N.
i had a hard time understanding this, our professor give us other formula to solve homogeneity.. your formula there was the same with test of goodness-of-fit... idk anymore..
Note for future revision.
Two Different groups.
Test of homogeneity = Test whether the Distribution of those groups for certain variable are similar or not.
= Test whether the elements in the two groups are from the same population.
= Test whether a var in both groups varies in similar way or not. If yes, then the elements in the groups are similar (and are from the same population).
Ho = No difference in subject preference for left-hand and right-hand groups.
Steps are exactly the same as test of independence. But in test of independence, we test whether two variables (left/right-handed and subject preference) affect each other.
Thank you for uploading it
is there any tool for measuring the spatial homogeneity of one group of data?
Thank you so much 👍😍😍
How do we get the p-value?
sir are test of independence and test of homogeneity are same? or not.. because as far as i concern for you to able to reject null hypothesis the X^2 or the chi square must be greater to your alpha?
Sorry, don't we fail to reject the null hypothesis if the value is less than the critical value (5.991 assuming alpha=.05, df=2)? The Chi sq should be larger, isn't it?
I have the same doubt.
He said that
If the P-VALUE is less, not the statistic.
Thank you for the video
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Sir, are "test of homogeneity" and "test of independence" are same? Or these are same in case of two random variables??
The test for independence is evaluating whether or not two variables are truly independent of one another, whereas the test for homogeneity is testing whether or not two samples came from the same population. The approach is virtually the same though, in that your expected values for both tests are calculated by multiplying the marginal totals and dividing by total N.
i had a hard time understanding this, our professor give us other formula to solve homogeneity.. your formula there was the same with test of goodness-of-fit... idk anymore..
1 st.
Why can't u just upload something very simple n step by step 😔 and maybe use an easier example
that was pretty simple...