pooled /unpooled t test

Alma1

Hi 

What is the appropriate two sample t procedure for the summary below milking periods of cow breeds pooled/unpooled (Welch) using R?

Frisian cow          Xbar=342.5           S1=10.2                 n1=126

Jersey cow         Xbar =348.6           S2=12.2                 n2=39

Construct 95% confidence interval for µ1-µ2

Give proper interpretation of the interval

Thanks

Georg

@Alma1 , I do not know what data you have, an example would be helpful.

In the below script (when you execute) you see a dataset and both t-test performed, giving different results.

 

Generally, statistical Tests have preconditions, and t-test assumes normal Distribution of the dataset,

pooled t-test assumes equal variance,

t-test works also with different variance.

This is because they work with mean and variance, and if that two numbers do not represent the data correctly, the method doesn't work.

 

If you perform a t-test, and the assumptions are not valid, you cannot rely on the result.

In the below example you can see different results for both t-Tests, but be Aware, that normal Distribution is also not valid in this case.

You can find These results in the documentation also, and I found STIPS a quite good training to understand this stuff.

 

 

 

 

 

Names Default To Here( 1 );
cdt = Open( "$SAMPLE_DATA\companies.jmp" );

cdt << Oneway(
	Y( :Name( "Profits ($M)" ) ),
	X( :Type ),
	Means( 1 ),
	t Test( 1 ),
	Mean Diamonds( 1 ),
	SendToReport(
		Dispatch( {"Oneway Anova"}, "Summary of Fit", OutlineBox, {Close( 1 )} ),
		Dispatch( {"Oneway Anova"}, "Analysis of Variance", OutlineBox, {Close( 1 )} ),
		Dispatch( {"Oneway Anova"}, "Means for Oneway Anova", OutlineBox, {Close( 1 )} )
	)
);