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Computing Pooled Variance and Standard Error for 2 Sample Means

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Two separate samples, each with n=15 individuals, receive different treatments. After treatment, the first sample has SS=1740 and the second has SS=1620.
The pooled variances for the two samples is _________.
Compute the estimated standard error for the sample mean difference.
Estimated s(M1-M2)=________
If the sample mean difference is 8 points, is this enough to reject the null hypothesis and conclude that there is a significant difference for a two tailed test at the .05 level?
* Fail to reject the null hypothesis; there is no significant difference.
* Reject the null hypothesis; there is a significant difference.
* Fail to reject the null hypothesis; there is a significant difference.
* reject the null hypothesis; there is no significant difference.

t - critical = ±_________
t= ________

Assume that the two samples are obtained from populations wight the same mean, and calculate how much difference should be expected, on average, between the two sample means.
Each sample has n=4 with s2=68 for the first sample and s2= 76 for the second. ________
Each sample has n=16 scores with s2=68 for the first sample and s2=76 for the second. ______
In the second part of this question, the two samples are bigger than in the first part, but the variances are unchanged. How does the sample size affect the size of the standard error for the sample mean difference?
* As sample size increases, standard error remains the same.
* As sample size increases, standard error increases
* As sample size increases, standard error decreases.

https://brainmass.com/statistics/hypothesis-testing/computing-pooled-variance-and-standard-error-for-2-sample-means-585063

Solution Preview

The pooled variances for the two samples is ___(1740+1620)/(15-1+15-1)=120______.

Estimated s(M1-M2)=___sqrt[120*(1/15+1/15)]=4_____

If the sample mean difference is 8 points, is this enough ...

Solution Summary

The solution gives detailed steps on computing pooled variance, standard error for two sample means and explaining relevant hypothesis testing problem.

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