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I have two groups of data (N > 30 in each group). I want to know if the two groups differ from each other. So I thought about making an independent t-test. … My question is: Am I still allowed to perform a t-test knowing that my groups are not normally distributed and that I have N > 30 in each group? Thank you for your time. …

I am recording the subjects' responses via a sensitive brain instrument, so I've been told that exposing them to the stimulus 30 or more times is desirable. … Is it possible to get at my N by having more subjects rather than more events per subject? If not, under what circumstances is an N < 30 acceptable? …

From population choosing samples(size n=30) and calculate its mean then repeating it N times will converge to normal distribution as N->inf when mean of each sample is plotted as a histogram. … edit: for clarification I am referring to n,N as follows: n = number of data in a sample N = number of time sample(of size n) is sampled …

Can one use paired t-test for N over 30? …

I also now that due to CLT, samples of n > 30 can be assumed normal, and that my sample size is 58; however, I ran a Shapiro-Wilk Test for normality and it rejected the null hypothesis that the data is …

My understanding is my method would tell me if it's appropriate to do a normal distribution though because I thought that for heavy skewed data the n to reach ~normal distribution was higher. … Also if needing a sample size of 30 was all you needed for assuming normality why is so much work done on other distributions in statistical software? …

I want to use repeatead measures ANOVA with sample size approximately n=40. Normality is violated according to S-W test. …

In multiple-choice answer statistics exams, I've had to use this approximation instead of $(1)$ whenever $n \geq 30$. … I don't want, ever again, to blindly apply the rule $n \geq 30$. Are there good references that can support me in a refusal to do so and provide appropriate alternatives? …

My understanding is that, to apply a t-test, the distribution itself does not need to be normally distributed as long as the mean of samples of size n drawn from the distribution is normally distributed … Would it make sense to draw several samples with replacement of size, say, 30 from my larger dataset to generate a histogram? …

The dataset is refers to N = 18000 and about 30 clusters. …

I have found the z score by taking the square root of pqr (30).5.5 =sq rt of 7.5. z score = 1.15 and using tables probability = 23.27% chance of rain more than 20 of the 30 days we checked. …

The students are drawn from a discrete uniform distribution. This is one of the exercise questions from mit.ocw. I can't quite figure out how to use the numbers selected (1,3,7) into the likelihood es …

I have a bag of 60 marbles(N=60). I can only examine 30 random marbles (n=30) at a time. After each trial, I replace the sampled marbles back in the bag. …

In a case where X is normally distributed, and n > 30, and $\sigma^2$ is known, it is obvious a Z-test is appropriate. … Similarly, suppose X is not normally distributed, but n > 30, and $\sigma^2$ is not known. …

What statistics to use for testing hypothesis about regression coefficient when n is 120. I plan using a z score but am not sure. …