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Is it okay to use hypothesis testing with at test when population distribution is not normal?
For a t-test to be valid on a sample of smaller size, the population distribution would have to be approximately normal. The t-test is invalid for small samples from non-normal distributions, but it is valid for large samples from non-normal distributions.
Does we need normal distribution for hypothesis testing?
In order for a hypothesis test’s results to be generalized to a population, certain requirements must be satisfied. The normal test will work if the data come from a simple, random sample and the population is approximately normally distributed, or the sample size is large, with a known standard deviation.
Can you use Anova with non normally distributed data?
As regards the normality of group data, the one-way ANOVA can tolerate data that is non-normal (skewed or kurtotic distributions) with only a small effect on the Type I error rate. However, platykurtosis can have a profound effect when your group sizes are small.
How to test hypothesis that data does not have normal distribution?
Assuming my data does not have a normal distribution, how to test these hypothesis? Join ResearchGate to ask questions, get input, and advance your work. Some statistical tools do not require normally distributed data.
What happens if the t-test assumes normality?
Of course if X isn’t normally distributed, even if the type 1 error rate for the t-test assuming normality is close to 5%, the test will not be optimally powerful. That is, there will exist alternative tests of the null hypothesis which have greater power to detect alternative hypotheses.
Is the t-test valid when x does not follow a normal distribution?
In fact, as the sample size in the two groups gets large, the t-test is valid (i.e. the type 1 error rate is controlled at 5%) even when X doesn’t follow a normal distribution. I think the most direct route to seeing why this is so, is to recall that the t-test is based on the two groups means and .
What are the steps of a hypothesis test?
General Steps of Hypothesis (Significance) Testing Steps in Any Hypothesis Test 1. Determine the null and alternative hypotheses. 2. Verify necessary data conditions, and if met, summarize the data into an appropriate test statistic. 3. Assuming the null hypothesis is true, find the p-value.