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Your question is a bit difficult to understand. I will rephrase: In hypothesis testing, when the sample mean is close to the assumed mean of the population (null hypotheses), what does that tell you? Answer: For a given sample size n and an alpha value, the closer the calculated mean is to the assumed mean of the population, the higher chance that null hypothesis will not be rejected in favor of the alternative hypothesis.
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What happens to the sample mean as the sample size increases?
With a good sample, the sample mean gets closer to the population mean.
When using the distribution of sample mean to estimate the population mean what is the benefit of using larger sample sizes?
The variance decreases with a larger sample so that the sample mean is likely to be closer to the population mean.
What is population mean in statistics?
The population mean is the mean value of the entire population. Contrast this with sample mean, which is the mean value of a sample of the population.
Why is the sample mean an unbiased estimator of the population mean?
The sample mean is an unbiased estimator of the population mean because the average of all the possible sample means of size n is equal to the population mean.
What does it mean for a sample to representative of a population?
That the key characteristics of the population are reflected in the sample.
