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The larger the sample size, the more accurate the test results.

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Q: How does sample size effect the test statistic?
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What is the meaning of Sampling distribution of the test statistic?

Given any sample size there are many samples of that size that can be drawn from the population. In the population is N and the sample size in n, then there are NCn, but remember that the population can be infinite. A test statistic is a value that is calculated from only the observations in a sample (no unknown parameters are estimated). The value of the test statistic will change from sample to sample. The sampling distribution of a test statistic is the probability distribution function for all the values that the test statistic can take across all possible samples.


If you select a large enough sample size can you reject any null hypothesis?

The simple answer is no. This depends on a lot of factors such as alpha which determines the critical value and the absolute value of the difference between the claim and sample data. Mathematically speaking, all things being equal, the larger the sample size the larger the absolute value of the test statistic. The formula for the test statistic mean with sigma known is shown below. You can substitute values in and perform the mathematics. The larger the sample size, the larger the Z value; but note if the numerator is small, even a small denominator will not produce a large Z value. In fact, the numerator could be zero which would make the test statistic zero. Z = (Xbar - μxbar)/(σ/√n) (formula from Elementary Statistics by Mario F. Triola)


The s2 statistic is used to test to test whether the assumption of normality is reasonable for a given population distribution The sample consists of 5000 observations and is divided into 6 category?

The s2 statistic is used to test to test whether the assumption of normality is reasonable for a given population distribution. The sample consists of 5000 observations and is divided into 6 categories (intervals). The degrees of freedom for the chi-square statistic is:


Why would you use a z test rather than a t test?

When the sample size is greater than 30


You are using the t distribution to estimate or test the mean of a sample from a single population If the sample size is 25 then the degrees of freedom are?

There are 24 df.