Which Statistical test should I use

In summary, to calculate the probability or confidence interval that the 8th number from the top in a descending number series is larger than a certain number, say 9, the first step is to estimate the population mean and variance. This can be done using the normal estimator for the mean and the chi-square estimator for the variance, assuming a normal distribution. Once the estimators are obtained, a point estimate can be chosen to represent the population mean and variance. This information can then be used to calculate the final probability, which will be in terms of standard deviations from the mean. It is important to note that these calculations assume the data is normally distributed, and the Shapiro-Wilk test can be used to check this assumption.
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I have a number series ranked from largest to smallest in descending order from 10 - 1. the sample is assumed to be large enough to be normally distributed. If I pick say the 8th number from the top, which statistical test should I use to calculate the probability/C.I that the number picked is larger than a certain number, say 9?

It can be assumed that the mean and standard deviation of the sample is known
 
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Hey Link.

The first thing to do is to estimate the population mean and variance. If you are assuming a normal distribution, you can use the normal estimator for the mean and the chi-square estimator for the variance.

Once you have these estimators, you'll probably be choosing your point estimate (but remember the estimate is an uncertain thing so you will only get one out of very many: infinitly possible means both positive and negative and infinitly many variances greater than 0).

Then once you find an estimate to use for your population mean and variance, you use this information to get the final probability. The probability will correspond to whatever number you are picking, which will be in terms of standard deviations from the mean when dealing with a normalized distribution (which is used to do probability calculations for any normal).

It sounds like you haven't done much in the way of statistics, so look up estimators for normal distributions and how to estimate the mean and variance of the population of a normal distribution given a sample that assumes normality.

You should also probably inform the readers here why you assume its normal. The fact is that it may not be normal and that the assumptions you have do not reflect the reality of the data.

One test that is popular for checking whether something is normal under a measure of uncertainty is the Shapiro-Wilk test that can be done in any common statistics package, and you can use the same package to do the estimator calculations for you as well.
 

Related to Which Statistical test should I use

1. What is the purpose of statistical tests?

Statistical tests are used to analyze and interpret data in order to make conclusions or predictions about a population based on a sample. They help determine whether the results observed in a sample are due to chance or reflect true differences in the population.

2. How do I know which statistical test to use?

The type of statistical test to use depends on various factors, such as the research question, type of data, and study design. It is important to carefully consider these factors and consult with a statistician or refer to statistical textbooks or online resources to determine the most appropriate test for your data.

3. Can I use any statistical test for my data?

No, not all statistical tests are suitable for all types of data. For example, parametric tests assume that the data follows a normal distribution, while non-parametric tests do not have this assumption. It is important to understand the characteristics of your data and choose a test that is appropriate for those characteristics.

4. What is the difference between a parametric and non-parametric test?

A parametric test is based on certain assumptions about the data, such as a normal distribution, equal variances, and independence. Non-parametric tests, on the other hand, do not have these assumptions and are used for data that may not meet the requirements of parametric tests. Non-parametric tests are also considered more robust and can be used for smaller sample sizes.

5. Can I use more than one statistical test for my data?

Yes, it is common to use multiple statistical tests to analyze the same data, especially if the results of one test are inconclusive or if different aspects of the data need to be examined. However, it is important to be cautious when using multiple tests as it can increase the chances of making a Type I error (false positive).

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