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Table of contents Step 1: Write your hypotheses and plan your research design. Step 2: Collect data from a sample. Step 3: Summarize your data with descriptive statistics. Step 4: Test hypotheses or make estimates with inferential statistics. Step 5: Interpret your results. Other interesting articles.

A statistical test provides a mechanism for making quantitative decisions about a process or processes. The intent is to determine whether there is enough evidence to "reject" a conjecture or hypothesis about the process. The conjecture is called the null hypothesis.

For example, the test statistic for a Z-test is the Z-statistic, which has the standard normal distribution under the null hypothesis. Suppose you perform a two-tailed Z-test with an ? of 0.05, and obtain a Z-statistic (also called a Z-value) based on your data of 2.5. This Z-value corresponds to a p-value of 0.0124.

Statistics deals with collection, organisation, analysis and interpretation of data. The word 'statistics' has different meanings in different contexts.

Data is any numerical or. categorical data. Statistics is used to predict and make decisions. Describing is done through. statistical formulas, and analysis is interpretation of this data through statistical formula also.

How to calculate a test statistic Find the raw scores of the populations. Assume you want to perform a z-test to determine whether the means of two populations are equal. ... Calculate the standard deviation of the population. ... Calculate the population mean. ... Evaluate the z-value. ... Apply the t-test formula. ... Interpret the results.

There are many different types of tests in statistics like t-test,Z-test,chi-square test, anova test ,binomial test, one sample median test etc. Parametric tests are used if the data is normally distributed .