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  1. 3 days ago · Common statistical tests include t-tests, Chi-squared, ANOVA, regression analysis, and more, and each is suited to different types of data and research questions. Using the wrong statistical test can lead to misleading conclusions, compromised data integrity, and invalid results.

  2. 4 days ago · This article explores various statistical tests, including parametric tests like T-test and Z-test, and non-parametric tests, which do not assume a specific data distribution. Through these tests, we can draw meaningful conclusions from our data.

  3. 4 days ago · Hypothesis Testing in Statistics. Hypothesis testing is a fundamental concept in statistics used to make decisions or inferences about a population based on a sample of data. The process involves setting up two competing hypotheses, the null hypothesis H0 and the alternative hypothesis H1 .

  4. 3 days ago · One-Tail vs Two-Tail Tests. Two-tailed Test. When testing a hypothesis, you must determine if it is a one-tailed or a two-tailed test. The most common format is a two-tailed test, meaning the critical region is located in both tails of the distribution. This is also referred to as a non-directional hypothesis.

  5. 3 days ago · Steps of Hypothesis Testing: State the Null & Alternative Hypotheses. These should reflect the hypothesis test that you anticipate conducting. For example, an alternative hypothesis for an ANOVA will state that there are significant differences between one or more means. Determine α.

  6. 5 days ago · In statistics, a two-tailed test is a method in which the critical area of a distribution is two-sided and tests whether a sample is greater or less...

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