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T-Test

This presentation educates you about T-Test, Key takeways, Assumptions for Performing a t-test, Types of t-tests, One sample t-test, Independent two-sample t-test and Paired sample t-test.<br><br>For more topics Stay tuned with Learnbay

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T-Test

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  1. T-Test Swipe

  2. T-Test A t-test is a type of inferential statistic used to determine if there is a significant difference between the means of two groups, which may be related in certain features. It is mostly used when the data sets, like the data set recorded as the outcome from flipping a coin 100 times, would follow a normal distribution and may have unknown variances.

  3. T-Test A t-test is used as a hypothesis testing tool, which allows testing of an assumption applicable to a population. A t-test looks at the t-statistic, the t-distribution values, and the degrees of freedom to determine the statistical significance. To conduct a test with three or more means, one must use an analysis of variance.

  4. Key takeways A t-test is a type of inferential statistic used to determine if there is a significant difference between the means of two groups, which may be related in certain features. The t-test is one of many tests used for the purpose of hypothesis testing in statistics.

  5. Calculating a t-test requires three key data values. They include the difference between the mean values from each data set (called the mean difference), the standard deviation of each group, and the number of data values of each group. There are several different types of t-test that can be performed depending on the data and type of analysis required.

  6. Assumptions for Performing a t-test The data should follow a continuous or ordinal scale (the IQ test scores of students, for example) The observations in the data should be randomly selected The data should resemble a bell-shaped curve when we plot it, i.e., it should be normally distributed. You can refer to this article to get a better understanding of the normal distribution Large sample size should be taken for the data to approach a normal distribution (although t-test is essential for small samples as their distributions are non-normal) Variances among the groups should be equal (for independent two-sample t-test)

  7. Types of t-tests One sample t-test Independent two-sample t-test Paired sample t-test

  8. One sample t-test The one-sample t-test is a statistical hypothesis test used to determine whether an unknown population mean is different from a specific value.

  9. Independent two-sample t-test The two-sample t-test (also known as the independent samples t-test) is a method used to test whether the unknown population means of two groups are equal or not.

  10. Paired sample t-test The paired sample t-test, sometimes called the dependent sample t-test, is a statistical procedure used to determine whether the mean difference between two sets of observations is zero. In a paired sample t-test, each subject or entity is measured twice, resulting in pairs of observations

  11. Topics for next Post Chi-square Test Non-Probability methods Sentimental Analysis Stay Tuned with

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