What is Hypotheses testing and what are its types?

Introduction

• Analytical methods are needed to handle the challenges posed by extensive data.

• The earliest and the most commonly used statistical analysis is hypothesis testing, whose first use dates back to 1710 by John

Arbuthnot

• Hypothesis testing finds its application in business, marketing, finance, biology, medicine, social science and psychology

Types and examples of hypothesis testing

• A statistical technique called hypothesis testing is used to assess a claim or hypothesis about a population parameter using sample data.

• It involves setting up a null hypothesis, the claim being tested, and an alternative hypothesis, which is the opposite of the null hypothesis.

There are several types of hypothesis testing, which are as follows:

• One-sample hypothesis testing: This type of test compares the mean of a sample to a known value or a hypothesised value.

Example:

• A researcher wants to test whether the average height of students in a school is 6 feet.

• The null hypothesis is that the average height is 6 feet, and the alternative hypothesis is that it is not equal to 6 feet.

• Two-sample hypothesis testing:

The most common type of hypothesis testing, this test compares the means of two different samples to determine whether they are significantly different

Example:

• The average salary for male and female employees will be compared to see if there is any discernible difference.

• While the null hypothesis states that there is no difference in the average salary, the alternative hypothesis is that there is a difference

If there is a significant correlation between two categorical variables, it will be revealed by this kind of test.

Example:

• A researcher wants to test whether a significant association between smoking status and lung cancer exists.

• For this research null hypothesis states that there is no association between smoking status and lung cancer, and the alternative hypothesis states that there is an association.

• ANOVA (analysis of variance):

This kind of test is used to examine whether the means of three or more groups differ significantly from one another

Example:

• A researcher wants to ascertain whether a statistically significant difference exists in the mean test scores from three teaching approaches.

• There is no difference in the mean score, according to the null hypothesis.

• On the contrary, the alternative hypothesis is that at least one of the average scores is different from the others.

Conclusion

• Hypothesis testing is a crucial aspect of statistical analysis that allows researchers to draw valid conclusions about populations based on sample data

• One-sample, two-sample, chi-square and ANOVA are the types of hypothesis testing that find their applications for analysing quantitative studies.

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