HYPOTHESIS Testing

Source:  https://www.sixsigma-institute.org

Here, we will discuss the several types of Hypothesis testing for Discrete Independent variables.

1.       T Test

T-Test is used to determine the hypothesis for cases. The t test is one type of inferential statistics. It is used to determine whether there is a significant difference between the means of two groups. With all inferential statistics, we assume the dependent variable fits a normal distribution. A t test is used when we wish to compare two means (the scores must be measured on an interval or ratio measurement scale.)

Following assumptions are made for T-test

·         The samples have been randomly drawn from their respective populations

·         The scores in the population are normally distributed

·         The scores in the populations have the same variance (s1=s2)

T test is appropriate when there is only one independent variable and one dependent variable.

1.       Simple T-test

Simple T-Test is used in cases when there are two levels within the independent variable. For example: the impact of training employees on the efficiency of their performance. The research question for t-test would be “Is there significant impact of training on the efficiency of employees?”

2.       Independent T-Test

Independent T-test is used when there are more than two levels in the independent variable. For example: “Is there significant impact of training on the efficiency of lower management, middle management and top management on their work efficiceny?”

3.       Paired T-Test

Paired T-test is used in cases where there is a pre and a post analysis. The same research/survey is conducted on the same set of population before and after an event. For example: “Efficiency of employees before and after the week long training.”

2.       ANOVA

ANOVA is short for ANalysis Of Variance. ANOVA is used when there are more than two levels of Independent variables and only one dependent variable. For example: “impact of Surf excel, Rin and Wheel on the cleanliness of the cloth.” ANOVA can be said to be combination of n number of T-test.

ANOVA can have two or more independent variables too. A two-way ANOVA has two independent variables. And it has three research questions: One for each of the two independent variables and one for the interaction of the two independent variables.

Sample Research Questions for a Two-Way ANOVA:

Do Democrats, Republicans, and Independents differ on their opinion about a tax cut?

Do males and females differ on their opinion about a tax cut?

Is there an interaction between gender and political party affiliation regarding opinions about a tax cut?

3.       MANOVA

MANOVA is short for Multiple ANalysis Of Variance. MANOVA is best used when there are multiple independent variables and multiple dependent variables. MANOVA is a combination of n number of ANOVA.

MANOVA is complicated and it is advised to use ANOVA n times rather than using MANOVA.

References:

https://researchbasics.education.uconn.edu/t-test

https://researchbasics.education.uconn.edu/anova_regression_and_chi-square