One-Way And Two-Way-Anova

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what is ANOVA ? 🤔

ANOVA means Analysis of Variance is way to find out if survey or experiment result are significant .In normal words it is use to figure out if you have to Rejcet Null Hypothesis or accept alternate Hypothesis.

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One-way and Two-Way refer to the number of independent variables in your ANOVA.

• One-way has one independent variable (with 2 levels)
• Two-way has two independent variables (it can have multiple levels)

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One Way ANOVA:

A one way ANOVA is used to compare two means from two independent (unrelated) groups using the F-distribution. The NULL Hypothesis for the test is that the two are means equal. Therefore, a significant result means that the two means are unequal.

if you want to try the shiny app click here.the sample data set is provided in the repository for data set click here.

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Limitations of One-Way Anova:

A one way ANOVA will tell you that at least two groups were different from each other. But it won’t tell you which groups were different. If your test returns a significant f-statistic, you may need to run an ad hoc test (like the Least Significant Difference test) to tell you exactly which groups had a difference in means.

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Two Way ANOVA:

A Two Way ANOVA is an extension of the One Way ANOVA. With a One Way, you have one independent variable affecting a dependent variable. With a Two Way ANOVA, there are two independents. Use a two way ANOVA when you have one measurement variable (i.e. a quantitative variable) and two nominal variables. In other words, if your experiment has a quantitative outcome and you have two categorical explanatory variables, a two way ANOVA is appropriate.

if you want to try the shiny app click here.the sample data set is provided in the repository for data set click here.

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if you want to try the merged shiny app click here.

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