September 18, 2019 by Statisticshomeworkhelper
ANOVA is popularly known as analysis of variance. It was developed in the 1920s by a famous statistician called Robert Fisher. ANOVA is a collection of statistical tools that are used to draw significant conclusions about various data sets. Since 1920 this area has advanced in a higher dimension with new changes. Improvements have facilitated statisticians to infer meaningful findings across multiple research areas. For that reason, ANOVA has been incorporated as a universal module to students pursuing statistics as a major. It's an exciting area of study which demands a full understanding of what you are doing. You don't jump into questions, but you must have serious comprehension of data set facets. Which are vital basics you must know before tackling any problem related to ANOVA?
1. The variance- It will help you to draw necessary inferences by comparing results from diverse sets of data.
2. Standard deviation- Understand how to quantify each data in a set of different mean observations.
3. The T- tests- You must be able to analyze the two means given through statistical examinations to get correct answers.
4. Hypothesis testing - Ensure you can determine results from the different samples. By testing hypothesis, you should either reject or accept the inferences you obtain reflecting the population.
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