Null Hypothesis and Alternative Hypothesis | ANOVA | Hypothesis Statistics | Data Analysis

Null Hypothesis and Alternative Hypothesis | ANOVA | Hypothesis Statistics | Hypothesis Testing | Statistics and Data Analysis | Business Statistics | Lean Six Sigma | Research Hypothesis | Research Methodology | Data Analysis Hypothesis Testing | Data Science Hypothesis Testing
In this video, you will understand how can we state the null and alternative hypothesis? And what are the possible relations among the multiple population means under ANOVA?
Suppose we have ‘r’ number of populations or treatments having ‘r’ population means. Then the null hypothesis and alternative hypothesis under ANOVA will be stated as
Null Hypothesis: All population means are equal (all treatments are equally effective)
Alternative Hypothesis: Not all population means are equal (all treatments are different effective or not equally effective)
For example under an agricultural experiment, crops were given different treatments such as being grown using a different kinds of fertilizers, the null hypothesis states all treatments are equally effective.
Whereas the alternative hypothesis implies some treatments are better than others. Here better referred to those treatments that would produce crops of greater average weight. Hence the alternative hypothesis states the treatments are differently effective or not equally effective.
CHAPTERS:
0:00 Introduction
0:28 Null Hypothesis and Alternative Hypothesis of ANOVA
1:27 Example
#nullhypothesis #alternativehypothesis #anova #hypothesis #hypothesistesting #statistics #businessstatistics #leansixsigma #researchhypothesis #dataanalysis
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[@2mgarsilchar526]

wow thats so simply explained. Thank you so much.

[@nicolasbuchhammer3863]

Invaluable Help Thank you!

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