2^k Factorial Designs Experiment - ANOVA Model

This lecture explains 2^k Factorial Designs Experiment - ANOVA Model.
Other videos ‪@DrHarishGarg‬
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Lecture 1: One Way ANOVA Theory: Link: • Lecture #1: One-Way AN...
Lecture 2: Procedure of One-Way ANOVA: Link: • Lecture #2: Solved Exa...
Lecture 3: Two-Way ANOVA Theory & Introduction: • Lecture #3: Two way AN...
Lecture 4: Two-Way Anova Examples: Link: • Lecture #4: Solved Exa...
Lecture 5: Latin Square Design - ANOVA Model: Link: • Lecture 05: Latin Squa...

[@prayaanshmehta3200]

3:00 yates notation
5:40 2^2 ANOVA
contrast 6:30

[@komalameen3819]

amazing

[@shyamalab.s9345]

Sir please make a video on concept of confounding

[@jyotibhatia2809]

Sir plz make video about confounding and partial confounding

[@muhammadsobankhan7348]

Sir please explain Confounding topic

[@surajsamant7661]

you are doing great work sir💥💥

[@DrHarishGarg]

My pleasure ... Keep watching and sharing with others too

[@DrHarishGarg]

Many thanks....
Join my telegram link of Probability and Statistics
t.me/gargProbability

[@domenicoscarpino3715]

Hi sir, does this design works when we have multiple factors and multiple levels? For instance 4 factors and 3 levels each. Thanks in advance

[@vaibhavjadhav1457]

In which case, G^2 / N ( correction factor ) will be zero?

[@UJJWAL_SHARMA0]

Sir, can you write some merits of Stratified random sampling?
I shall be highly obliged to you sir.
Mujhe university exam me likhna hai mila nahi book m ye...plz

[@yohanesb.1728]

dear prof,
I want to test whether public exposure (IV2) to norm violations and relations with perpetrators (IV 1) of norm violations have an effect on observer vicarious embarrassment (VE).
So there are two factors that cause VE, namely public exposure and relations with perpetrators of norm violations. Public exposure has two levels, namely (a) there is exposure and (b) there is no exposure/quiet. Level relationships: (a) Friends and (b) strangers. I'm planning to use a vignette to get the VE data. My question is:
1). Should the vignette show two directly interacting variables such as: "My friend (IV2) spoke loudly in the library and was seen by many people (IV1), how embarrassed are you for her actions?" or
2) vignette only contains information for each level independently. Examples in friendship relationships: My friend (IV1) spoke loudly in the library, how embarrassed are you for what he did?, Someone you don't know (IV1) spoke loudly in the library how embarrassed were you for what he did?
I think that to get the main effect, the simulation is carried out per level, and then a statistical test of the interaction between IV1 and IV2 is carried out.
Meanwhile, if the vignette contains two IVs that interact directly with each other, such as (friends x public exposure), (foreigners x public exposure), then this has directly tested the interaction effect so that the main effect for each IV is not obtained. Is my thinking correct?
The analysis is repeated measures for 4 different conditions.
thank you for your kindness.

[@kritikagrover4980]

Sir in. S power n. What s and n denote??

[@mathewkpv]

I think, at 15:10, the first value in column 1 is wrong. I got the value as 111.767 instead of 115.380. With my value of 111.767 the values on the column 2 are obtained as given by you. But if 115.380 is used the Grand total obtained is also wrong.

[@avnimishra6874]

If sum of square is zero than what to do....plz answer

[@DrHarishGarg]

Sum of sqaure will be zero only for constant series otherwise it will never be zero... Check your calculation.

[@user-nl1sc2mg3x]

hindi me bol na