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In Unit 7, you considered the t-test for autonomous means, and you utilized this test to think about two specimen bunches from the free variable called video access. In Unit 7, my examination inquiry was whether making video addresses for my understudies will essentially influence aggregate class focuses.
In Unit 7, I had a class of 30 understudies. To research this inquiry, I gave 15 understudies access to video instructional exercises every week, and the other 15 did not have entry.
My indigent variable was aggregate class focuses.
My inquiry was whether the mean aggregate class focuses for Group1 (understudies WITH video access) was essentially not quite the same as Group 2 (understudies WITHOUT video access).
Ho: mean aggregate focuses for Group1 = mean aggregate focuses for Group2
Ha: mean aggregate focuses for Group1 ≠ mean aggregate focuses for Group2
We can extend this idea into having a free variable that is isolated into more than two gatherings.
Assume that rather than looking at just two means (Group 1 and Group 2), I need to think about three unique gatherings:
Bunch 1: Watches all recordings (1 every week)
Bunch 2: Watches half of the recordings (1 each other week)
Bunch 3: Watches none of the recordings (no entrance to recordings)
Once more, my single autonomous variable is video access. Yet, for this situation, it is currently isolated into three gatherings (now and then called levels or classes).
Since I need to look at the mean aggregate focuses for every one of the three gatherings, I must utilize an ANOVA test.
Ho: mean aggregate focuses Group1 = mean aggregate focuses Group2 = mean aggregate focuses Group3
Ha: mean aggregate focuses Group1 ≠ mean aggregate focuses Group2 ≠ mean aggregate focuses Group3
Assume I imagine that I am going to dismiss the invalid speculation Ho. This implies that no less than one of my three video access gatherings is fundamentally not the same as the others. At the end of the day, utilizing alpha is .05, the p-esteem (Sig of the F test for ANOVA) is not as much as alpha and I can dismiss the invalid.
Next, I can utilize the Post Hoc to take a gander at an examination between each of the three gatherings. The Post's aftereffects Hoc will help me to figure out which gatherings are essentially not quite the same as one an
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