Comparing Weight Gain in Rats: An Analysis of Diets A & B

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Homework Help Overview

The discussion revolves around a study comparing weight gain in male rats on two different diets, A and B, focusing on statistical analysis methods such as F-tests and t-tests to evaluate the data collected from the experiment.

Discussion Character

  • Exploratory, Conceptual clarification, Mathematical reasoning, Problem interpretation

Approaches and Questions Raised

  • Participants discuss the rationale for conducting an F-test to compare sample standard deviations and the necessary components such as null hypotheses and significance levels. There are questions about the correct formulas for t-tests and confidence intervals, as well as the implications of using paired versus independent tests.

Discussion Status

Some participants have provided guidance on defining hypotheses and selecting significance levels. There is an ongoing exploration of the appropriate statistical methods to apply, with multiple interpretations of the formulas and their applications being discussed. Participants express uncertainty about the correct approaches and seek clarification on various aspects of the statistical tests.

Contextual Notes

Participants mention reliance on textbooks and statistical tables for critical values and formulas, indicating constraints in accessing resources. There is also a focus on the implications of sample size decisions in the context of the study.

  • #31
I like Serena said:
Yes...

So the interval would be close to zero in the plus and minus direction, something like
(-3, 3)

Like that yeah?
 
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  • #32
Yes! :smile:

So how can you see from your interval whether it is significant or not?
 
  • #33
Because my interval has both boundaries greater than zero, we're 95% certain the difference is between these boundaries, so that means we're 95% certain the difference is greater than zero. This is significant and forces us to reject the null hypothesis?
 
  • #34
Yep! :smile:

When you use a CI in a test to compare the means of two samples, the criterion is whether the CI contains zero.
 
  • #35
Ah I see! :smile:

So it would be better to do a confidence interval instead of a t-test?
 
  • #36
Ah, now we're getting into the murky stuff that is open questions and discussions.

Let me counter that by asking: what are the pro's and con's of a CI versus a t-test?
What's the difference anyhow between a t-test and this confidence interval?

And I'll ask one more question: can you do a 1-sided test with a confidence interval?
 
  • #37
With a CI, we know that if the interval doesn't contain zero the means can't be the same. With a t-test we're relying on probabilities and approximations.

I would sat yes, because if you test Ha: u1>u2, and find a CI for u1-u2, and if this doesn't contain zero we're 95% certain Ha is true
 
  • #38
Maybe_Memorie said:
With a CI, we know that if the interval doesn't contain zero the means can't be the same. With a t-test we're relying on probabilities and approximations.

Wow! Stop!
A CI does not give certainty!
Basically the CI is a t-test. It's just represented differently.
But the ultimate result (rejection or not) is the same.

Maybe_Memorie said:
I would sat yes, because if you test Ha: u1>u2, and find a CI for u1-u2, and if this doesn't contain zero we're 95% certain Ha is true

Hmm, suppose the CI is (-6, -1).
That does not contain 0.
Does that mean Ha is probably true?
 

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