Hypothesis Testing in Statistics

AI Thread Summary
The discussion focuses on hypothesis testing using a sample of 30 rats, consisting of 18 females and 12 males, to determine if the proportion of treated females differs from last year's 0.65. The null hypothesis is set as p = 0.65, while the alternative hypothesis is p ≠ 0.65. The participant is uncertain about which test statistic to use for calculating the p-value and whether to apply the normal or binomial approximation. It is noted that the normal distribution can be used due to the sample size and number of successes, although there is consideration of the binomial test for smaller samples. The thread concludes with an appreciation for guidance on approaching the problem.
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Homework Statement



A random sample of 30 rats has 18 females and 12 males. If last year's proportion of females treated was 0.65, do the above data confirm that this year the proportion of females is different than last year?

Homework Equations



p = treated / total
If using standard normal: z = (value - mean) / (standard deviation / squareroot(sample size) )

The Attempt at a Solution



I *think* the null hypothesis is p = 0.65 and the alternative hypothesis is p ≠ 0.65
What I'm stuck on now is I don't know what test statistic to use to find the p value to decide if I should reject the null hypothesis. Not sure if normal or binomial is supposed to be used and how to do the calculations for this.
 
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As you can see from this, in most cases the normal is a good approximation to the binomial. Your null hypothesis is p = 0.65, so normal mean = 0.65 * 30 = 19.5 and normal variance = p*(1-p)*30 under the null hypothesis.
 
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say that if I can't use the normal approximation, how would I do this?
 
Why wouldn't you use the the usual test for one proportion?

<br /> H_0 \colon p = 0.65, \quad H_a \colon p \ne 0.65<br />

with test statistic

<br /> Z = \frac{\hat p - 0.65}{\sqrt{\dfrac{0.65 \cdot 0.35}{30}}}<br />

Your sample size, together with the number of "successes", will allow you to use the normal distribution for your test.
 
I was thinking about using binomial in case the sample size was really really small (small proportions test) but I'll worry about that later.

Thanks for showing me how I was supposed to approach this problem. :)
 
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