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- No Problem. If you are having trouble in your school, you can just ask me.
- Thanks for explaining that to me. I think I have a better understanding of what a test statistic is now.
- The formula for the test statistic depends on the specific hypothesis being tested and the type of data you're working with. For example , if you're comparing the means of two groups, the test statistic might be the difference between the sample means divided by the standard error of the difference.
- For example, A researcher want to test whether the mean weight of a certain species of bird is different from 100g. They collect a random sample of 50 birds and measure their weights. The sample mean weight is 95g with a standard deviation 10g.Conduct a hypothesis test with a significance level of 0.05 using the appropriate test statistic.
- Okay, I think I get it. But how do you calculate the test statistic?
- plugging in the values, we get: t=(95-100)/50)=-3.16
- Since the sample size is greater then 30 and the population standard deviation is unknown, we can use a t-test. The appropriate test statistic is the t-score which is calculated as: t=(x-u)/(s/_/n) where x is the sample mean weight, u is the hypothesized population mean weight(100g), sis the sample standard deviation, and n is the sample size
- Using a t-distribution with 49 degrees of freedom ,we find that the p-value for a two-tailed test with a t-score of -3.16 isapproximately0.002. Since the p-value is less than the significance level, we reject the null hypothesis ad conclude that the mean weight of bird species is significantly different from 100g.
- That makes sense...
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