BIOL 3327 Experimental Methods Lecture 7

These flashcards cover the key concepts and definitions related to the t-test and statistical analysis as discussed in Lecture 7 of BIOL 3327.

What is the purpose of a t-test?

The t-test allows us to determine whether the difference between two means is significant and not due to chance.

What is considered a statistically significant result in a t-test?

A result is considered statistically significant if the p-value is less than or equal to 0.05.

What does a p-value represent in statistical analysis?

A p-value represents the probability that the observed data would occur by chance if the null hypothesis were true.

How does sample size affect the estimate of variance in a t-test?

Smaller sample sizes can lead to poorer estimates of variance, increasing the risk of Type 1 and Type 2 errors.

What is the null hypothesis in a t-test?

The null hypothesis (H0) states that there is no difference between the means of two populations.

What is the effect of sample size on the t-test's results?

With larger sample sizes, the t-test yields more accurate estimates of the means and variance, reducing error rates.

What are degrees of freedom in the context of a t-test?

Degrees of freedom in a t-test are calculated as the total sample size minus the number of groups being compared (n-1).

What does a symmetrical distribution indicate in a normal distribution?

In a symmetrical distribution, the values are evenly distributed around the mean, with 68% of data within one standard deviation and 95% within two.

What is the difference between statistical significance and biological relevance?

Statistical significance refers to the likelihood that a result is not due to chance, while biological relevance refers to the practical importance of a result in a biological context.

What is a Type 1 error in statistical testing?

A Type 1 error occurs when a true null hypothesis is incorrectly rejected, resulting in a false positive.