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Biostatistics · Biostatistics Fundamentals

Biostatistics: Hypothesis Testing and P-Values

Null and alternative hypotheses, type I and type II error, statistical power, confidence intervals, and p-value interpretation, as cloze cards with each term defined.

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The ____ is the default claim that there is no effect or no difference in a statistical test.
null hypothesis
The ____ states that there is an effect or difference, contradicting the null hypothesis.
alternative hypothesis
A ____ occurs when a true null hypothesis is incorrectly rejected.
Type I error
The probability of committing a Type I error is denoted by the symbol ____.
alpha
A ____ occurs when a false null hypothesis is incorrectly not rejected.
Type II error
The probability of committing a Type II error is denoted by the symbol ____.
beta
____ is the probability that a test correctly rejects a false null hypothesis.
statistical power
Statistical power is calculated as ____.
1 minus beta
The most commonly used significance level (alpha) in biomedical research is ____.
0.05
The ____ is the probability of observing a result as extreme or more extreme than the one obtained, assuming the null hypothesis is true.
p-value
When the p-value is ____, the null hypothesis is rejected.
less than the significance level (alpha)
A p-value does not measure the probability that the null hypothesis is ____.
true
A ____ is a range of values calculated from sample data that is likely to contain the true population parameter.
confidence interval
A 95% confidence interval means that if the sampling process were repeated many times, about ____ percent of the resulting intervals would contain the true parameter.
95
Increasing the ____ generally increases the statistical power of a test.
sample size

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