● Null hypothesis - The claim being assessed in a hypothesis test is called the null hypothesis. Usually, the null hypothesis is a statement of “no change from the traditional value,” “no effect,” “no difference,” or “no relationship.” For a claim to be a testable null hypothesis, it must specify a value for some population parameter that can form the basis for assuming a sampling distribution for a test statistic. ● Alternative hypothesis - The alternative hypothesis proposes what we should conclude if we find the null hypothesis to be unlikely. ● Two-sided alternative - An alternative hypothesis is two-sided when we are interested in deviations in (Two-tailed alternative) either direction away from the hypothesized parameter value. ● One-sided alternative - An alternative hypothesis is one-sided (e.g., ) when we are interested (One-tailed alternative) in deviations in only one direction away from the hypothesized parameter value. ● P-value - The probability of observing a value for a test statistic at least as far from the hypothesized value as the statistic value actually observed if the null hypothesis is true. A small P-value indicates either that the observation is improbable or that the probability calculation was based on incorrect

assumptions. The assumed truth of the null hypothesis is the assumption under suspicion. ● One-proportion z-test - A test of the null hypothesis that the proportion of a single sample equals a specified value.