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Chapter 10 Review Vocabulary Null hypothesis Claim about population that is initially assumed to be true Statement of equality Alternative hypothesis Competing claim that we search for evidence for Statement of inequality Test statistic Calculated z / t value P-value Probability of this sample statistic or one more extreme occurring assuming that the null hypothesis is true Significant When p<α our sample statistic probability did not happen by random chance, but instead we believe alternative to be true Error Type I Error Error of rejecting null when null is true Denoted by α, significance level Always remember CONTEXT! Type II Error Error of failing to reject null when null is false Denoted by β Remember that as α increases, β decreases. Would you prefer a test with α=0.01 or α=0.05? Power Power Probability of correctly rejecting the null When H0 false, power = 1 - β Factors that affect Power: Sample size Significance level Discrepancy between hypothesized value and true value The larger any of these three are, the higher the power PHANTOMS P – parameter H – hypothesis Remember to describe both in context of problem A – assumptions N – name Test name, α, table, tails, df (if applicable) T – test statistic O – output For conclusion, remember that your decision is in terms of ALTERNATIVE. You can R or FTR null, which means you do or do not have evidence for Ha. M – make your decision (R or FTR) S – state your conclusion in CONTEXT P-value shows…. Large-Sample Hypothesis Test for Population Proportion A – assumptions Same as assumptions for confidence interval T – test statistic z p (1 ) n One-Sample t Test for Population Mean A – assumptions Same as assumptions for confidence interval Sample size must be large OR population approximately normal T – test statistic x t s n Statistical vs. Practical Significance Formula Sheet