Download Statistical Inference: Understanding Confidence Intervals and Hypothesis Testing and more Quizzes Statistics in PDF only on Docsity! TERM 1 If p-value < (alpha) DEFINITION 1 Possible Type II Error Reject H Test is significant There is enough evidence to suggest a change, increase, etc. Strong evidence against the null Possible Type I Error TERM 2 If p-value > (alpha) DEFINITION 2 Fail to reject H0 (but never accept it!) Test is insignificant There is insufficient evidence to suggest a change, increase, etc. No strong evidence against the null Possible Type II Error TERM 3 Point Estimate DEFINITION 3 sample mean/proportion TERM 4 Confidence Interval for Proportions DEFINITION 4 point estimate+ confidence interval(z) * standard error TERM 5 Computing a Confidence Interval DEFINITION 5 -first get point estimate-find margin of error- z* standard error- t* standard error- upper limit- point estimate- + or - point estimate from margin of error- ___% confident that population proportion/mean is in the interval TERM 6 Properties of a C.I. DEFINITION 6 The sample proportion/mean is ALWAYS inside the confidence interval!- in the middleThe population proportion/mean may or may not be inside the confidence interval TERM 7 Interpretation of a C.I. DEFINITION 7 We are 95% confident the population mean/proportion is somewhere inside the interval. The population mean, while unknown, is fixed What changes is the intervalIt is incorrect to say The population mean isin the confidence interval 95% of the time.A 95% C.I. also means that about 95% of all C.I.s constructed contain the true population proportion/mean, and about 5% do not TERM 8 Determining z DEFINITION 8 95% C.I. : z = 1.96 (memorize) For others: use at least 5 decimalsP (z >= ?) TERM 9 Valid Confidence Interval for proportions DEFINITION 9 Random sampleWe need np> 15 We need n(1-p) >15 TERM 10 Confidence level DEFINITION 10 Increasing level of confidence (z) widens the intervalDecreasing level of confidence (z) shortens the interval TERM 21 Hypothesis testing for proportions DEFINITION 21 H0: p=p0Ha: p <,>,=/z=p-hat - p0 divided se TERM 22 Hypothesis testing for means DEFINITION 22 H0: m=m0Ha: m <,>, =/t= x-bar - m0 divided by se TERM 23 Assumptions for Testing proportions DEFINITION 23 categorical datarandom samplesindependent samplesnp0> 15n(1-p0)> 15 TERM 24 Assumptions for Testing means DEFINITION 24 quantitative variablerandom sampleindependent samplesn> 30population's normal TERM 25 Type 1 error DEFINITION 25 reject the null when in fact you shouldnt have: it was actually the true conclusionConcluding the alternatives true when really the null is true TERM 26 Type 2 error DEFINITION 26 fail to reject the null when in fact you should have: the alternative was the correct oneConcluding theres no sufficient evidence to contradict the null, when in fact the alternative is true
