STT 315 Study Guide - Midterm Guide: Confidence Interval, Null Hypothesis, Bias Of An Estimator

• School: MSU
• Department: Statistics and Probability
• Course: STT 315
• Professor: A Sinha

Document Summary

No, because the clt states that the sampling distribution of x_ is approx. normal distributed only if sample size. Will the sampling distribution of x_ always be approx normally distributed? is large enough. Sampling mean distribution finding mean: use 1 var stats = e(x)= remember =(cid:4666)(cid:4667)= (cid:3041) normalcdf=(lower, upper, , (cid:4667) invnorm(area on other side of z) Z-score of x= x / (cid:3041) as the value of n increases, the histograms become less spread out. Sample is considered large enough if n (cid:885)(cid:882) -sample size increases, the sample mean x bar estimates the population mean within retain margin of error with higher probability. Sampling distribution of p u(p )=p (p )= (cid:3017)(cid:4666)(cid:2869) (cid:3017)(cid:4667)(cid:3015) z= (cid:2926) (cid:2926) (cid:3043)(cid:4666)(cid:2869) (cid:3043)(cid:4667)/(cid:3041) sample is large enough if np (cid:883)5 & (cid:4666)(cid:883) (cid:1868)(cid:4667) (cid:883)5. Adjusted (1- ) 100% confidence interval for population proportion: p /(cid:2870) (cid:2926) (cid:4666)(cid:2869) (cid:2926) (cid:4667) (cid:3041)+(cid:2872) p =+(cid:2870)(cid:3041)+(cid:2872)