University:
Missouri State University
Course:
MTH 343 | Foundations of Probability and Statistics for Teachers
Academic year:

2020
Views:

29

Pages:

2
Author:

Kevin Riddle

Unit 5-Binomial Chapter 18 - Sampling Distributions Day 6: Review - geometric, binomial, CLT, sampling distributions, proportions TEST TOMORROW! Take out your warm up packets.... Warm ups: MC (part 3) #25, 27, 32, 33, 34 sigma_{x} = sigma/(sqrt(n)) sigma_{x} = (10x)/(sqrt(2n)) 00000 mu_{12x} = 12(1) = 12 ( matrix 2s\\ i ,t matrix ) n = 12 G_{12x} = sqrt(12 * (0.1) ^ 2) = 0.346 sigma_{S} = 346/(sqrt(12)) = neth (13,1000, 12. Now try a. add it up! 17 b, binomiall 2929 B (10,..17) P(x = 3) = c. center 1,65 spread 1.851 / r * t(150) = 0.1511 shape approximately normal because of CLT M sigma_{pi} = sigma/(sqrt(n)) = (37Delta)/(sqrt(100)) n >= 25 mu = 60 or = 20 N(60, 20/(sqrt(100))) P(X >= 65) 006 Try Problem Hints! A N( 15, 7 , Delta7) a. Find prob, of more than 18 and less than 14 0081 P(x + 14) + P(x > 1pi) b. Find prob, between 15 and 16 5072 P(15 < x < 16) c. binomial 1139 B(12, 0.5072) 197 P(x = 4) 3. Bawah 2,000 (a) sample of size 15 having a mean greater than 10 inches because there is more variability in smaller samples, so it is more likely to happen (b) z = (7.5 - 8) 3-1666 answer: 0478 (c) Oh yeah, baby! Central Limit Theorem (CLT) says that when the sample size is more than 25, the sampling distribution is approximately normally distributed! Whoo hool