Review Day 2 May 4 th 2013. Probability Events are independent if the outcome of one event does not influence the outcome of any other event Events are.

Slides:



Advertisements
Similar presentations
Chapter 10: Estimating with Confidence
Advertisements

Chapter 8: Estimating with Confidence
Statistics 1: Introduction to Probability and Statistics Section 3-3.
Class notes for ISE 201 San Jose State University
Sampling Distributions
BHS Methods in Behavioral Sciences I
The Normal Curve and Sampling A.A sample will always be different from the true population B.This is called “sampling error” C.The difference between a.
Probability (cont.). Assigning Probabilities A probability is a value between 0 and 1 and is written either as a fraction or as a proportion. For the.
Review Measures of Central Tendency –Mean, median, mode Measures of Variation –Variance, standard deviation.
Chapter 10: Estimating with Confidence
Normal and Sampling Distributions A normal distribution is uniquely determined by its mean, , and variance,  2 The random variable Z = (X-  /  is.
Chapter 4 SUMMARIZING SCORES WITH MEASURES OF VARIABILITY.
Standard error of estimate & Confidence interval.
INFERENTIAL STATISTICS – Samples are only estimates of the population – Sample statistics will be slightly off from the true values of its population’s.
Chapter 6: Sampling Distributions
AM Recitation 2/10/11.
Chapter 6 Confidence Intervals.
6.1 What is Statistics? Definition: Statistics – science of collecting, analyzing, and interpreting data in such a way that the conclusions can be objectively.
Essentials of Marketing Research
Today’s lesson Confidence intervals for the expected value of a random variable. Determining the sample size needed to have a specified probability of.
Dan Piett STAT West Virginia University
McGraw-Hill/Irwin Copyright © 2007 by The McGraw-Hill Companies, Inc. All rights reserved. Chapter 6 Sampling Distributions.
Confidence Intervals (Chapter 8) Confidence Intervals for numerical data: –Standard deviation known –Standard deviation unknown Confidence Intervals for.
AP Statistics Chapter 9 Notes.
+ The Practice of Statistics, 4 th edition – For AP* STARNES, YATES, MOORE Chapter 8: Estimating with Confidence Section 8.1 Confidence Intervals: The.
Population All members of a set which have a given characteristic. Population Data Data associated with a certain population. Population Parameter A measure.
AP STATISTICS LESSON 10 – 1 (DAY 2)
Copyright ©2011 Nelson Education Limited The Normal Probability Distribution CHAPTER 6.
Introduction to Summary Statistics
Smith/Davis (c) 2005 Prentice Hall Chapter Six Summarizing and Comparing Data: Measures of Variation, Distribution of Means and the Standard Error of the.
Biostat. 200 Review slides Week 1-3. Recap: Probability.
Slide 1 © 2002 McGraw-Hill Australia, PPTs t/a Introductory Mathematics & Statistics for Business 4e by John S. Croucher 1 n Learning Objectives –Identify.
10.1: Confidence Intervals – The Basics. Review Question!!! If the mean and the standard deviation of a continuous random variable that is normally distributed.
February 2012 Sampling Distribution Models. Drawing Normal Models For cars on I-10 between Kerrville and Junction, it is estimated that 80% are speeding.
+ The Practice of Statistics, 4 th edition – For AP* STARNES, YATES, MOORE Unit 5: Estimating with Confidence Section 10.1 Confidence Intervals: The Basics.
Copyright © Cengage Learning. All rights reserved. 2 Descriptive Analysis and Presentation of Single-Variable Data.
Sampling distributions rule of thumb…. Some important points about sample distributions… If we obtain a sample that meets the rules of thumb, then…
Chapter 10: Confidence Intervals
Statistics Chapter 6 / 7 Review. Random Variables and Their Probability Distributions Discrete random variables – can take on only a countable or finite.
© Copyright McGraw-Hill 2004
10.1 – Estimating with Confidence. Recall: The Law of Large Numbers says the sample mean from a large SRS will be close to the unknown population mean.
Lesson The Normal Approximation to the Binomial Probability Distribution.
Ex St 801 Statistical Methods Inference about a Single Population Mean (CI)
+ The Practice of Statistics, 4 th edition – For AP* STARNES, YATES, MOORE Chapter 8: Estimating with Confidence Section 8.2 Estimating a Population Proportion.
1 STAT 500 – Statistics for Managers STAT 500 Statistics for Managers.
AP Stats Review: Probability Unit Unit #2 – Chapters 6, 7, and Section
Confidence Intervals. Point Estimate u A specific numerical value estimate of a parameter. u The best point estimate for the population mean is the sample.
+ The Practice of Statistics, 4 th edition – For AP* STARNES, YATES, MOORE Chapter 8: Estimating with Confidence Section 8.1 Confidence Intervals: The.
WARM UP: Penny Sampling 1.) Take a look at the graphs that you made yesterday. What are some intuitive takeaways just from looking at the graphs?
Sampling and Sampling Distributions. Sampling Distribution Basics Sample statistics (the mean and standard deviation are examples) vary from sample to.
Statistics and probability Dr. Khaled Ismael Almghari Phone No:
AP Stats Exam Review: Probability TeacherWeb.com 1.
Chapter 6: Sampling Distributions
AP Statistics Final Exam Review!!!!!.
Chapter 7 Review.
CHAPTER 6 Random Variables
Inference for the Difference Between Two Means
AP Stats Exam Review: Probability
Chapter 6: Sampling Distributions
Section 6-4 – Confidence Intervals for the Population Variance and Standard Deviation Estimating Population Parameters.
Chapter 8: Estimating with Confidence
Calculating Probabilities for Any Normal Variable
Estimating a Population Proportion
Section 6-4 – Confidence Intervals for the Population Variance and Standard Deviation Estimating Population Parameters.
Chapter 8: Estimating with Confidence
Chapter 8: Estimating with Confidence
Chapter 8: Confidence Intervals
Advanced Algebra Unit 1 Vocabulary
Chapter 8: Estimating with Confidence
Chapter 8: Estimating with Confidence
Presentation transcript:

Review Day 2 May 4 th 2013

Probability Events are independent if the outcome of one event does not influence the outcome of any other event Events are mutually exclusive if they cannot occur together. P(A or B) = P(A) + P(B) – P(A and B) If A and B are independent: P(A&B)= P(A)  P(B) P(B|A) = P(A and B)/P(A) The most common way to check for independence is simply to check that P(B) = P(B|A)

Review Questions 1. What is the probability? 2. What is the probability? 3. The two events are 4. What is the probability? 5. What is the probability that exactly one is defective? 1. C2. B3.D4. A5. D

Random Variables

Binomial Distribution

Geometric Distribution

Calculating Geometric Probability

Review Questions P Hint: Binomial Probability 2. Hint: Geometric Probability 3. Hint: Sum of expected sales 4. Hint: Put in L1, L2 (Stat,Cal L1,L2) 5. Hint: To add σ convert to variance Answers: cebea

Free Response P. 183 A. Describe an appropriate model for the number of defective batteries in the shipment. B. What is the mean and standard deviation? C. The consumer group has reason to believe that the rate of defective batteries is at least 5%. Based on your findings in (b), what is the probability that more than 5% of this shipment would be defective if 4% of the manufacturer’s batteries are defective?

The Normal Distribution Symmetric Highest point μ Area under curve = 1 Area on either side of μ is.5 The empirical rule: 68%, 95%, 99.7% Z score measures the distance an observation is from the mean in standard deviations.

Review Questions P Hint: Use Normal Distribution on Calculator. 2. Find the z for top 5%, then find raw score 3. Find both z scores Answers: DAB

Question 4 P. 198 A researcher notes that two populations of lab mice-one consisting of mice with white fur, and one of mice with gray fur-have the same mean weight, and both have approximately normal distributions. However, the population of white mice has a larger standard deviation than the population of gray mice. If the weights for both of these populations were plotted, how would the curves compare to each other?

Question 5 P. 198 Which of the following statements is NOT true for normally distributed data? A. The mean and median are equal B. The area under the curve is dependent upon the mean and standard deviation. C. Almost all of the data lie within 3 σ. D. Approximately 68% of all the data lies within 1 σ. E. When the data are normalized, the distribution has a mean μ = 0, σ = 1

Sampling Distributions Central Limit Theorem for the Mean Central Limit Theorem for Proportion T Distribution Chi Square Distribution

Review Questions P Which of the following statements about the t- distribution is true? 2. The bigger the n, the smaller the σ 3. This is a definition that we had 4. This check for Normality 5. Remember the mean of our sample is the same as our population. The standard deviation divide by square root of n. Answers: becac

Free Response P. 217

Estimation Confidence Intervals: Point estimate ± ME On the AP: statistic ± (critical value)(standard deviation of statistic) Interpreting: a 98% CI indicates that if confidence intervals for all possible samples of size n were constructed for the given population, 98% of the those intervals would contain the population parameter.

Steps for CI 1. Identify parameter 2. Check Conditions 3. Find critical z or t (Perform Calculations) 4. Interpret the results (Context)

Review Questions P c 2. b 3. e 4. d 5. a 6. d 7. a

8. Calculator A 9. B 10. D 11. B 12. C 13. D 14. Calculator won’t work Use formula D 15. A Calculator 2 Prop Z interval

16. Work out by hand 17. D 18. Calculator E (our answer is off b/c DF) 19. B 20. D 21. D 22. C 23. C 24. A