1. 1. When I give you the signal, you will have 10 seconds to look at a slide and make a guess as to the average number of m&m’s per pile. Do not use pencil or paper… just guess.

7. On Word Document

9.  Population-entire group of individuals we want information about.  Sample-part of the population to represent the population Population Sample

10.  Observational  To gain information w/out influence  Experiment  Imposes some treatment on individuals to observe response.  Use for cause and effect

11.  Sampling  Used to study part of a population to gain information of the whole population  Census  Attempts to contact every individual in the population.

12.  Voluntary response  People choose to participate  Extremely Biased  “bad design”  Convenience Sample  Based on easy access with out looking at representation of the whole population ▪ Example: You want to know if Kimball students like Math so you ask your math class.  “bad design”

13.  Exercise 5.1-5.8

14.  Simple Random Sample (SRS)  Random, everyone has a chance of being picked  This is a good Sampling method  Stratified Random Sampling  Used when you want groups to be equally represented.

15.  Random, everyone has a chance of being picked  Step 1: Label: Assign an numerical value to all the individuals  Step 2: Random Assignment ▪ Use the random number table (Table B) ▪ Random number generator (using the calculator) ▪ Math  PRB  #5:RandInt  enter  (1,33) ▪ Seed  5  rand  Seed #, store, math, PRB, option 1:rand

16.  Stratified Random Sampling is NOT SRS  Step 1: Separate the population into similar groups called strata ▪ For equal representation  Step 2: SRS each strata, these SRSs form your sample  Choose strata based on facts known before the sample is taken  Ex: A population of election districts might be divided into urban, suburban, and rural strata.  Every group is represented.

17.  Randomly choose stage 1 strata  Random States in the country  Randomly choose stage 2 strata  Random cities in the states  And so on until you get your sample size.

18. Every 5 th person to walk by is interviewed

20.  Exercise 5.9-5.11

21.  Undercoverage  A group of the population is left out  If you use a phone directory to get a sample. You miss out on…  Nonresponse  No answer, do not mail back etc.  Left out of the representation  Response Bias  Participants are not telling the truth  Wording of questions

22.  We want to make inferences about the population as a whole population.  We cant afford to talk to everyone.  Note: Two samples following the same design will give you different results. Each one is an estimate of the population.

23.  Large random samples give more accurate results than smaller samples.

24.  Read the summary on Pg.285  Exercise 5.19-5.29odd, 26  Plan your Data Collection Sample  You need to write your plan on a binder paper ▪ Goal: Describe Population and purpose of survey. ▪ Sample: State Sampling Design, size and plans for implementation. ▪ Foreseen Bias: What are they, Give details on how they apply (ex: undercoverage-who was left out), how do they impact your results.  Turn in raw data  Display data visually and Describe  Summarize your experience collecting the data ▪ Cautions experienced- restate the predicted and additional ones. ▪ Any surprises  Due Thursday

26.  Read the summary on Pg.285  Exercise 5.19-5.29odd, 26  Start your chapter 5 summary  You may use diagrams, visuals, bullet points  You may not just copy down a list of definitions