1. Sampling Techniques

2. Simple Random Sample Keep Your Index Card Number On You Table 1 – Random Numbers 9263078240192679545753497238943770879862 7944578735715494484326104673180070134986 5965471966273865000405358940312928118544 3152449587766123978913537480865948360680 0634876938903795130255887710150920979157 The Winners Are!!!!

3. When you choose members of a sample, you should decide whether it is acceptable to have the some population member selected more than once. If it is acceptable, then the sampling process is said to be with replacement. If it is not acceptable, then the sampling process is said to be without replacement. Does Somebody Win More Than Once???

4. Members of the population are divided into STRATA Characteristics???? Separate into two subsets – Gender Hand out Second Set of Index Cards Same number of Ladies and Gentlemen are chosen!!

5. Members of the population are divided into STRATA Characteristics???? Separate into three subsets – Low, Medium and High Income Hand out Third Set of Index Cards Same number people with different incomes are chosen!!

6. Divide Population into groups called CLUSTERS Do you all live in Montville Township?? Section of in to different region of Montville Township. I will choose one of the clusters as my sample. It is important to make sure that the clusters have similar characteristics!!

7. Back to One Index Card!! Everyone get in order!! Choose a number between 1 and 6, for our regular intervals It is the easiest sample but it should be avoided do to regular patterns.

8. Takes members of a population that are available. I would like do a survey To monitor how students feel when they do too much math work. Is any one available to do extra Math Homework??? Leads to a Biased Study!!!

9. 1.) Simple Random Sample 2.) Stratified Sample 3.) Cluster Sample 4.) Systematic Sample 5.) Convenience Sample

11. Sometimes it is possible to collect all the data for a given population. Such as the ages of the 50 most powerful women in the world in 2012. 26, 31, 35, 37, 43, 43, 43, 44, 45, 47, 48, 48, 49, 50 51, 51, 51, 51, 52, 54, 54, 54, 54, 5, 55, 55, 56, 57, 57, 57, 58, 58, 58, 58, 59, 59, 59, 62, 62, 63, 64, 65, 65, 65, 66, 66, 67, 67, 72, 86 Researchers usually need sample data in order to analyze populations

12. Frequency Distribution Histogram ClassFrequency 26 – 342 35 – 435 44 – 5212 53 – 6118 62 – 7011 71 – 791 80 – 881

13.  Add them all and divide by 50  Oldest age – youngest age

14. Grouping Data into Intervals called Classes And forming a Frequency Distribution

15. ClassFrequency, f 1 – 55 6 – 108 11 – 156 16 – 208 21 – 255 26 - 304

16. ClassFrequency, f 1 – 55 6 – 108 11 – 156 16 – 208 21 – 255 26 - 304 Lower Class Limit – least number that can belong to the class, Example: 1, 6, 11, 16, 21, 26 Upper Class Limit – greatest number that can belong to the class Example: 5, 10, 15, 20, 25, 30

17. The Range is the difference between the maximum and minimum data entries. Class width are the intervals, the distance from the upper and lower limits of a class.