1.2 &1.3 Sampling Methods Objective: to distinguish between observational studies and designed experiments and to distinguish between the types of random sampling Review the statistical process difference between descriptive and inferential statistics qualitative vs quantitative data discrete vs continuous data

Ways to Obtain (collect) Data Census Existing Sources Survey Sampling or Observational Studies measuring without manipulating Designed Experiment some “treatment” is applied

Examples Rats with cancer are divided into two groups. One group receives 5 mg of a medication that is thought to fight cancer, and the other receives 10 mg. After two years, the spread of the cancer is measured. A poll is conducted in which 500 people are asked whom they plan to vote for in the upcoming election.

Sampling Goal of sampling Obtain individuals that accurately represent the population Reason for sampling Designed to eliminate bias

Sampling Styles 1. Simple Random Sample any sample of size “n” has an equal chance of being selected. 2. Stratified Sampling Simple random sample of each strata 3. Systematic Sampling every k th individual 4. Cluster Sampling all members of randomly selected sub-group 5. Convenience Sampling individuals are easily obtained

Examples To determine the average IQ of ninth-grade students, a school psychologist obtains a list of all high schools in the local public school system. She randomly selects five of these schools and administers an IQ test to all ninth-grade students at the selected schools. A member of Congress wishes to determine her constituency’s opinion regarding estate taxes. She divides her constituency into three income classes: low-income households, middle-income households, and upper-income households. She then takes a simple random sample of households from each income class. A radio station asks its listeners to call in their opinion regarding the U.S. forces in peacekeeping missions.

Assignment Due WednesdayPage odd Page , 23-30