1. Created by Tom Wegleitner, Centreville, Virginia Section 1-4 Design of Experiments

2. Major Points  If sample data are not collected in an appropriate way, the data may be so completely useless that no amount of statistical tutoring can salvage them.  Randomness typically plays a critical role in determining which data to collect.

3.  Observational Study observing and measuring specific characteristics without attempting to modify the subjects being studied Definitions

4.  Experiment apply some treatment and then observe its effects on the subjects Definitions

5.  Cross Sectional Study Data are observed, measured, and collected at one point in time.  Retrospective (or Case Control) Study Data are collected from the past by going back in time.  Prospective (or Longitudinal or Cohort) Study Data are collected in the future from groups (called cohorts) sharing common factors. Definitions

6.  Confounding occurs in an experiment when the experimenter is not able to distinguish between the effects of different factors Try to plan the experiment so confounding does not occur! Definitions

7. Controlling Effects of Variables  Blinding subject does not know he or she is receiving a treatment or placebo  Blocks groups of subjects with similar characteristics  Completely Randomized Experimental Design subjects are put into blocks through a process of random selection  Rigorously Controlled Design subjects are very carefully chosen

8.  Replication repetition of an experiment when there are enough subjects to recognize the differences in different treatments Replication and Sample Size  Sample Size use a sample size that is large enough to see the true nature of any effects and obtain that sample using an appropriate method, such as one based on randomness

9. Identify the type of observational study(cross- sectional,retrospective, or prospective) 1. A researcher from the New York University School of Medicine obtains data about head injuries by examining the hospital records from the past five years. 2. The U.S. Labor Department obtains current employment data by polling 50,000 people this month. 3. A researcher from Mt. Sinai Hospital in New York City plans to obtain data by following (to the year 2010) siblings of victims who perished in the World Trade Center terrorist attack of September 11, 2001

10.  Random Sample members of the population are selected in such a way that each individual member has an equal chance of being selected Definitions  Simple Random Sample (of size n ) subjects selected in such a way that every possible sample of the same size n has the same chance of being chosen

11. Random Sampling selection so that each has an equal chance of being selected

12. Systematic Sampling Select some starting point and then select every K th element in the population

13. Convenience Sampling use results that are easy to get

14. Stratified Sampling subdivide the population into at least two different subgroups that share the same characteristics, then draw a sample from each subgroup (or stratum)

15. Cluster Sampling divide the population into sections (or clusters); randomly select some of those clusters; choose all members from selected clusters

16.  Random  Systematic  Convenience  Stratified  Cluster Methods of Sampling

17. Identify the type of sampling (random,stratified,systematic, cluster, or convenience. 1. A sample of products is obtained by selecting every 100 th item on the assembly line. 2. Random numbers generated by a computer are used to select serial numbers of cars to be chosen for sample testing. 3. An auto parts supplier obtains a sample of all items from each of 12 different randomly selected retail stores.

18. 4. A car maker conducts a marketing study involving test drives performed by a sample of 10 men and 10 women in each of 4 different age brackets. 5. A car maker conducts a marketing study by interviewing potential customers who happen to request test drives at a local dealership

19.  Sampling Error the difference between a sample result and the true population result; such an error results from chance sample fluctuations  Nonsampling Error sample data that are incorrectly collected, recorded, or analyzed (such as by selecting a biased sample, using a defective instrument, or copying the data incorrectly) Definitions

20. Recap In this section we have looked at:  Types of studies and experiments  Controlling the effects of variables  Randomization  Types of sampling  Sampling Errors