Random Sampling and Introduction to Experimental Design

1. Random Sampling and Introduction to Experimental Design

2. Simple Random Sample: • n measurements from a population • Population subset • Selected such that: • Every sample of size n from the population has an equal chance of being selected • Every member of the population has an equal chance of being included

3. How to select a simple random sample: • Assign an number to each child. • Use Random Number Table A13 • Pick the first 5 two digit numbers. Example

4. Simulation: • Provides arithmetic imitations of “real” situations. • Stock Exchange Problem. Sampling with replacement: Item selected for a sample is not removed

5. Other Sampling Techniques Stratified Sampling: • Groups or classes inside a population that share common characteristics (strata). A random sample is drawn for each strata. Systematic Sampling: • Elements of a population are in some order, then you select a starting point and every kth element for sampling

6. Other Sampling Techniques: Cluster Sampling: • A demographic region is divided into sections. Then you randomly select sections or clusters and every member is included in the sampling Convenience Sampling: • Results or data that is conveniently and readably obtained

7. Introduction to a Statistical Study • Basic guidelines for planning a statistical study • Identify the individuals or objects of interest • Specify the variables as well as protocols for taking measurements or making observations • Determine if you will use an entire population (use a census) or a representation sample. If using a sample, decide on a viable sampling method • Collect data. • Use appropriate descriptive statistics methods (chapters 2, 3, 10) and make decisions using appropriate inferential statistics (chapters 8-12) • Note an concerns you might have about your data collection methods and list any recommendations for future studies

8. Observation or Experiment? Observational Study: • An activity when the experimenter notes differences and their effects on the measurement Experiment: • A planned activity that results in measurements. • Treatment is deliberately imposed on the individual in order to observe change in the variable.

9. Planning and Conducting Experiments Response/Dependent Variable: • Variable to be measured in the experiment Explanatory/Independent Variable: • Variable that may explain the differences in responses Control: • Used to establish the baseline response expected if no treatment is given

10. Planning and Conducting Experiments Placebo: • A control group for some medical experiments • Looks exactly like the real medicine Randomized two-treatment experiment: • Patients assigned to the treatment and control group by random selection

11. Planning and Conducting Experiments Single-Blind: • Either the patient does not know which treatment he/she is receiving or the person measuring the patient’s reaction does not know Double-Blind: • Both the patient and the person measuring do not know which treatment the patient was given

12. Survey Nonresponse: • Selected respondents refuse to respond • Too many nonresponses can cause the study to be biased Voluntary Response: • Often over represents people with strong opinions Hidden Bias: • The way you conduct the survey many leave part of a population out

13. Results Lurking/Confounding Variable: • The effect of one variable on another can be hidden by other variables for which no data has been obtained Generalizing results: • Replication