1. BIOSTAT - 1 Data: What types of data do you deal with? What do you think “statistics” means? Where do you obtain your data? What is a random variable in statistics. What is the difference in a “Quantitative Random Variable” and a “Qualitative Random Variable”?

2. BIOSTAT - 1 What is the difference in a discrete random variable and a continuous random variable? What is the difference in a population and a sample? Give some examples of a population you deal with at work. What are the characteristics of that population you are interested in?

3. BIOSTAT - 1 Give some examples of the following 4 “measurement scales”. –Nominal Scale [qualiltative, categorical, no natural order] –Ordinal Scale [qualiltative, categorical, has a natural order] –Interval Scale [quantitative, numerical, no natural zero] –Ratio Scale [quantitative, numerical, has a natural zero and the ratio of two values has meaning.

4. BIOSTAT - 1 What is statistical inference? Give some examples of how you might use statistical inference in your job. What is a simple random sample? How would you suggest we take a simple random sample? In statistics what do the symbols “n” and “N” normally mean? How does the population size affect what we find out when we take a random sample?

5. BIOSTAT - 1 Give an example of a research study? [designing sampling protocols, collecting and analyzing data, and providing valid conclusions based on the results of the analysis] Give an example of a statistical experiment (experimental design)? [observations after specific manipulations of conditions have been carried out]

6. BIOSTAT - 1 What is a systematic sample, how would you select one, and give examples. What is stratified sampling, how would you select one, and give examples. What are some ways you can foul up the sampling process?

7. BIOSTAT - 1 Scientific Method – process by which scientific information is collected, analyzed, and reported in order to produce unbiased and replicable results in an effort to provide an accurate representation of observable phenomena. Key element in statistical studies: Make observation, formulate hypothesis (research or statistical), design experiment, analyze data, reach conclusions.

8. BIOSTAT - 1 Key ways to mess up a study: –Improperly designed experiments are the leading cause of invalid results and unjustified conclusions –The accuracy and precision of the measurement is poor –Failure to randomize! –Failing to control other potential factors that affect the results

9. BIOSTAT - 1 Problems: 1, 2, 3, 5, 6, 7, Congratulations: You are almost finished with this course. Next up: –Chapter 2 –Chapter 3 (primarily section 3.5)