1. An Introduction

5.  Summarize and describe data

9.  A way of expressing knowledge or belief that an event will occur  Probability distributions ◦ Discrete  Binomial  Poisson  Hypergeometric ◦ Continuous  Normal

10.  Using the data obtained from a sample to draw inferences and apply them to the greater population

18. Qualitative Variables ◦ Attributes, categories  Examples: male/female, registered to vote/not, ethnicity, eye color.... Quantitative Variables ◦ Discrete - usually take on integer values but can take on fractions when variable allows - counts, how many ◦ Continuous - can take on any value at any point along an interval - measurements, how much © 2008 Thomson South-Western

19. For each of the following, indicate whether the appropriate variable would be qualitative or quantitative. If the variable is quantitative, indicate whether it would be discrete or continuous.

20. Whether you own a big screen television set Your status as a full-time or a part- time student Number of people who attended your school’s graduation last year

21. The price of your most recent haircut Sam’s travel time from his dorm to the student union

22.  Why do we use inferential statistics?  What risks could be associated with using inferential statistics?  What is the difference between a discrete and a continuous variable?