602 Set 2

  1. Population
    the class of individuals a researcher wants to generalize about.

    E.g. the population of a presidential election = eligible voters in the U.S.
  2. Parameter
    Usually a numeric fact about the population

    E.g. # of male voters in the U.S., # of democrats etc…
  3. Sample
    • part of the population
    • g. eligible voters in Hawai’i
  4. Statistic
    • a number computed from a sample
    • g. # of male voters in Hawaii
  5. When is estimating parameters valid? (First and second important)
    • When the sample represents the population
    • 2nd is sample size
  6. What methods must be used to ensure sample representativeness?
    • Probability methods must be used to ensure sample representativeness
    • Simple random sampling is the most basic probability method
  7. Simple random sampling
    drawing at random without replacement
  8. Drawing at random
    everyone in the population has an equal chance to be sampled.
  9. What are the two features shared by all probability sampling methods?
    1. The interviewer has no discretion at all as to whom they survey 2. There is a definite sampling procedure, and it involves the planned use of chance
  10. What are biases?
    Any systematic error (eg surveying every third student passing the coffee stand)
  11. Can sampling error be completely eliminated?
    No. Biases can be, sampling error cannot. Needs to be quantified
  12. What is an expected value?
    With a simple random sample, the expected value for a sample statistic = corresponding population parameter.
  13. Simultaneity
    X and Y mutually cause each other
  14. What are experiments?
    Experiments are a quantitative method to establish the effect of a presumed cause.
  15. How do randomized controlled experiments resolve the threat of simultaneity and endogeneity?
    Randomization “equalizes” subjects between conditions by sorting different types of individuals into each condition with equal probability given large N. Thus randomization eliminates “unobserved heterogeneity” (= all individual differences not measures or measurable in a study).
  16. Know how to describe one-factor between-subjects designs with two or more factors (I think he meant conditions) in writing. How are factors and IVs related?
    Factors are independent variables. Conditions = levels of an IV, values that an IV takes.
Card Set
602 Set 2
Lessons 4 & 5