IDS 270 Chapter 3

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  1. What is an observational study?
    • It observes individuals and measures variables of interest but doesn't attempt the response.
    • Ex: A telephone survey regarding personal health
  2. What is an experiment?
    • It deliberately imposes some treatment on individuals to observe their responses.
    • Ex: Testing a drug vs. a placebo and measuring blood pressure
    • (Show 2 different ads to different people and see who buys more)
  3. What means confounding?
    • Two variables (explanatory or lurking variables) are confounded when their effects on a response variable cannot be distinguished from each other.
    • Ex: What if we saw that people who use cell phones have higher incidence of brain cancer.
  4. What means population?
    Entire group of individuals
  5. What is a sample?
    Part of the population from which we actually collect info, used to draw conclusions about the whole
  6. Call-in opinion polls?
    Ex: 67% of people who called in their opinion to ABC said that the UN should not continue to have its headquarters in NY.  
    Representative for US?
    • No
    • People who spend time/ money to call aren't representative of US population.
    • Voluntary Response Sample
  7. Convenience Sampling
    • Picking the sample based on the fact that the individuals are convenient to get to.
    • Ex: Mall Intercepts
  8. What is Bias?
    The design of a study is biased if it systematically favors certain outcomes.
  9. Voluntary response sampling?
    people pick themselves for the study
  10. Simple Random Sample?
    A SRS of size n consists of n individuals from the population chosen in such a way that every set on n individuals has an equal chance to be the sample actually selected.
  11. Stratified Random Sample?
    • To select a SRS, first divide the population into groups of similar individuals, called strata. Then choose a separate SRS in each stratum and combine these SRS to form the full sample.
    • Ex: Stratifying radio stations by type of music played and then sampling the songs from a sample of the stations in each strata.
  12. Multi-Stage Sampling?
    • =stratified sample where we stratify on the physical location of who or what we are studying.
    • Ex: Stratify cities, sample some cities, sample some blocks within the selected cities, then sample households within the block. *(we don't have to send pollsters to every city, neighborhood).
    • Current population Survey=MSS
  13. Survey?
    • Ask people questions about the topics that are studied.
    • Ex: Do you like the ad for Mc Donald's that is running currently better than ads run last month?
  14. Subjects?
    The individuals studied in an experiment are often called subjects, especially if they are people.
  15. Factors?
    The explanatory variables in an experiment are often called factors.
  16. Treatment?
    is any specific experimental condition applied to the subjects. If an experiment has several factors, a treatment is a combination of a specific value (level) of each of the factors.
  17. Completely Randomized Design?
    All the subjects are allocated at random among all the treatments.
  18. Statistical Significance?
    An observed effect so large that it would rarely by chance is called statistically significant.
  19. Double Blind?
  20. Matched Pair Design:
    • Match subjects who are alike in ways that are likely to influence the response.
    • Ex: Current weight in weight-loss drug experiments
    • Then randomly assign one matched subject to one group (control group) and the other to another group (the group receiving the drug)
  21. Block Design?
    Is a group of subjects that are known before the experiment to be similar in some way expected to affect the response to the treatments. The random assignment of individuals to treatments is carried out separately within each block.
  22. 3.3 Towards Statistical Infernce
  23. Parameter?
    Is a number that describes the population. A parameter is a fixed number, but in practice we do not know its value.
  24. Statistic?
    Is a number that describes a sample. The value of a statistic is known when we have taken a sample, but it can change from sample to sample. We often use a statistic to estimate an unknown parameter.
  25. Sampling Distribution?
    The SD of a statistic is the distribution of values taken by the statistic in all possible samples of the same size from the same population.
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IDS 270 Chapter 3
2014-02-04 20:12:57
IDS 270

IDS 270
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