Psyc 3000 test 2!

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Psyc 3000 test 2!
2013-03-09 17:18:27
Psyc 3000

Psyc 3000
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  1. IV Examples
    • Mood when manipulated by researcher
    • Movie when selected by researcher.
  2. True IV:

    Many quasi-IVs are....
    Researcher sets or manipulates IV

    Researcher observes BUT DOES NOT MANIPULATE level

    participant variables
  3. Quasi-IV
    Researcher observes BUT DOES NOT MANIPULATE level
  4. Example of Quasi-IV
    • Mood when participant shows up for study
    • Movie when selected by participant
    • Sex of participant
  5. Cell or Condition
    A combination of IV levels

    Study of sex differences among drivers in two countries (USA & Greece)
  6. Confounding variable
    Other names =
    What do they do?
    • AKA confound, covariate, or 3rd variable
    • Affects DV. but is not an IV
    • Can bias study, lead to wrong conclusion
    • Ultimately has affect on IV

    (IV STIMULUS --> DV RESPONSE --> Confounding variable --> IV STIMULUS)
  7. Examples of covariates
  8. Whats the order
    Date -> ______ ->
    Data, statistical analysis, Information
  9. What are the two types of statistics?
    • Descriptive Statistics
    • Inferential Statistics
  10. Descriptive Statistics:
    Best way to describe a variable is?
    Summarize/Describe the data from your study (the sample)

    Goal:Try to summarize data with two numbers without sacrificing crucial data:

    • Average = Signal
    • Variability = Noise

    • Problems:
    • Information loss
    • Assumptions

    Best way to describe a variable is  by its type (nominal, ordinal, etc) and distribution
  11. Inferential Statistics:
    Are used to make predictions/inferences about the population based on the sample
  12. Average:
    Common averages:
    Single value most typical of all data

    • Mean =
    • Meadian =
    • Mode = Most freq value
  13. Mode =
    Works best for what distribution?
    Used to describe?
    Okay for what types of data?
    • -Most freq value
    • -Works best for unimodal distribution
    • -Used to describe average of nominal variable
    • -Okay for what types of data:
    • (Ordinal Interval or Ratio)
  14. Median =
    APA format =?
    • Apa = Mdn
    • Divide Data in half ( 125 )
  15. Mean =
    Used to describe which data?
  16. Mean = Best guess
    average of interval or ratio variables, but only if distribution is unimodal and symmetric (not skewed)
  17. IF distribution is unimodal and symmetric
    Mode = Mdn = M
  18. If distribution is unimodal with positive skew:
    Mode < Mdn < M if unimodal
  19. Would you report Mean, Median, or Mode?
    Eye Color
    Test Score (0-50)- Normal Distribution
    Test score (0-50)- Highly Skewed Distribution
    Temperature-- Normal Distribution
    SIze of dog (small, medium, large)
    Exam Grades (A, B, C, D, F)
    INcome under (10k, 10-20k, 20-30 etc)
    Eye ColorTest Score (0-50)- Normal DistributionTest score (0-50)- Highly Skewed DistributionTemperature-- Normal DistributionSIze of dog (small, medium, large)Exam Grades (A, B, C, D, F)INcome under (10k, 10-20k, 20-30 etc)
  20. What is mean, median, mode of
    • Mean =
    • Median=
    • Mode = 1
  21. Which would u use? Mean median mode
  22. Does average completely describe the data?
    No, because two distributions can have same average but look very different.

    Need at least one other descriptive statistic.
  23. Variation
    Aka: Dispersion/Spread
    *Single most typical difference from average

    *Need to describe how much scores differ from average (ho wmuch noise is present)
  24. IQR
    Extends from?
    Often used for?

    Variabilities:                 How to measure them?
    • Interquartile Range- Middle half of scores
    • 25th - 75th percentile
    • Ordinal Data

    • Variabilities:
    • Range = Largest datum - smallest datum
    • IQR= Q3-Q1
    • where Q3 is the median of the upper half and Q1 is the median of the lower half of data.  Q2 is the median of all data
  25. Variance =
    Squared Standard Deviation
  26. Standard Deviation =
    Know formula
    Mean deviation from M, ignoring sign (sort of)
  27. Standard Deviation
    Different Mean =
    Same Mean =
    Different Mean =
    • Different Mean = Same SD
    • Same Mean = Different SD
    • Different Mean = Different SD
  28. Descriptive Statistics to report in Method Section/Participant subsection
    • Sex: # of M & # of F
    • Age: Min, Max, and either M and SD (of symmetric) or Mdn and IQR range (of skewed)

    Other key demographics such as ethnicity if important
  29. Descriptive Statistics of DV to report in...
    • Results Section
    • If DV is nominal or ordinal with few levels:
    • Mode for each cell
    • If DV is ordinal, or interval/ratio and skewed: n, Mdn, and IQR rang for each cell

    If DV is interval/ratio and symmetric: n, M, and SD for each cell
  30. Descriptives calculate:
    M, SD, Min, and Max