Behavioral Statistics Midterm.txt

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Behavioral Statistics Midterm.txt
2014-10-20 17:24:28
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  1. Definition
    • Numerical Summarize measure computed on data from a sample
    • Numerical Characteristics of a Sample
    • Ex: Mean, T-Test, Z-Score
  2. Definition
  3. Definition
    • A target group of participants about which the researcher will make decisions
    • Ex: OU Students, Am Citizens, 1999 Honda Civics
  4. Definition
    Population: Characteristics (3)
    • 1. Large
    • 2. Unobtainable-never can collect all data (CENSUS)
    • 3. Hypothetical-we make assumptions because 1 &2 are as well as people are always changing
  5. Definition
    Subgroup of Population

    Small group of participants from which the researcher makes decisions about the population
  6. Definition
    Random Sample
    Random Sampling eliminates biases
  7. Definition
    • Quantity or property that takes on different values
    • Continuous-infinite # of values
    • Discrete-finite # of values
  8. Definition
    Independent Variable
    variables manipulated by researchers
  9. Definition
    Dependant Variables
    behavior observed and measured
  10. Definitions
    Extraneous Variables
    • Not IV or DV but might effect the study
    • a variable we need to control
    • Ex: Gender
  11. Ways to control Extraneous Variables
    • 1 Randomize participants into groups
    • 2 Keep all participants constantion EV
    • 3 include EV in the design of experiment
  12. Definition
    Types of Experiment Designs
    • True Experiment
    • Observational Research
    • Quasi-Experiemtn
  13. Definition
    True Experiment
    • Manipulation of Independent Variable
    • Randomization of Group
    • Optional methods to control Extraneous variables
    • Causal relationship between IV and EV

    Problems:Taking it to the streets
  14. Definition
    Observational Research
    • Predictive relationships
    • Observation of prediction and criterion variable
    • No Manipulation
    • Minimal control of EV
    • Predictive relationship btwn prediction of variable and criterion variable
  15. Definition
    Quasi Experimental Design
    • Manipulation of IV
    • No Randomization
    • Some control of EV
    • degree to which we can attribulte a causal relationship depends on consideration of possible outcomes

    • 1)internal validity-applies outside the lab
    • 2)External validity-applies in the lab only
  16. Definiton
    Scale of Measurment
    • Nominal
    • Ordinal
    • Internal
    • Ratio
  17. Definition
    • Data with identity only
    • Qualitative in nature
    • Ex: Gender, religion
  18. Definition
    • N+O
    • Identity
    • Order
    • Ex:Ranking, Year in School, Scales!!!
  19. Definition
    • N+O+I
    • Identity
    • Order
    • Equal Distance on # Scale
    • Ex: Temperature, Not Scales!
  20. Definition
    • N+O+I+R
    • Identify
    • Order
    • Equal Distance
    • True point 0
    • Ex:Kelvin Temp, Height, Weight
  21. Definition
    • If Both halves of the distribution is said to be Normal Distributed
    • Departure from Symmetry is defined as Skewness
  22. Definition
    Measures of Central Tendency
    • A typical or Representative score
    • Scores that represents the middle of the distribution
    • Ex:Test scores in class, Average age
  23. Definition
    Measure of Central Tendency
    Statistics and Parameters
    • Mode:Most frequestn score
    • Median-Middle valuse in distribution-50% below/above
    • Mean-arithmetic average= Sum X/N
    • Parameter Mean µ
    • Statistic Mean= X_bar
  24. Definitions
    Measures of Variability
    • Spread
    • Dispersion of the Scores
    • EX: Variance, Standard Deviation,Range, Biased Sampled Variance
  25. Definition
    Measure of Variability
    Statistics and Parameters
    • Variance
    • Parameter = σ2
    • Statistic= S*2 and S2
  26. Definition
    Measure of Variability
    Stats and Para
    Standard Deviation
    • Standard Deviation
    • Parameter= σ
    • Statistic= S* & S
  27. Definition
    Measure of Variablity
    • Range
    • Maximize mean
    • *Point of the class*
    • Stat= obtain from sample
    • Parameter= Exists in Population
  28. Definition
    Measure of Variability
    Biased Sample Variance
    • Biased Sample Variance
    • Bias to small on average
    • Bias sample variance (s*2) average2 Deviation from mean
  29. Definition
    • Z=(x-μ)/σ
    • it is used to identify and describe the exact location of each score in a distribution.
  30. Define
    • Each X to a Z
    • Mean= Z_bar=0
    • Variance= sz*2=1
    • Standard Deviation= sz*=1
    • Transformation to Z-Score does not change the shape of the distribution
  31. Define
    Normal Distribution
    • Symmetric-same on both sides
    • Smooth
    • Unimodal-1 mode
    • 4 Bell Shaped
    • Tails of distrubution-never touch X-axis
    • Mode = Median=Mean
    • Infinite # of score values (continuous variable)
  32. Define
    The degree of linear relationship between two variables.
  33. Define
    Correlation and
    Correlation does not mean causation.
  34. Definition
    Strengh of Association
    • r = I 1 I
    • Closer to 0= Weak
    • Closer to 1 or -1 = Strong
  35. Definition
    • The area of statistics where a researcher is concerned with predicting one variable from another
    • -Describing data for two variables
  36. Definition
    • Y'= predicted score of criteron variable
    • b=slope of the line= Rise/run (Rise over Run)
    • X=score of the predictor variable
    • a= Y-intercept of the line
    • (Y=observed point, Y' what come out of formula)
  37. Definition
    Sample Space
    • Group of data points representing all possible outsomes of an experiment
    • Ex: A population of a deck of Cards
  38. Definition
    Elementary Event
    • Single member in a sample space
    • (Ace of Diamonds in a deck of cards)
  39. Definition
    • Any group of elementary events
    • Ex: Kings
  40. Definition
    # in the event divided by total # of possible outcomes
  41. Definition
    Conditional Probability
    • A probabilit of one event that is dependent of another event
    • P(A/B)
  42. Definition
    One event occuring does not change the probability of another event occuring
  43. Definition
    Multiplication (AND) Rule
    • P(A&B)= P(A) X P(B)
    • P(A&B)= P(A/B)*P(B)=P(A)*P(B/A)
  44. Definition
    Mutually Exclusive
    • When A & B do not have an elementary event in common
    • P(A&B)=0
  45. Definition
    Addition (OR) Rule
    P(A or B)= P(A) + P(B)- [P(A&B)]
  46. Definition
    Sampling Distributions
    Distribution of all possible values of a statistic, sample mean, st devi, or variance
  47. Definition
    Sampling Distribution
    sahpe of the mean is approximated by normal distribution
  48. Definition
    Sampling Distribution
    Statistics and SD
    Every statistic has a sampling distribution
  49. Definition
    Sampling Distrubution
    • 1 Pop and Param are typically unknow-we want to make decision about them
    • 2 Sample and Stats are know and stats are estimates of parameter can't say stats is = to param and make decisions directly b/c stats have variability
    • 3 Samp dis of stats is used to quantify into probability the info about variability of the stat
  50. Definition
    Central Limit Theorem
    as N (Sample size) approaches infinity, the sampling distribution of X_Bar approches normality

    N=30 is best (closest to infinity)
  51. Application/ Identification
    Statistics vs. Parameter
    (s* vs. σ)
    • Stats are used to estimate the Parameter
    • Statistics- do vary
    • Parameters-do not vary
  52. Application/Identification
    Types of Statistics (2)
    • Descriptive Statistic
    • Stat procedures used to describe a sample
    • Ex: Mean, St Devi

    • Inferential Statistic
    • Statistic procedure used to make decisions about a population based upon result from a sample
    • Ex: T-Score, ANOVA, Z-Score
  53. Application/Identification
    IV, DV, EV
    • Indepentdent Variables-One manipulated by researcher
    • Dependent Variables-Changes observed
    • Extraneous Varibles- something that effects the experiment