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  1. Statistics is A branch of mathematics focused on
    • *organization
    • *analysis
    • *interpretation of numbers
  2. goal of statistics
    to organize and interpret data
  3. Characteristics or conditions that can change.
    • Variables
    • (most research begins with a question about the relationship between 2 variables for a specific group of individuals.)
  4. The entire group of individuals is
  5. examples of population
    * relationship between class size and academic performance for 3rd graders
  6. selected to represent the population
    (populations are usually so large that researchers cannot examine the entire group)
  7. measurements obtained in a study
  8. Two types of Statistical Methods
    • *Descriptive statistics
    • *Inferential statistics
  9. Organize and summarize data
    • Descriptive statistics
    • examples:
    • * tables, grapshs, average score
  10. parameter
    a descriptive value for a population
  11. Statistic
    a descriptive value for a sample
  12. Use sample data to make general conclusions about population
    Inferential Statistics
  13. 1. a sample is only a part of the whole _____
    2. sample data provide limited info about the___
    3. sample statistics are imperfect representatives of the corresponding ___ parameters
  14. the discrepancy between a sample statistic and its population parameter is called
    Sampling error
  15. 2 classifications of variables
    • 1. discrete variables
    • 2. continuous variables
  16. discrete variables
    • indivisible categories
    • examples
    • *gender
    • *car*sex
  17. infinitely dividable
    • Continuous variables
    • examples
    • *height,pain, time, weight
  18. to establish relations between 2 variables...
    • *Variables must be measured
    • *Variables must be classified into one category
  19. 2 scales of measurement
    • 1.nonimal scale
    • 2.ordinal scale
    • 3.interval scale
    • 4.ratio scale
  20. an unordered set of categories
    • Nominal scale
    • examples
    • *gender
    • *martial status
  21. an ordered set or categories
    • Ordinal scale
    • example
    • *horse races, contests with places 1st, 2nd, 3rd
  22. an ordered series of equal-sized categories
    • Interval scale
    • examples
    • *6-point likert scale (rate 1-10)
    • *IQ
  23. An ordered series of equal-sized categories
    A value of zero indicates none of the variable
    • Ratio Scale
    • examples
    • *lenth, volume
  24. 3 major classifications
    • - experiemental studies
    • -correlation studies
    • -quasi-experiemetal studies
  25. one variable is manipulated IV
    a second variable is observed for changes DV
    all other variables are controlled to prevent them from influencing the results.
    Experimental Studies
  26. what is teh goal of experimental studies ?
    and give an example?
    • to establish a cause-effect relationship between the IV and the DV
    • - i.e., does noise decrease test scores
    • amount of noise=IV
    • test scores=DV
    • environment and time = controlled
  27. observe two variables as they exist naturally..
    I.e., is high school GPA related to SAT scores?
    Correlation Studies
  28. similar to an experiment but is missing either the manipulated IV or the control necessary for a true experiment
    • Quasi-experimental study
    • - the IV is usually a pre-existing variable
    • -i.e., parent child relationship, cancer.
  29. the number of scores with a value
  30. the pattern of frequencies over different values
    frequency distribution
  31. frequency tables
    • make sense of a set of numbers.
    • show how many times a number is used
  32. bar graph.
    provide a picture of distribution
  33. line graph
    frequency polygons
  34. a frequency distribution with 2 or more high points
  35. Image Upload
  36. Negative Skew
    points to the left, peak is in the right.
  37. ceiling effects means what skew?
    and if the table was test grades what would the result tell you
    ceiling effect is a negative skew, most scores piled up at the right meaning the test was too easy.
  38. floor effect means what? and what a floor effect mean for a test?
    floor effect is a positive skew. most scores piled up at the left, meaning the test was too hard.
  39. a representative or typical value in a distribution
    Central Tendency
  40. 3 meausres of central tendency
    • 1. mean
    • 2. median
    • 3.mode
  41. of the best measure of central tendency.
    most frequently reported in research articles
    think of the mean as the "balancy point" of distribution.
  42. Middle value in a group of scores.
    half the scores are above, half the scores are below (aka the "50h percentile")
    • Median
    • - unafftected by extreme individual scores
    • - unlike the mean prefereable as a measure of central tendency when a distribution has EXTREME scores or when SKEWED.
  43. most common single number in distribution.
    IF distribution is symmetrical and unimodal ____ = the mean
    - typical way of describing central tendency of a nominal variable
  44. the second way to describe numbers
  45. 3 measures of dispersion
    • 1.range
    • 2.vairance
    • 3. standard deviation
  46. simpliest measure of dispersion. The distance from the lowest to the highest score
  47. how spreadout the scores are from the mean.
  48. another measure of variation. Roughly the average amount scores differ from the mean. used more widely than variance.
    standard diviation
  49. are standardized scores used to compare numbers from different distributions.
    describe particular scores. where a score fits in a group of scores in a distribution.
    • Z scores
    • - raw scores are meaningless.
    • -i.e., i got a score of 565 in meaningless.
    • vs, i got a z-score of 1.64
  50. z scores continued.
    the sign of the z score (- or +) indeciateds. the score is located above the mean (+). or below the mean (-).
    the value of z indicates the number of standard deviation between x and the mean of distribution.
    • -z score of 1.0 is one SD aboce the mean
    • -z score of -2.5 is two and a half SDs below the mean
    • -z score of 0 is AT the mean
  51. measure and describe the relationship between 2 variables
    • Correlation
    • - X = one score
    • -y = other score
    • pair of XYsocres is usually from the same subject
  52. descriptive statistic
    - single number (e.g. r=.78)
    - summarizes and describes a relationship
    correlation coefficient
  53. Coffee and nervousness, are correlation coefficient but they DONT ____ each other
    • need a true experiment
  54. as X scores increase, Y scores also increase
    positive linear relationship
  55. as X scores increase, Y scores decrease
    negative linear relationship
  56. as X scores increase, Y scores do NOT only increaseor only decrease.
    - at some point the Y scores change their direction of change
    • non-linear relationships
    • (curvilinear)
  57. The larger the absolute value of the correlation coefficient, the _____ the relationship
    • Stronger.
    • the sign only indicates the direction of the linear relationship, NOT the strength.
    • i.e., .78 and -.78 are strong relationships
  58. describe relationships of 2 variables in a sample luck of the draw may produce a correlation, so you'll also need statistical significance.
    correlatoin coefficients
  59. only accept a correlation as "real" if it's significiant.
    "income was related to agression (r=-.78, p<.05).
    what does this tell you...
    • that it is significant.
    • that there is less than a 5% chacne that the correlation in a population is NOT REAL
    • (which means a 95% chance that it is real)
  60. Research articles report: Correlation coefficientts : put single correlations _____
    • in text.
    • i.e., there was a significant correlation (r=.51, p<.05) between age and depression.
  61. Research Articles Report:
    Correlation Coefficients, put several correlations ____
    • in table.
    • (variables listed down left and across top)
  62. The correlation of each pair of variables is shown in tables the table is called a ____
    Correlation Matrix
  63. Correlations help in making ____
    • predictions
    • e.g., prediction college GPA from HS SAT
  64. what is the variable being predicted from
    predictor variable (X)
  65. whats the variable being predicted to
    criterion variable (Y)
  66. social scientists call prediction
    • regression.
    • - can predict using 2 scores or raw scores
  67. prediction using 2+ predictor variables is called
    • multiple regression
    • *** mutiple regression and correlation are frequently reported in research articles, so its important to have a general understanding of them.
Card Set:
2011-02-05 03:36:09

Exam Chapters 1-3
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