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  1. Descriptive Statistics
    Summarize a data set
  2. Inferential Statistics
    • reveal the larger group through the smaller group's characteristics
    • representative samples
  3. Population
    all the members of a defined group
  4. Sample
    • any subset of a population
    • works for interval data
    • works for ratio data
  5. Qualitative variables
    differ by category rather than by amount but there are measurable differences
  6. Constants
    never vary, hold little analytical value
  7. Variables
    they have different manifestations
  8. A Research Design
    formal plan for gathering and analyzing data
  9. Independent Variable
    the variable thought to affect another
  10. Dependent variable
    the variable influenced
  11. Data Scale
    different kinds of measures gauge different qualities
  12. Measurement
    using rules to asign numbers
  13. Nominal data
    indicate a category, yields the least amount of information about an object
  14. Ordinal data
    • allows ranking
    • greater than
    • less than
    • percentile scores
  15. Interval data
    indicates degree of difference
  16. Ratio data
    • includes a zero
    • uncommon in educational measurement
  17. Interval Scale Data
    how much greater or less
  18. Descriptive Statistics
    calculated so that one can know the essential characteristics of data sets without having to refer to each individual measure.
  19. Central tendency
    most typical in a data set
  20. Measures of Central Tendency
    mode, median, mean
  21. Mode
    most frequently occuring measure in a group
  22. Unimodal
    one mode
  23. bimodal
    two modes
  24. Median
    • the point below which half the scores in the group occur.
    • isn't calculated as much as it is identified.
    • the middle most number
  25. Mean
    most commonly used measure of central tendency is the arithmetic average
  26. Outliers
    measures in a group that are so high or so low compared to the others that they will have an undue effect on the statistics.
  27. Range
    the difference between the highest and the lowest
  28. Quartiles
    Fourths of the range
  29. Interquartile Range
    stretches from the 25th to the 75th percentile in a distribution.
  30. Semi-interquartile Range
    half the interquartile range
  31. Variance
    the sum of the squared score to mean differences divided by n-1
  32. Standard Deviation
    the square root of the variance
  33. Frequency Distribution
    data are displayed so that their variety and their frequency of occurrence are both apparent.
  34. Class Intervals
    grouping the data in a frequency distribution rather than listing them individually
  35. Apparent Limits
    represented by the lowest and highest integers in the category
  36. Actual Limits
    extend the interval up and down by 1/2 point
  37. Stem and Leaf Display or Stem Plots
    liar all values according to stem (the numbers preceding the final value) and leave (the final digit)
  38. Pie Charts and Bar Charts
    used to represent proportional differences in data categories either by triangular wedges or with bars of different sizes
  39. Quadrant
    graphs are created by vertical and horizongal ines which intersect at right angles. The four sections which result are each called a quadrant.
  40. Normal Distribution
    Gaussian Distribution
    takes on the bell shape because it is symmetrical and unimodal and the standard deviation is 1/6 of the range.
  41. Point of Inflection
    a normal curve moves outward more quickly than downward occurs at +/- one standard deviation from the mean
  42. positive skew
    when the mean is larger than the median
  43. negative skew
    when the mean is smaller than the median
  44. Kurtosis
    • describes how much spread there is in a distribution
    • skewness
    • defines how bunched up the data is
  45. Mesokurtic
    • Normal distribution
    • standard deviation is about 1/6 R
  46. Platykurtic
    • distribution with too much variability
    • Standard deviation is greater than 1/6 R
  47. Leptokurtic
    • little variability
    • standard deviation is less than 1/6 R
  48. Standard Normal Distribution
    there is only one standard normal distribution
  49. Z transformation
    • scores = 0
    • standard deviation = 1
  50. Modified Standard Score
    created so that it has a prespecifiied mean and standard deviation
  51. The Distribution of Sample Means
    population based on the means of samples rather than on individual scores. it allows one to determine whether a particular sample is likely to have been drawn from the specified population which is the z test
  52. Central Limit Theorem
    A population of sample means will be normal even if the distribution of individual scores wasn't
  53. Sampling Error
    the difference between characteristics of the sample and those of the population
  54. law of large numbers
    indicates that error diminishes as sample size increases
  55. Standard Error of the Mean
    measure of variability in the distribution of sample means. It is the standard deviation of all the sample means that constitute the distribution of sample means.
  56. Statistically Significant
    that an outcome isn't likely to have occured by chance
  57. Alpha level
    • the probability of incorrectly determining a statistically significant result
    • occurs if when the null hypothesis is erroneously rejected.
    • if further testing with new data indicates that the initial finding of statistical significance was in errror, an alpha error occured with that first test.
  58. Type II or Beta error
    occurs when one incorrectly concludes that a result isn't statistically significant.
  59. Confidence Intervals for Z
    intervals within which the population mean represented by a sample will probably occur.
  60. stastistics v. parameters
    characteristics of sample v characteristics of population
Card Set
terms from the book
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