collier

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1. Raw scores
they are meaningless because we dont know whats good or bad, high or low
2. Relative scale
• most test scores are judged on a relative scale
• relative to other test takers
3. Summary statistics
• about summarizing single variables
• focus on quantitative (numerical)variables
• start with a "bag of data" (collection of numbers)
• consists of one or (usually) more variables
4. what does summarizing mean
• making information more concise (shorter)
• summarizing depends on the sample size (N)
• if N is large, we need to be very concise
• if N is small, we can be less concise (more complete)
5. Sorting
• the simpliest summary technique is to sort the data
• works with small sets of numbers
• easier to see the distribution when the data are sorted
• no information is lost; the presentation is merely simplified
6. Histogram
• a bar graph of a grouped frequency distribution of quantitative variable
• the apperance of a histogram can vary depending on how many categories you use
7. how to create a histogram
• create categories or groups of bins
• count the number of people or items in each group
• make a bar graph, one bar for each group
8. Frequency polygons
• the same as histograms, but midpoints connected by lines, rather than using bars
• not used very much
9. raw frequencies
• counts
• are the original numbers
10. relative frequencies
• the numbers divided by N (the total)
• percentages are the same relative frequency, except with the decimal point shifted over two places
11. Symmetrical
• left side is the mirror image of the right side
• many distributions are symmetrical
12. Shapes of distributions
• Symmetrical
• Uniform
• Bell-shaped
• Floor and Ceiling effects
• Skewed
• Bimodal
13. Uniform
• equal probabilities in all categories
• uniform distribution is symmetrical
• bars are close together in uniform
14. Bell-shaped
• most common
• another examole of a symmetrical distribution
• bars are close togther in a bell shape
15. Floor effects
• there is a lower limit to the possible numbers
• usually this is 0
• examples: incomes, which generally cannot be negative
16. ceiling effect
an upper limit to the possible numbers
17. Skewed
• to the right (positively skewed)
• to the left (negatively skewed)
• skew us frequentky due to floor and ceiling effects
18. Bimodal
• two humps or central points
• like two bell shaped put together
19. Boxplots (or box-and-whisker plots)
• includes median (a small square)
• outliers (small circle)
• non-outlier range (in the shape of a capital I)
• and the percentage (a big box)
20. measures of central tendency
• these measure where the "middle" or "center" is, or where most of the action is in the distribution
• includes the mean, median, and mode
21. measures of dispersion or variability
theses measure how spread out the data are
22. mean
• arithmetic average- add them up and divide by N
• most sensitive to outliers
23. median
• middle-most number (same as the 50th percentile)
• if there is an even amount of numbers, average the middle two
• sort the numbers first
• less sensitive to outliers
24. mode
• the most frequently occuring number.
• the hump in the histograms
• the only measure that works with qualitative data
• the only measure of central tendency where there can be two (eg. bimodal)
25. when a distribution is symmetrical and bell-shaped
the mean median and mode are the same
26. when distributions are skewed
mean, median, and mode are separate
27. measures of dispersion of variability
• these measure how spread out the data are
• a data set: 3 3 3 3 (0 variability)
• another data set: 1 2 3 4 5 (medium variability)
• another data set: -1 1 3 5 7 (larger variability)
28. Ordinal measures of variability
• these depend only on the order of the numbers
• range, interquartile range, and semi-interquartile range
29. range
highest to lowest
30. interquartile range
• chop off the top 25% (upper quartile)
• chop off the bottom 25% (lower/bottom quartile)
• take the difference
31. semi-interquartile range
half of the interquartile range
32. quantitative measures of variability
• these are based on the actual numbers, not just their orders
• variance and standard deviation
33. variance
average squared deviation from the mean
34. Standard deviation
square root of the variance
35. Norms
• are summary statistics of test results-they tell us what is "normal" or average
• we can tell how far an individual score is from average using summary statistics
• Z scores are commonly used
 Author: brittanyball42 ID: 177812 Card Set: collier Updated: 2012-10-15 18:43:46 Tags: chp Folders: Description: chapter 4.1 Show Answers: