1. Chapter 2: Organizing Data

2. Frequency ·. How many of the data are. in a category or range ·
Frequency ·   How many of the data are in a category or range ·    Just count up how many there are

3. Notation: n  number in sample x  number in a certain category

5. Frequency Distribution. Counting how many of the
Frequency Distribution Counting how many of the data are in various ranges or categories

10. Histogram A bar graph that shows a frequency distribution

12. Types of distributions

13. Uniform Distribution ·. All ranges or categories. have nearly the same
Uniform Distribution ·  All ranges or categories have nearly the same value ·   a.k.a. “Rectangular” distribution

16. Things that should be approximately uniform: ·. Rolling one die ·
Things that should be approximately uniform: ·  Rolling one die ·   Birth of babies on different days of the week

17. Skewed Distribution ·. Top-heavy or bottom-. heavy ·
Skewed Distribution ·   Top-heavy or bottom- heavy ·     More data at one end than the other

20. Things that are likely to be skewed ·. Grades in a college class ·
Things that are likely to be skewed ·   Grades in a college class ·     Incomes of people who own stocks

21. Normal Distribution ·. Big in the middle, small at. the sides ·
Normal Distribution ·   Big in the middle, small at the sides ·    Makes a mirror image

22. · a.k.a. “Symmetrical” distribution · a.k.a. “bell curve”

26. ·. Normal distributions are. the best distributions for
·   Normal distributions are the best distributions for statistical purposes ·   In a large population, virtually any characteristic will take on an approximately normal distribution.

27. Bimodal Distribution ·. 2 “humps” ·. More than one most
Bimodal Distribution ·   2 “humps” ·     More than one most common value (or range)

30. ·. Statistics that typically. have different values for
·   Statistics that typically have different values for men and women (such as sports statistics) often form bimodal distributions.

31. Other terms used when organizing data:

32. Cluster ·. a number or range where. there is a lot of data ·
Cluster ·   a number or range where there is a lot of data ·   the “humps” in a normal or bimodal distribution ·   These are of interest when we are looking for trends.

33. Gap · a range where there is no data (or sometimes very little data)

34. Outlier ·. A piece of data that lies. outside of the main body
Outlier ·  A piece of data that lies outside of the main body of the data ·   Something much bigger or much smaller than the rest

35. ·. An “exception” to the rule ·. There is always a gap
·    An “exception” to the rule ·   There is always a gap between an outlier and the rest of the data

36. · In analyzing data, we look for reasons to explain gaps and outliers.

37. COMMON WAYS OF ORGANIZING DATA

38. · Bar Graph o Shows differences in numbers by category

39. ·. Pareto Chart. o. a special kind of bar. graph that organizes
· Pareto Chart o    a special kind of bar graph that organizes data (which must combine to make a whole) from largest to smallest to make it easier to compare things.

41. o This makes it easier to spot categories with the most data.

42. · Pictograph or pictogram o    Uses pictures of objects to approximate a bar graph

43. o. While pictographs can. be fun to look at, be. careful that the
o    While pictographs can be fun to look at, be careful that the information is still clearly communicated.

44. ·. Circle Graph. o. Shows PERCENT. (relative frequency) in
· Circle Graph o   Shows PERCENT (relative frequency) in different categories, by dividing a circle into angles.

45. o. The parts must. combine to make a. whole. o. Sometimes circle
o   The parts must combine to make a whole. o   Sometimes circle graphs will show raw numbers, but they are designed to show percents.

48. o A doughnut is a variation on the same idea.

49. o. You can figure out how. many degrees are in. each angle by taking
o   You can figure out how many degrees are in each angle by taking the percent X 360o.

50. o. A divided rectangle. (sometimes in the form. of a thermometer) also
o   A divided rectangle (sometimes in the form of a thermometer) also accomplishes the same purpose.

53. ·. Line Graph OR Time. Plot. o. Also called a “time
· Line Graph OR Time Plot o   Also called a “time plot” or “time series graph” o   Shows how a variable changes over time.

56. ·. Ogive. o Line graph that. shows CUMULATIVE. frequency distribution
· Ogive o    Line graph that shows CUMULATIVE frequency distribution (the grand total of everything up to a certain date)

57. Percentage of Children Who Have Had Some Form of Formal Schooling at Different Ages

58. o. The percentage. always grows,. because you take what
o   The percentage always grows, because you take what you had before and add onto it. o   So the line will always go up or stay the same.

59. Public Buildings in the United States Fully Compliant with the Americans with Disabilities Act

60. o. Usually levels off at the. top. o. Often approaches, but
o   Usually levels off at the top. o    Often approaches, but rarely equals 100% (or the total number in the group)

61. Other things you might use an ogive for: •. Percent of babies who
Other things you might use an ogive for: • Percent of babies who have spoken their first word by different ages

62. •. Number of people who. have seen an. advertisement that was
• Number of people who have seen an advertisement that was first introduced during the Superbowl after various amounts of time

63. •. Number of homes that. have air conditioning. turned on when the
• Number of homes that have air conditioning turned on when the temperature reaches different levels • Percent of people who have ever had sexual relations by different ages

64. When you make a graph …

65. ·. You should include a title. or explanation of the. graph’s purpose
· You should include a title or explanation of the graph’s purpose. · You should choose an appropriate type of graph for what you want to display.

66. ·. You must include a scale. and legend. ·. The scale must go in even
· You must include a scale and legend. · The scale must go in even intervals.

67. ·. Bar and line graphs should. always start at zero (or
· Bar and line graphs should always start at zero (or indicate 0 if both positive and negative numbers are possible). Sometimes for practical reasons you must show a break, but realize this is always deceptive.

68. Categories being. compared should be of. comparable size. ·
Categories being compared should be of comparable size. · For instance, if you use age groups, you should go in even intervals.

69. Percentages on circle. graphs should add up to. 100%. ·
Percentages on circle graphs should add up to 100%. · Categories can’t overlap and must account for everything.

70. · Pictographs should include pictures that are the same size.

71. · You should avoid 3-D graphics, which magnify differences in size.

72. ·. Make sure your graph. shows only the. information—not
· Make sure your graph shows only the information—not extraneous or misleading details.

73. Examples of misleading graphs:

74. · Using the wrong type of graph

75. · Bar or line graphs that don’t start at 0 or have an even scale

82. · Pictographs with two- dimensional figures

84. · Graphs with misleading 3-D graphics

86. · Overlapping categories

87. Stem & Leaf Plots

88. One quick way to organize quantitative data is a stem & leaf plot
One quick way to organize quantitative data is a stem & leaf plot. The plot itself approximates a histogram.

89. Stem ·. the first part of a number ·. for example, the tens in a
Stem ·  the first part of a number ·    for example, the tens in a 2-digit number

90. Leaf · the end of a number · for example, the ones in a 2-digit number

91. To make a stem & leaf plot: 1. Draw a line down the
To make a stem & leaf plot: 1. Draw a line down the middle of your paper

92. 2. Place the stems of your. numbers in order down the
2.  Place the stems of your numbers in order down the left side of the line (including any missing numbers)

93. 3. After each stem, write the leaves of the associated numbers

94. ·. Write the leaves in. order from smallest to. largest. ·
·    Write the leaves in order from smallest to largest ·    If a leaf repeats, write it more than once.

95. Example: 35, 17, 26, 39, 28, 50, 37, 21, 17, 35, 19

97. Making a stem & leaf plot ·  sorts the data from smallest to highest ·    gives you an idea of the type of distribution · shows outliers & gaps