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Statistical Reasoning for everyday life

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{ Line charts help us to see increasing and decreasing trends.} Example: ... 3.2 Picturing Distributions of Data. HW: pg 110 # 1, 5 14 all, 19, 21, 25 ... – PowerPoint PPT presentation

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Title: Statistical Reasoning for everyday life


1
Statistical Reasoningfor everyday life
  • Intro to Probability and Statistics
  • Mr. Spering Room 113

2
3.2 Picturing Distributions of Data
  • Distribution refers to the way in which values
    are spread over all possible values. We can
    summarize a distribution in a table or show a
    distribution visually with a graph.
  • i.e. bar graph, histogram, pareto chart, dot
    plot, pie chart, stem-and-leaf plot, line chart,
    time-series diagram, scatter plot, and
    box-whisker plot (review in section 4.3)

3
3.2 Picturing Distributions of Data
  • (Crucial Components) Important Labels for Graphs
  • Vertical scale numbers along the vertical axis
    should clearly indicate the scale. The numbers
    should line up with the tick marks the marks
    along the axis that precisely locate the
    numerical values.
  • Horizontal scale the categories should be
    clearly indicated along the horizontal axis (Tick
    marks may not be necessary for qualitative data,
    but should be included for quantitative data.)
  • Vertical axis title Include a title that
    describes the variable shown on the vertical axis
  • Horizontal axis title Include a title that
    describes the variable shown on the horizontal
    axis
  • Title/caption and legend (key) the graph should
    have a title or caption that explains what is
    being shown, and if applicable, lists the source
    of the data. If multiple data sets are displayed
    on a single graph, include a legend or key to
    identify the individual data sets.

4
3.2 Picturing Distributions of Data
  • Bar graph is a diagram consisting of bars that
    represent the frequencies (or relative
    frequencies) for particular categories. The
    lengths of the bars are proportional to the
    frequency.
  • EXAMPLE
  • Number of police officers in Crimeville, 1993 to
    2001

5
3.2 Picturing Distributions of Data
  • Dot plot (line plot) similar to a bar graph,
    except each individual data value is represent by
    a dot or symbol.
  • EXAMPLE
  • Barley Yields, Grand Rapids

6
3.2 Picturing Distributions of Data
  • Pareto chart is a bar graph with the bars
    arranged in order according to frequency. Pareto
    charts make sense only for data at the nominal
    level of measurement.

7
3.2 Picturing Distributions of Data
  • Pie Chart (circle graph) circle divided so that
    each wedge represents that relative frequency of
    a particular category. The wedge size is
    proportional to the relative frequency and 360
    degrees. The entire pie represents the total
    relative frequency of 100.
  • Example

Music preferences in young adults 14 to 19
8
3.2 Picturing Distributions of Data
  • Histogram is a bar graph showing a distribution
    for quantitative data (at the interval or ratio
    level) the bars have a natural order and the bar
    widths have specific meaning.
  • EXAMPLE
  • Exam Scores
  • of 27 students

9
3.2 Picturing Distributions of Data
  • Stem-and-leaf plot much like a histogram turned
    sideways, except in place of bars we see a
    listing of the individual data sources or values.
    Allows us to list all data easily
  • Example

The numbers 40, 42, and 43 are from Data Set
A.The numbers 41, 45, 46, and 47 are from Data
Set B.
10
3.2 Picturing Distributions of Data
  • Line chart (line graph) shows distribution of
    quantitative data as a series of dots connected
    by lines. Each dot is the center of the bin it
    represents and the vertical position is the
    frequency value for the bin. Line charts help us
    to see increasing and decreasing trends.
  • Example

11
3.2 Picturing Distributions of Data
  • Scatter plot is a chart that uses Cartesian
    coordinates to display values for two variables.
    The data is displayed as a collection of points,
    each having one coordinate on the horizontal axis
    and one on the vertical axis.
  • A scatter plot does not specify dependent or
    independent variables. Either type of variable
    can be plotted on either axis. Scatter plots
    represent the association (not causation) between
    two variables.

12
3.2 Picturing Distributions of Data
  • Time-series diagram (plots over time) A
    histogram or line chart in which the horizontal
    axis represents time.
  • NEXT SLIDE

13
3.2 Picturing Distributions of Data EXAMPLE
Time-series diagram
14
3.2 Picturing Distributions of Data
  • Summary
  • Many different ways to display data. Remember be
    very observant, and study displays carefully for
    misleading information. Finally, make sure you
    can recognize and interpret all forms of display.

15
3.2 Picturing Distributions of Data
GOOD LUCK !!!!!!!
16
3.2 Picturing Distributions of Data
How many degrees hotter was it on Wednesday than
Thursday?
30-1020 degrees hotter
17
3.2 Picturing Distributions of Data
Data from an experiment was put into a circle
graph and a bar graph. Which set of bars could
show the same data as the circle graph?
18
3.2 Picturing Distributions of Data
A band director surveyed her students to ask them
their favorite instrument. The table shows the
results of the survey.
Which is the most appropriate graph of the
information in the table to show what fraction
of the students choose each instrument?
19
3.2 Picturing Distributions of Data
The following stem-and-leaf plot shows the ages
of the teachers at Central Heights Elementary
School. Which age group has the most teachers?
KEY 4 5 45
Teachers in their thirties
20
3.2 Picturing Distributions of Data
The graph shows the population of four towns.
  • Town A
  • Town D
  • Left out important/relevant information

21
3.2 Picturing Distributions of Data
  • HW pg 110 1, 5 14 all, 19, 21, 25
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