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18 terms

CSCC Math 135 Chapter 2

Statistics Chapter 1 Review
STUDY
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are they data errors or simply unusual data values?
Watch the outliers -
Large gaps between stems containing leaves, especially at the top or bottom, suggest the existence of
outliers
By looking at the stem-and-leaf display "sideways", we can see the ? of the data.
Distribution shape
Displays the distribution of the data while maintaining the actual data values.
Stem & Leaf Plot
Displays how a total is dispersed into several categories.
Circle graphs
Identify the frequency in decreasing order.
Pareto Charts
These graphs are useful for quantitative or qualitative data.
Bar graphs
Shows data measurements in chronological order. Data are plotted in order of occurrence at regular intervals over a period of time.
Time Series
Used for qualitative data Wedges of the circle represent proportions of the data that share a common characteristic. "Good practice" requires including a title and either wedge labels or legend.
Pie Chart
A bar chart with two specific features: Heights of bars represent frequencies. Bars are vertical and are ordered from tallest to shortest.
Pareto Chart
Used for qualitative or quantitative data. Can be vertical or horizontal. Bars are uniformly spaced and have equal widths. Length/height of bars indicate counts or percentages of the variable. "Good practice" requires including titles and units and labeling axes.
Bar Graphs
Data values that are very different from other values in the data set. may indicate data recording errors
Outliers
Might indicate that the data are from two different populations.
A bimodal distribution shape
Graphical summary of a frequency table. Find the class limits. The lower limit of the "leftmost" class is set equal to the smallest value in the data set.
Histogram
Is basically an interval on a number line.
A "data class"
The proportion of data values that fall within a class.
Relative Frequency:
The number of data values that fall within a class.
Frequency:
An interval of values. Example: 61 £ x £ 70 organizes quantitative data. organizes quantitative data. partitions data into classes (intervals).shows how many data values are in each class.
Class: