Scatter plots and time series plots discussed in another chapter.
Stem and Leaf Plots
Each number split into a stem and a leaf.
Similar to a histogram, retains original data values, and allows sorting of data.
Example:
Small data set: 26, 21, 25, 25, 26, 27, 28.
Stem for 26 is '2', leaf is '6'.
Leaves are written in numerical order.
Key Points:
Use rightmost digit as leaf; first digit as stem.
Key interpretation is crucial (e.g., 10/2 could mean 102 or 10.2).
Ensure no gaps (e.g., write '13' stem even if no data for 130-139).
Visual resemblance to a histogram when viewed sideways.
Practical use mainly for small data sets or quick pattern identification.
Dot Plots
Plots each data entry above a horizontal axis.
Example:
Horizontal axis from 20 to 45, dots placed for each data value.
Stack dots for repeating values.
Practical use is limited in real-world applications.
Identifies outliers easily (e.g., 145 as an outlier in text message data).
Pie Charts
Used for representing qualitative data as a whole.
Circle divided into sectors representing categories, proportional to frequency.
Example:
Degrees conferred in thousands (associates, bachelors, etc.).
Use central angle and relative frequency to construct pie chart.
Calculate angle by multiplying 360 degrees by category's relative frequency.
Relative frequencies often shown as percentages for clarity.
Can be created in Excel and StatCrunch.
Pareto Charts
Vertical bar graph with bar height representing frequency or relative frequency.
Bars arranged from tallest to shortest (left to right).
Deals with categorical data.
Example:
Leading causes of death in the U.S. organized from highest to lowest frequency.
Can be created in StatCrunch and Excel.
Conclusion
While some graphs like stem and leaf and dot plots are less common in professional settings, they are useful for educational and small data set purposes.
Pie and Pareto charts are more commonly seen in professional and real-world applications.