1. Graphs that Enlighten and Graphs that Deceive Chapter 2 Section 4

2. Types of Graphs ●Scatter plot (Scatter Diagram) ●Time Series Graph ●Dot plots ●Stem-plots ●Bar Graphs ●Pareto ●Pie Charts ●Frequency Polygons ●Ogive ●Pictographs

3. Graphs That Enlighten

4. Scatter Plot A scatter plot is a plot of paired (x, y) quantitative data with horizontal x- axis and vertical y-axis. used when there is a correlation between the variables.

5. Time Series Graph A time-series graph ia a graph of time series data, which are quantitative data that have been collected over different points in time, such as monthly or yearly.

6. Dot-plots A dotplot consists of a graph in which each data value is plotted as a point (or dot) along a horizontal scale of values. Dots representing equal values are stacked.

7. Stem-plots A stemplot (or Stem-and- leaf plot) represents quantitative data by separating each value into two parts: the stem (such as the leftmost digit) and the leaf (such as the rightmost digit).

8. Bar Graphs A bar graph uses bars of equal width to show frequencies of categories of Categorical (or Qualitative) data.

9. Pareto Graphs This is similar to a Bar Graph, but there is one stipulation/condition the data be arranged in descending order.

10. Pie Graph A pie chart is a graph that depicts categorical data as slices of a circle, in which the size of each slice is proportional to the frequency count for each category.

11. Frequency Polygon Frequency polygons are similar to histograms but they use line segments and have points plotted at the class midpoints.

12. Ogive An ogive (pronounced “oh-jive”) is a line cummulative line graph or frequency polygon.

13. Graphs That Deceive

14. Non-Zero Axis Always examine a graph to see whether an axis begins at some point other than zero so that differences are exaggerated.

15. Pictographs When examining data depicted with a pictograph, determine whether the graph is misleading because objects of area or volume are used to depict amounts that are actually one-dimensional.

16. Conclusion Describe – Graphs should be descriptive. Explore – Look for features that are useful in the graph. Compare – Make several different graphs and compare the results.