1. Section 2.2: More Graphs and Displays

2. Objective: To be able to create and analyze a variety of graphical displays. 5. Stem and leaf plot: a way of viewing a smaller quantitative data set in which you can still see all the observations. Stems represent on place value and increase going down. Leaves represent one place value less than the stems and increase going away from the stem. (For example, if the stems is the hundreds place then the leave unit is the 10s place. Or if the stem is the thousands place then the leaf unit is the 100s place.) Always include your leaf unit. No punctuation in this graph When needed state whether the data was rounded or truncated. It is possible to have 2 or 3 digit stems.

3. Example: Create a stem and leaf plot for the pulse rate data. Example: Create a SPLIT STEM AND LEAF PLOT for the pulse rate data.

4. Example: Create a back to back stem and leaf plot for gender. Example: Create a stem and leaf plot for the following data set. 716, 778, 883, 813, 921, 1084, 1117

5. 6. Dotplot: used with small quantitative data sets. Label the horizontal axis as a number line that spans the range of the data. Place dots above the values that correspond to the observations. Draw it accurately so that the shape is clear. Example: Create a dotplot for the pulse rate data set.

6. Qualitative Graphs: 7. Pie Chart: a method for displaying categorical data. Create a frequency table. Calculate central angles. Approximate the angle and draw the pie chart. Example: Create a pie chart for the sports team data set.

7. 8. Pareto Chart (bar chart): Used for categorical data Used with counts. Bars decrease from left to right. Bars should not touch as these are categories. (book has them touching) Example: Create a Pareto chart of the sports team data set.

8. 9. Scatterplot: Best graph for displaying paired data. Explanatory variable goes on the x-axis. Response variable on the y-axis. Label all axes, scales and title. Plot points Do NOT sort points. Example: Create a scatterplot of height and shoe size.

9. 10. Timeplot: this is a scatterplot that allows us to observe trands over time. Time on the x-axis. Connect points with segments. Describe the trend. Example: Create a timeplot for the following data set: Year:19701980199020002010 Price:42.23 44.50 44.0048.0058.75