2. Graphing Data: Introduction to Basic Graphs Grade 8 M.Cacciotti

3. Objectives Why do anthropologists use graphs? Different types of graphs Uses of these graphs Components to graphs How to graph data Graphing your own data

4. Why do anthropologist graph data? Anthropologists use graphs primarily to provide quantitative data. Quantitative data is useful to provide an object to biases for evaluating claims. Easier to Compare data Easier to Sort data Graphs are great because they communicate information visually. For this reason, graphs are often used in newspapers, magazines and businesses around the world.

5. What are the different Types of Graphs?

6. Circle Graph A circle graph is divided into fractions that look like pieces of pie, (sometimes called a pie chart)each of these pieces represents a fraction of a whole. The circle of pie charts represents 100%. The circle is subdivided into slices representing data values. The size of each slice shows what part of the 100% it represents.

7. Circle Graph Uses Pie charts can be used anytime you want to show what percent a particular item represents of a data series such as: –A baseball player's batting average can be shown with a pie chart as it represents the percentage of hits when compared to his total number of at bats for a season. –Time spent in the shower

8. Making a Circle Graph When constructing a circle graph, follow the steps below (NOTE: If the data is not already in a table, put it into tabular form.) Is the Data Suitable: Determine if there is a "whole" for the data. Then determine what the different parts, or data groups, of the whole are. Calculate Percentages: For data that is not already given as a percentage, convert the amounts for each part, or data group size, into a percentage of the whole. (NOTE: If you need review on how to convert parts of a whole into a percent, you should review Book II of this series.) Draw the Graph: Draw a circle and draw in a sector for each data group. Try to make the sector sizes look as close to the percentage of the circle as the percentage of the data group. Title and Label the Graph: Label the sectors with the data group name and percentage. Then add a title to the graph. This is the same as the title of the table.

9. Bar Graph A graph consisting of parallel, usually vertical bars or rectangles with lengths proportional to the frequency with which specified quantities occur in a set of data. Also called bar chart.

10. Uses for Bar Graphs There are many characteristics of bar graphs that make them useful. Some of these are that: They make comparisons between different variables very easy to see. They clearly show trends in data, meaning that they show how one variable is affected as the other rises or falls. Given one variable, the value of the other can be easily determined. Zombie Apocalypse Objects by Usefulness.

11. Making a Bar Graph Use graph paper (1) Choose the size graph paper that best fits the data Number the Y-axis (the vertical one)- Dependent Variable (2) Always start numbering a bar graph at zero (3) Only number as high as your highest value (if the highest value is 18, don’t number to 100!) (4) Line up the numbers on the lines, not in the spaces (5) Evenly space out the numbers (number by 1’s, 2’s, 5’s, etc.) to fill up the page (don’t squeeze your graph into one corner of the paper!) Draw the bars on the X-axis (the horizontal one)-Independent Var. (6) Make all bars the same width (7) Evenly space out the bars (they should not touch) (8) Label what each bar represents (9) Color in or shade the bars differently Label the graph (10) Put a label on the X-axis to tell what all of the bars represent (hobbies, months, types of plants, etc.) (11) Put a label on the y-axis to tell what the numbers represent (# of people, # of days, height of plants, etc.) == Make sure you include the proper unit (height of plant in inches, temperature in degrees Celsius, etc.)

12. Histogram The histogram is a summary graph showing a count of the data points falling in various ranges. The effect is a rough approximation of the frequency distribution of the data. The groups of data are called classes, and in the context of a histogram they are known as bins, because one can think of them as containers that accumulate data and "fill up" at a rate equal to the frequency of that data class. Histogram Group Count 0 - 91 10 - 192 20 - 293 30 - 394 40 - 495 50 - 594 60 - 693 70 - 792 80 - 892 90 - 991 Frequency Table:

13. Uses for a Histogram Histograms are useful data summaries that convey the following information: The general shape of the frequency distribution (normal, chi-square, etc.) Symmetry of the distribution and whether it is skewed The histogram of the frequency distribution can be converted to a probability distribution by dividing the tally in each group by the total number of data points to give the relative frequency.

14. Making a Histogram Sounds complicated... but the concept really is pretty simple. We graph groups of numbers according to how often they appear. Thus if we have the set {1,2,2,3,3,3,3,4,4,5,6}, we can graph them like this:

15. Line Graph Line graphs compare two variables. Each variable is plotted along an axis. A line graph has a vertical axis and a horizontal axis. So, for example, if you wanted to graph Justin Bieber’s popularity over time you would put time on the horizontal, or x-axis, and popularity along the vertical, or y-axis.

16. Uses for Line Graphs Some of the strengths of line graphs are that: They are good at showing specific values of data, meaning that given one variable the other can easily be determined. They show trends in data clearly, meaning that they visibly show how one variable is affected by the other as it increases or decreases. They enable the viewer to make predictions about the results of data not yet recorded. Respect for Pluto.

17. Making a Line Graph Identify the variables –Independent Variable - (controlled by the experimenter) Goes on the X axis (horizontal) –Should be on the left side of a data table. –Dependent Variable - (changes with the independent variable) Goes on the Y axis (vertical) –Should be on the right side of a data table. Determine the variable range. –Subtract the lowest data value from the highest data value. –Do each variable separately. Determine the scale of the graph. –Determine a scale, (the numerical value for each square), that best fits the range of each variable. –Spread the graph to use MOST of the available space. Number and label each axis. –X-axis (Horizontal) – Y-axis (Vertical) Plot the data points. –Plot each data value on the graph with a dot. –You can put the data number by the dot, if it does not clutter your graph. Draw the graph. –Draw a curve or a line that best fits the data points. –Most graphs of experimental data are not drawn as "connect-the-dots". Title the graph. –Your title should clearly tell what the graph is about. –If your graph has more than one set of data, provide a "key" to identify the different lines.