2. Why do we analyze data?  To determine the extent to which the hypothesized relationship does or does not exist.  You need to find both the central tendency and the variance within the data.

3. Qualitative VS Quantitative Data  First, you need to determine if your data is qualitative or quantitative.  Qualitative data is based on observations and descriptions, for example color or texture  Quantitative data deals with numbers and data that can be measured, for example length, weight, or speed  SO, is your data qualitative or quantitative?

4. Central Tendency  Central tendency is the central, or typical, value to a set of data.  You can measure central tendency in many ways:  Mean- the arithmetic average of a set of data, can be calculated by dividing the sum of the elements by the number of elements, is strongly influenced by extreme values  Median- the middle element in a set of data once the data has been ordered by magnitude, not influenced by one or two extreme values  Mode- the most frequent data value

5. Variance  Variance measures how far a set of numbers are spread out. A small variance indicates that the numbers are close to the mean while a large variance indicates that the numbers are spread out from each other.  Measures of Variation  Range – the difference between the greatest and least values in the set  Frequency distribution – depicts the number of cases falling into each category, used in qualitative data  Standard Deviation – measures how closely the individual points cluster around the mean

6. What Do I Choose??  Choose your numerical summaries based on this table: Type of DataCentral TendencyVariation QuantitativeMeanRange Standard Deviation QualitativeModeFrequency Distribution

7. Graphs  You need to choose the graph that best represents your data.  Types of Graphs:  Bar Graph – common way to show categorical data with a non-standard scale ( quantitative data)  Line Graph – used for continuous data with a standard scale to show the change in a variable over time  Scatter Plot – used when two measurements are made for each element in the sample, helps to determine if two characteristics are correlated

8. WHAT Do I Graph?  You should be able to graph both the central tendency and the variation in the data.  Raw data (all the trails) is generally not shown in graph form.  X-axis indicated independent variable while the y-axis indicates the dependent variable

9. Discussion of Data/ Data Analysis  You will need to describe your data in paragraph form, mainly answering the question “What does the data tell me?”  Follow these steps for your discussion of data: 1.Write a topic sentence stating the independent and dependent variables, and a reference to graphs and tables 2.Write a sentence describing the correlation between variables, if one exists. 3.Write sentences comparing the measures of central tendencies of the groups. 4.Write sentences describing the variation within the groups.

10. Additional Resources…  The following items can be found on my website, under the “GT Science Project”:  This PowerPoint  How Do I Analyze My Data? Notes sheet  The Planning Sheet for YOUR data analysis section  A SAMPLE data analysis/results section  Graphing Checklist