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.

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?

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

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

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

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

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

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.

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