Graphing data allows you to visualize relationships between variables and gain additional interpolated and extrapolated data points. Key rules for graphing include labeling the x- and y-axes with units, titling the graph, numbering axes correctly, plotting data points, and connecting them with a smooth curve or line of best fit. Sample data sets are provided to illustrate graphing height versus number of boxes or lamps.

1. Warm - Up Write the significant figures and convert into scientific notation for each of the following: 54.30 4 sig figs 5.430 x 10 1 0.00230 3 sig figs 2.30 x 10 -3 1000.00 6 sig fig 1.00000 x 10 3

2. 1-7: Presenting Data Organize and analyze data using tables and graphs. Determine type of graph to use.

3. Why do we graph data? To show the relationship between the graphed variables. (Without calculations) To gain interpolated and extrapolated data. “ inter” – in between data points. “ extra” – outside of data points.

4. Graphing is NOT: Easier – Quitting after data collection is easier than graphing the data! More visual – A data table is also a visual! More organized – A data table is organized, by its very design!

5. Rules for Graphing Label x and y axes . Include units. Title your graph. (y vs. x!) Number axes correctly. Plot data with a fine point Connect data points - smooth curve or line of best fit.

7. Sample data for graphing Height vs. # of boxes # of boxes height (m) 1 0.5 2 1.0 3 1.5 4 2.0 5 2.5 6 3.0 Height vs. # of lamps # of lamps height (m) 1 0.4 2 1.0 3 1.3 4 2.1 5 4.1 6 4.5

8. Interpreting the Graphs Which graph would give more reliable interpolated and extrapolated data? If I had 7.5 m of stacked boxes, how many boxes would I have? Approximately how tall would a stack of 7 lamps be? How many boxes could I stack in a room with a 4 m ceiling?