Graphs in Science Section 1.5.

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Presentation transcript:

Graphs in Science Section 1.5

Objectives Explain what type of data line graphs can display. Describe how you determine a line of best fit or the slope of a graph. Explain why line graphs are powerful tools in science.

The importance of graphs One way to show data is in a data table. You can also show it in the form of a graph Graph: “picture” of your data

The Importance of Graphs Three types that scientists commonly use: Line graph Bar graph Circle graph We will focus on line graphs for this section

Why are line graphs useful? Line graphs are used to display data to show how the responding variable changes in response to the manipulated variable.

Plotting a Line Graph Draw the axes. Horizontal axis (x-axis) runs left to right. Vertical axis (y-axis) runs up and down. Label the axes. Don’t forget units! Create a scale Origin: where the two axes cross Coordinate a pair of numbers used to determine the position of a point on a graph

Plotting a line graph 4. Plot the data. Data Point: A point on a graph showing the location of a piece of data. 5. Draw a line of best fit Line of best fit: smooth line that reflects the general pattern of a graph Linear graph: a line graph where the data points give you a straight line 6. Add a title

Example: Data Table Volume of water (mL) Boiling Time (min) 500 7.8 1,000 16.6 1,500 26.0 2,000 33.7

Why Draw a Line of Best fit? A line of best fit emphasizes the overall trend shown by all the data taken as a whole. DO NOT zig zag them!

Slope Slope: steepness of the graph line The slope of a graph line tells you how much y changes for every change in x. Slope = rise/run = y2-y1/x2-x1

Example Suppose you chose the points (20,10) and (50,25).

Using Graphs to identify trends Nonlinear graph: a graph in which the data points do not fall along a straight line Line graphs are powerful tools in science because they allow you to identify trends and make predications.

Using Graphs to identify Trends Line graphs allow you to make predictions based on the data points you already have. Nonlinear graph types: Curved Repeating/cyclical No trend: usually means there is no relationship between the two variables