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# Math in science

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### Math in science

1. 1. Yes, that’s right. I know we’re in science. You still need to do math. MATH AND GRAPHS IN SCIENCE
2. 2. Estimation  An approximation of a number based on reasonable assumptions.  Everyone take a guess!  Winner gets 2 tickets!!!! Estimation! (Theartof guessing!) How many marbles???
3. 3. Accuracy  How close a measurement is to the true or actual value. Accuracy All aimed for bulls eye: all in
4. 4. Reproducible  How close a group of measurements are to each other. Reproducibility This is also reproducible. What if the darts were in a corner?
5. 5. What is this??  Neither!!! Accurate? Reproducible?
6. 6. Sig-Figs:  This measurement includes all digits that have been measured exactly plus one digit whose value has been estimated.  How many sig-figs ??? Significant Figures! My phone is 4.75 inches long! 3!!!!!
7. 7. Precision  This tells you how exact your measurement is. 4.7563 inches long Precision, precision, precision. Which is more precise?  My phone is 4.75 inches long  OR  My phone is 4.7563 inches long
8. 8. Yep, more math… almost done!! (it’s worth it, trust me)
9. 9. Graphs:  A visual representation of your data (easiest way to know what your data is “saying”)
10. 10. Origin  Where the two axes meet (where the graph starts)  Origin
11. 11. Horizontal Axis (x-axis)  Think “Horizon” as in- what you see when you watch the sunset!  This axis should be labeled with the manipulated variable. Vertical Axis (y-axis)  Think “the other one”  This axis should be labeled with the responding variable.
12. 12. Coordinates  A pair of numbers used to determine the position of a point on a graph  This is used in locations on a map as well (maps are just like graphs!!) Data Points  The point where the coordinates intersect (points of data that are plotted on a graph)
13. 13. What is it??  A smooth line that reflects the general pattern of a graph Why is it useful??  This allows you to see the general trend of the data.
14. 14. Linear Graph:  The linear graph is a result of the data points falling in a straight line naturally on the graph.  This data is very predictable Non-Linear Graph:  Any graph who’s data points don’t naturally land on a straight line.  This is most typical of graphs
15. 15. Slope:  The steepness of the graph line  The slope of the line tells you how much “y” changes for every change in “x”  To calculate the slope, use the following equation: Slope = Rise/Run
16. 16. SawTooth= BAD!!!!!  In science, we never have a broken graph (saw tooth).  This is how people make graphs look misleading!  Most people will use a saw tooth because it makes their graph look more interesting. This is why you should NOT do that! If it’s a boring graph, it’s boring for a reason and should reflect your boring data!!  DON’T BE MISLEADING!!!
17. 17. Let’sAnalyze Some Graphs! •What Do you notice about these graphs? •What’s good about them? •What’s bad about them? •What are they telling you?