1. Yes, that’s right. I know we’re in science. You still need to do math.
MATH AND GRAPHS
IN SCIENCE

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. Accuracy
 How close a
measurement is to the
true or actual value.
Accuracy
All aimed for bulls eye: all in

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. What is this??
 Neither!!!
Accurate? Reproducible?

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. 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. Yep, more math… almost done!!
(it’s worth it, trust me)

9. Graphs:
 A visual representation of your
data (easiest way to know what
your data is “saying”)

10. Origin
 Where the two axes meet
(where the graph starts)
 Origin

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. 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. 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. 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. 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. 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. 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?