happy tuesday scientists! today: return scored work grades data and graphs study guide collecting...
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Happy Tuesday Scientists!
Today:Return scored work
Grades
Data and Graphs Study GuideCollecting Discrete Data Activity
HW: Graph your data a second time using different scales for the DV
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Graphing Study Guide
Are you ready to go?
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• There are 4 major types of graphs we’ll use this year.
I can remember
that
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Types of Data
1. Discrete data = consist of categories (days of the week, kind of animal, color)
2. Continuous data = consist of measurements involving a scale with equal measurements; a range of values (temperature, length of time in hours, height in centimeters)
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Four major types of graphing
1. Pie chart/graph = consist of categories (display percentages)
2. Bar graph = used to represent discrete data; the IV is typically qualitative and DV is typically quantitative
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Four major types of graphing
3. Line graph = used to represent continuous data, usually tracking changes over time; the IV and DV are both quantitative and the line connecting the points has meaning
4. Scatter plot = similar to a line graph, but the data points are NOT connected because a connecting line would have no meaning; a line of best fit might be constructed to show a trend in the data; IV and DV are typically both quantitative
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Scatter plot
0 1 2 3 4 5 6 70
5
10
15
20
25Helicopter Drop Time Influenced by Pa-
perclips
# of Paperclips
Dro
p Ti
me
(s)
This is a line of best fit – it is a straight line that comes as close to possible as all the data points
The data points should NOT be directly connected because the IV is discrete
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Bar Graph6th period student drink choices
0
5
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pepsi coke rootbeer
dr.pepper
Drink Option
# o
f stu
den
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Series1
This is what we mean by discrete data – it’s a category and there’s no “middle value” between each category
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Line Graph
Jill's Elevation Change While Hiking
015030045060075090010501200
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5
Time (hours)
Ele
va
tio
n (
m)
Each value here has meaning (I could determine how Jill’s elevation at 3.2 hours) so I connect my data points with a line
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Pie chart
Here I have data organized in a percentage out of 100 – this is good way to represent it
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A few final thoughts
• Scientists must represent their data graphically in a fair way that tells the most accurate story
• It is possible to change the scale of a graph to make it look like the data tells a much different story than the numbers actually show
• Additional labels might also be used to make the reader infer certain things from the same set of data
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For example…• At most, how different is the average rainfall
from this year’s rainfall?
This graph has been manipulated to make it look like there is a much bigger difference in rainfall than 0.4 cmBad scientist!
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A more accurate graph
Good scientist!
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Another Example
Quarter, YearImage source: http://www.politicalmathblog.com/?p=401
Num
ber o
f job
s (t
hous
ands
)
U.S. Jobs by Quarter
What conclusions can you draw from this graph?
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Here’s the same graph with a few extra labels…
Image source: http://www.politicalmathblog.com/?p=401
The data is the same but it could be used to create different inferences
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Collecting and Graphing Discrete Data(title)
• A common example of discrete data is information collected when people complete surveys.
• Come up with a survey question you could ask of every student in this classroom (record on your paper under the title)– Example: Mrs. Ellis will be asking each student.
“What is the name of your 7th grade science teacher.
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Identify the IV and DV (Record)
• IV =• DV =
Create a data table (on your paper)
• Begin collecting data
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Graph your data
• Since this is discrete data, what types of graphs would be appropriate to use?
6th period student drink choices
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pepsi coke rootbeer
dr.pepper
Drink Option
# o
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Series1