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

Graphing Study Guide

Are you ready to go?

• There are 4 major types of graphs we’ll use this year.

I can remember

that

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)

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

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

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

Bar Graph6th period student drink choices

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pepsi coke rootbeer

dr.pepper

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This is what we mean by discrete data – it’s a category and there’s no “middle value” between each category

Line Graph

Jill's Elevation Change While Hiking

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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

Pie chart

Here I have data organized in a percentage out of 100 – this is good way to represent it

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

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!

A more accurate graph

Good scientist!

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?

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

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.

Identify the IV and DV (Record)

• IV =• DV =

Create a data table (on your paper)

• Begin collecting data

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

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