Transcript What Mentors Need to Know

GUTS Youth Leadership
Corps
Things you need to know
Emphasis in GUTS Clubs
 Programming Concepts using Starlogo TNG
 Complex Adaptive Systems
 Development of Research Skills
 Data Acquisition
 Data Analysis
 Data Interpretation
 Presentation Skills
Expectations of GUTS Mentors
• Knowledge Expectations
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Starlogo TNG
Complex Adaptive Systems
Data Acquisition
Data Analysis
• Club Expectations
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Help the teachers
Help the facilitators
Teach some curriculum
Teach some activities
Coach students with programming
Coach students with projects
Starlogo TNG Quiz
Take the quiz
See what you remember!
Starlogo TNG
 Build Tasmanian Devils
 Review Programming Concepts
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Setup
Procedures
Variables
Conditional Statements
Input
Output
Complex Adaptive Systems
Review
• Made up of agents in an environment
• The agents
– Have characteristics – size, color, age
– Follow simple rules - aging
– There is randomness associated with their behavior
• Two types of interactions occur
– Agent/Agent interactions – collisions, hatching
– Agent/Environment interactions – agents movement, agents change
the environment or environment changes the agents
Complex Adaptive Systems
Review
• The system is
– Leaderless - no agent is coordinating the actions of other
agents
– Self-organizing – simple rules result in the organization of
the agents or the environment as the result of agents
following simple rules without external control or a leader.
– Emergent patterns - Patterns that form even though the
agents were not “told” to make a pattern.
Complex Adaptive Systems Template
CAST
NEW ASSESSMENT TOOL
CAS CAST
Tasmanian Devils CAST Activity
Fill in the CAST for the
Tasmanian Devil Model …
Tasmanian Devils CAST
Data Acquisition
 Data collection is the systematic recording of
information while changing Variables (a quantity that
may assume any given value or set of values).
 Collect the output (i.e. number of healthy agents,
number of infected agents, time…) while changing the
variables (number of devils, number initially infected)
of the model
Data Acquisition
Why do we gather data?
 To answer questions
 To develop understanding
 To validate experiments
Data Acquisition
How do we gather data using StarlogoTNG?
 Collect the data by hand
 Create a line graph in Starlogo TNG and extract the
data to Excel
 Create a bar graph in Starlogo TNG and extract the
data to Excel
 Create a table in Stalogo TNG and extract the data to
Excel
Data Acquisition
How Much Data?
 Variable Sweeping – experimental considerations:
 Number of variables
 Range of variables
 What changes things?
Thought Experiment
 If you have two variables of interest in
your model
 You decide that each variable needs
to be examined at the low, medium
and high end of its ranges
 How many DIFFERENT TYPES of
experiments do you need to
perform
Data Acquisition
How Much Data?
Thought Experiment Continued
 What if you needed to evaluated each parameter at 5
different values?
 Does that mean you need to run your model only that
number of times?
 NO – Scatter in your data
Data Acquisition
How Much Data?
 Number of Runs at the same parameter values – experimental
considerations:
 Scatter in data
 How many data points do you need to determine if your average
will be enough?
 Minimum 5 runs
Data Acquisition
How Much Data?
Data Analysis
What should we do with the data?
 Display – usually graph it to make it easier to see trends
 Analysis – use math skills to uncover patterns and trends in
data sets
 Interpretation - involves possible explanation those patterns
and trends.
Data Analysis
Displaying Data
 Two common ways to display data
 Tables
 Graphs
 Reasons to Graphically Display Data
 Makes your data visible
 Helps find obvious patterns
 Does the data makes sense?
 Are your assumptions correct?
 Did you collect enough data?
Data Analysis: Displaying Data – Types of Plots
All plots from http://www.statcan.ca
 Bar Charts – preferred snacks
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Pie Charts – music preference
Pets purchased at pet store
Data Analysis: Displaying Data – Types
of Plots
All plots from http://www.statcan.ca
 XY Graphs – cell phone use
http://www.statcan.ca
 Scatter Plots
http://en.wikipedia.org/wiki/Scatterplot
Data Analysis
Displaying Data
 Exercise
 Use Tasmanian Devils Model to extract data into Excel
 Plot Data in Excel
Data Analysis
Statistics
 Statistics help you
Now it is easy to summarize, describe
and analyze the data….
The blue and the pink data have the
Same AVERAGE value (mean) but the
blue data is “NOISIER” (greater
standard deviation). Therefore…
 Summarize data
 Describe data
 Analyze data
Hard to describe the difference
Between the two data sets
22
22
18
18
Noisy
14
Noisier
14
Mean (both)
Noisy
Noisy + 2SD
Noisier
Noisy - 2SD
10
10
Noisier + 2SD
Noisier - 2SD
6
6
2
0
2
0
10
20
30
40
50
60
10
20
30
40
50
60
Data Analysis
Statistics
• Two Areas we will examine
– Statistics that describe the “middle” of the data (Data
Central Tendency)
• Median
• Mode
• Mean or average
– Statistics the describe the “scatter” of the data (Data
Spread)
• Range
• Standard Deviation
Statistics – Measurements of Central
Tendency
Mean (Average), Median, and Mode
 Definitions
 Mean (Average) – Sum divided by the number of data points
 Median – Middle data point when arranged from highest to lowest
 Mode – Most frequent value
LET’S DO IT
 Use data set to calculate Mean (Average) Median,
Mode, Max and Min
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Select Cell where you want the value of the function to appear
Select Insert then Function
Select Statistical
Select function wanted (AVERAGE, MEDIAN, or MODE) then hit OK
Select Range of data you want to analyze by clicking on range symbol
and highlighting range. Hit enter or OK
Statistics – Measurements of Data Spread
Range, Variance and Standard Deviation
 Definitions
 Range = maximum - minimum
 Variance = measures noise of the data
around the mean value.
 ~68% of the data are in the interval
Mean – S to Mean + S
 ~95% of the data are in the interval
Mean – 2 S to Mean + 2 S
 ~99% of the data are in the interval
Mean – 3 S to Mean + 3 S
EXCEL does it for you!!!
LET’S DO IT
300
250
Number of Rabvits
 Standard Deviation (S) is the square
root of the variance. Most commonly
used measure of spread (same units
as the data). Another reason to use S:
Rabbit Population
200
150
100
50
0
0
500
1000
1500
Ticks
Rabbits
Mean
Mean - 2 S
Mean + 2 S
2000