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TRANSCRIPT
Emphasis in GUTS Clubs
Programming Concepts using Starlogo TNG
Complex Adaptive Systems
Development of Research Skills
Data AcquisitionData AnalysisData Interpretation
Presentation Skills
Expectations of GUTS Mentors• Knowledge Expectations
– Starlogo TNG– Complex Adaptive Systems– Data Acquisition– Data Analysis
• Club Expectations– Help the teachers– Help the facilitators– Teach some curriculum– Teach some activities– Coach students with programming– Coach students with projects
Starlogo TNGBuild Tasmanian Devils
Review Programming ConceptsSetupProceduresVariablesConditional Statements InputOutput
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.
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 AcquisitionWhy do we gather data?
To answer questions
To develop understanding
To validate experiments
Data AcquisitionHow 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 AcquisitionHow Much Data?
Variable Sweeping – experimental considerations:Number of variablesRange of variablesWhat changes things?
Thought Experiment
If you have two variables of interest in your modelYou decide that each variable
needs to be examined at the low, medium and high end of its rangesHow many DIFFERENT TYPES of
experiments do you need to perform
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 AcquisitionHow Much Data?
Number of Runs at the same parameter values – experimental considerations:Scatter in dataHow many data points do you need to determine if your
average will be enough?Minimum 5 runs
Data AnalysisWhat 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 AnalysisDisplaying 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 PlotsAll plots from http://www.statcan.ca
• Pie Charts – music preference
Pets purchased at pet store
Bar Charts – preferred snacks
Data Analysis: Displaying Data – Types of PlotsAll plots from http://www.statcan.ca
XY Graphs – cell phone use
http://www.statcan.ca
Scatter Plots
http://en.wikipedia.org/wiki/Scatterplot
Data AnalysisDisplaying Data
ExerciseUse Tasmanian Devils Model to extract data into
ExcelPlot Data in Excel
Data AnalysisStatistics
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6
10
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18
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0 10 20 30 40 50 60
Noisy
Noisier
Mean (both)
Noisy + 2SD
Noisy - 2SD
Noisier + 2SD
Noisier - 2SD
Statistics help youSummarize dataDescribe dataAnalyze data
2
6
10
14
18
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0 10 20 30 40 50 60
Noisy
Noisier
Hard to describe the difference Between the two data sets
Now it is easy to summarize, describe and analyze the data….The blue and the pink data have the Same AVERAGE value (mean) but theblue data is “NOISIER” (greaterstandard deviation). Therefore…
Data AnalysisStatistics
• 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 TendencyMean (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
Use data set to calculate Mean (Average) Median, Mode, Max and Min
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
LET’S DO IT
Statistics – Measurements of Data SpreadRange, Variance and Standard Deviation
Rabbit Population
0
50
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150
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0 500 1000 1500 2000
Ticks
Nu
mb
er
of
Ra
bv
its
Rabbits Mean Mean - 2 S Mean + 2 S
Definitions Range = maximum - minimum
Variance = measures noise of the data around the mean value.
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:
~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