1. GUTS Youth Leadership Corps Things you need to know

2. Emphasis in GUTS Clubs Programming Concepts using Starlogo TNG Complex Adaptive Systems Development of Research Skills Data Acquisition Data Analysis Data Interpretation Presentation Skills

3. 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

4. Starlogo TNG Quiz Take the quiz See what you remember!

5. Starlogo TNG Build Tasmanian Devils Review Programming Concepts Setup Procedures Variables Conditional Statements Input Output

6. 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

7. 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.

8. Complex Adaptive Systems Template CAST NEW ASSESSMENT TOOL

9. CAS CAST

10. Tasmanian Devils CAST Activity Fill in the CAST for the Tasmanian Devil Model …

11. Tasmanian Devils CAST

12. 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

13. Data Acquisition Why do we gather data? To answer questions To develop understanding To validate experiments

14. 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

15. Data Acquisition How Much Data? Variable Sweeping – experimental considerations: Number of variables Range of variables What changes things?

16. 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

17. Data Acquisition How Much Data?

18. 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

19. 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

20. Data Acquisition How Much Data?

21. 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.

22. 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?

23. Data Analysis: Displaying Data – Types of Plots All plots from http://www.statcan.ca Pie Charts – music preference Pets purchased at pet store Bar Charts – preferred snacks

24. 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

25. Data Analysis Displaying Data Exercise Use Tasmanian Devils Model to extract data into Excel Plot Data in Excel

26. Data Analysis Statistics Statistics help you Summarize data Describe data Analyze data 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 the blue data is “NOISIER” (greater standard deviation). Therefore…

27. 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

28. 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 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

29. Statistics – Measurements of Data Spread Range, Variance and Standard Deviation 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