KT2: Assignment Instructions (Summer 2020)

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Perspectives

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Step #2

What - So What - Now What

(S) Systems

Step #1

Step #3: Pyramid Principle

Step #1b

(R) Relationships

(D) Distinctions

Systems Thinking... what is it?

(P) Perspectives

Step #1a

Empirical Rule

For nearly symmetric mound-shaped data sets, approximately 68% of the data is within one standard deviation of the mean and 95% of the data is within two standard deviations of the mean.

The Cartoon Guide to Statistics by Larry Gonick

https://www.amazon.com/Cartoon-Guide-Statistics-Larry-Gonick-dp-0062731025/dp/0062731025/ref=mt_paperback?_encoding=UTF8&me=&qid=

What makes statistics unique is its ability to quantify uncertainty, to make it precise. This allows statisticians to make categorical statements, with complete assurance-about their level of uncertainty!

Listen when you hear people state, "I'm 95% confident that..."

For example, in 1886, the space shuttle challenger exploded, killing seven astronauts. The decision to launch in 29-degree weather had been made without doing a simple analysis of performance data at low temperature.

Statisticians rely on three related disciplines: 1) Data analysis (gather, display, and summary of data); 2) Probability (the laws of change... gambling); 3) Statistical Inference (science of drawing statistical conclusions from specific data, using a knowledge of probability)

Data

are the statistician's raw material, the numbers we use to interpret reality. All statistical problems involve either the collections, description, and analysis of data, or Thinking about the collection, description, and analysis of data.

Data Description

how can we represent data in useful ways; how can we see underlying patterns in a heap of naked numbers; how can we summarize the data's basic shape

For example:

Frequency Table - we are showing how many data points are AROUND each value

Histogram - we can graph a frequency where each bar covers an interval and is centered at the midpoint. The bar's height is the number of data points in the interval.

Why statistics? Why it is simple to understand...

Zoom in

all that complexity must be coming out of really simple rules

Systems Thinking improves how we think

Zoom out

CAS emerge from simple rules. That underlying complexity, there is simplicity.

So, what do we mean then that our systemic thinking is both complex and simple? It means that the process of systems thinking is based on simple rules despite the fact that the outcomes may be terribly complex.

Systems Thinking as described in Super Thinking: The Big Book of Mental Models

https://www.amazon.com/Super-Thinking-Book-Mental-Models/dp/0525533583/ref=tmm_hrd_swatch_0?_encoding=UTF8&qid=&sr=

Systems thinking describes the act, when you attempt to think about the entire system at once.

By thinking about the overall system, you are more likely to understand and account for subtle interactions between components that could otherwise lead to unintended consequences from our decisions.

For example, when thinking about making an investment, you might start to appreciate how seemingly unrelated parts of the economy might affect its outcome.

Assignment Rules

Rules (Instructions)

Rule 1. Watch and review this presentation.

KT2 Assignment Instructions and How-To Video

Rule 2. Read Chapters 1-2 of your textbook.

Rule 3. Create a KT using DSRP to explain what the relationship of Standard Deviation and the Normal Curve is.

Starts on p. 18 of your textbook.

Rule 4. Create a Post in the Learning Community and include a link and/or image to your Plectica Map

You must respond to (at a minimum of two) other student post

Rule 5. Take the Feedback Survey (Required) at the following link (and post that you completed it).

https://www.surveymonkey.com/r/HYDVZL5

SMEAC

pronounced "SME - Ak"

Situation

You reviewed the situation by examining the assignment rules.

Mission

Complete a KT and post in the class WordPress site (and the Facebook Group for extra credit - don't forget the first to post this in the class WordPress site also receives extra credit).

Execution

Each student will focus their effort on completing the following simple rules. You will then post to the Swarm Learning (SL) WordPress site and respond to at least two other student posts.

Administration (and Feedback)

Each student must have access to Plectica, the WordPress site (and it is suggested that you are a member of the SL Facebook Group). Student KTs will serve as a feedback mechanism for the instructor.

Communication

Each individual student is in control of their KT. Your KT must be posted to the WordPress site (and respond to at least two other students) by no later than the end of the current module.

Blockchain understood using DSRP

https://www.plectica.com/maps/260JXNA8E

HHP (Blockchain) DSRP Example

idea C

view for perspective 1 and 2

courtroom

lawyer

hospital

doctor

Iran

Numbers

Israel

USA

idea B

perspective 2

idea A

perspective 1

Different perspectives result from changing the point, the view, or both.

idea

Letters

Political Ecology

Perspectives Example

Organizing by Part-Whole

Perspectives Rule

Any thing or idea can be the point or the view of a perspective.

Think of an analogy, simile, and metaphor.

For example, you could say....

A is to B as/like C is to D

Relationships Rule

Any idea or thing can relate to other things or ideas.

DSRP: 4 Patterns and 8 Elements

Simple Rule or Pattern

Distinction (D)

System (S)

Relationship (R)

Perspective (P)

Element 1

thing (t)

part (p)

action (a)

point (p)

Element 2

other (o)

whole (w)

reaction (r)

view (v)

Part-Whole Diagram

B1 and B2 as well as C1 and C2 are just parts, but they have the potential to be wholes

B and C act as parts of A but are also wholes that contain parts

A is just a whole

What is DSRP?

Universal cognitive patterns. Four simple rules that can be mixed and matched, combined and recombined in ways that are immensely complex, leading to robust, systemic thinking. Think of the diversity and creativity of nature that produces peacocks, giraffes, and star-nosed moles is born of genetic mutations of the four nucleotides of DNA (ATCG).

Much like the genetic code that underlies all species, DSRP provides a cognitive code that underlies human thinking.

While the simple rules of systems thinking are DSRP, the agents are little bits of information.

Systemic thought emerges from bits of information following simple rules (DSRP)

Simple Rules of a Flock

For example, a flock follows three simple rules

maintain distance x (locally to nearest neighbors)

Rule #1

adjust direction (locally to nearest neighbors)

Rule #2

avoid predators

Rule #3

Systems Rule

Any idea or thing can be split into parts or lumped into a whole.

Now What?

When we take a CAS perspective on systems thinking, we ask ourselves: what are its simple underlying rules? The simple rules are based on Distinctions (D), systems (S), relationships (R), and perspectives (P). That is, each bit of information can distinguish itself from other bits, each bit can contain other bits or be part of a larger bit, each bit can relate to other bits of information, and each bit of information can be looked at from the perspective of another bit of information and can also be a perspective of any other bit.

So What?

The cognitive patterns within DSRP are not merely applicable to systems thinking, they are universal to all thoguht.

What?

DSRP provides us simple rules to help us understand complex systems.

Gist

Four simple rules produce collective dynamics that in turn emerge as systemic thought.

2. Complex Adaptive Systems (CAS)

What are the basic features of a CAS?

1. autonomous agents following simple rules

2. the collective dynamics of which lead to

3. emergent complexity (e.g. intelligence, self-organization, robustness, resiliency, adaptive behavior)

A great example of a CAS is the flocking behavior in animals (i.e. flock of birds, flock of sheep) and other superorganisms, such as an ant colony and a school of fish.

There are no leaders providing direction... so what are they following?

They follow simple rules that bring about remarkable, adaptive, and complex behaviors.

1. Mental Models

mental model

real world

describes, summarizes, predicts, and leads to behavior in

consequences of which inform adaptation; selective effect on viability and on competition among models

Examining STv1.0 and STv2.0 through ST Questions

v1.0

What are systems?

How do systems work?

Are there universal elements to systems behavior across different types of systems?

What are the fundamental elements of a system?

What are the simple rules of complex systems?

Source: Systems Thinking Made Simple: New Hope for Solving Wicked Problems

https://www.amazon.com/Systems-Thinking-Made-Simple-Problems/dp/1520740492

Systems Thinking is a Complex Emergent Property of Four Simple Rules

To understand Systems Thinking v2.0, we must first understand two key ideas:

1. The idea of Mental Models

mental models approximate the real world, which provides feedback to adapt our mental models

2. The concept of a Complex Adaptive System (CAS)

a system that adapts to become better suited to its environment

v2.0

What is systems thinking?

How does systems thinking work?

Are there universal elements to systems thinking regardless of approach?

What are the fundamental elements of systems thinking?

What are the simple rules of systems thinking?

Thinkquiry example

https://www.plectica.com/thinkquiry

DSRP is Systems Thinking v2.0

We can first compare it to Systems Thinking v1.0

Distinctions Rule

Any idea or thing can be distinguished from the other ideas or things it is with.

Guiding Question

What is DSRP?

Relationships (R)

How are they related?

Systems (S)

What are its parts?

Distinction (D)

What is Statistics?

Tableau example of Standard Deviation

SCQ Framework

1. Subject

Standard deviation of measured dogs

2. Question

How do you determine it?

3. Answer

Find the mean, find the difference from the mean (and each number), square the result, find the mean of the squared differences, then find the square root.

4. Situation

Find the standard deviation of the measured dogs.

5. Complication

Don't know how to determine the standard deviation.

Question

Use the answer (3) above

Answer

147mm

6. New Question

Why is the standard deviation of 147mm important?

7. Key Line

Now we can show which heights are within 1 standard deviation (147mm) of the mean. So, using the standard deviation we have a "standard" way of knowing what is normal, and what is extra large or extra small.

Tip

Use this framework when creating your blog post

Bubble Logic for Two-Column Proofs

Statements

conclusions

1) The heights (at the shoulders) are: 600mm, 470mm, 170mm, 430mm and 300mm.

2) The mean (average) height is 394 mm

3) The difference from the mean for each dog is 206, 76, -224, 36, -94

4) The variance is 21,704

5) The standard deviation is 147mm

And the good thing about the standard deviation is that it is useful. Now we can show which heights are within 1 standard deviation (147mm) of the mean. So, using the standard deviation we have a "standard" way of knowing what is normal, and what is extra large or extra small.

We can expect about 68% of values to be within +/- 1 standard deviation

Reasons

If: statement above
Then: statement same line

1) Given

2) If you need to find the standard deviation of a set of numbers,

Then you must first find the mean

3) If the mean has been calculated,

Then we must calculate each dog's difference from the mean

600-394 = 206; 470-394 =76; 170-394 = -224; 430-394 = 36; 300-394 = -94

4) If the difference from the mean for each dog has been calculated,

Then we must calculate the variance by taking each difference, squaring it, and calculating the average result

5) If the variance has been calculated,

Then you must find the standard deviation, which is the square root of the variance

Given

The heights (at the shoulders) are: 600mm, 470mm, 170mm, 430mm and 300mm.

Find

The standard deviation of the heights of your dogs in millimeters.

Plectica Concept Map Rules

Guiding Question

What is statistics, measurement, evaluation, and assessment. And what is the standard deviation of test scores provided in this example?

Given Information/Data

Use example provided

Standard deviation

is a measure of how spread out numbers are from the average of a data set. It is not the same as average or mean deviation or absolute deviation, where the absolute value of each distance from the mean is used - is the measure most frequently used in statistical analysis

Its symbol is σ (the greek letter sigma)

Example

https://www.mathsisfun.com/data/standard-deviation.html

Guided Question

You and your friends have just measured the heights of your dogs (in millimeters). Find the mean, the variance, and the standard deviation.

Given Information/Data

The heights (at the shoulders) are: 600mm, 470mm, 170mm, 430mm and 300mm.

Rules and Logic (Bubble Logic)

To solve standard deviation:

1. Find the mean
2. Then for each number: subtract the mean and square the result
3. Then find the mean of those squared differences
4. Take the square root of that and you have the standard deviation

Assessment

The process of measure, evaluate, identify, and prescribe.

Evaluation

judgement about the measurement - for a measurement to be effective, it must be followed by evaluation

Test

is an instrument or a tool used to make a particular measurement

Propositions about a population

statistical inference makes propositions about a population, using data drawn from the population with some form of sampling

Hypothesis testing

given a hypothesis about a population, for which we wish to draw inferences, statistical inference consists of (first) selecting a statistical model of the process that generates the data and (second) deducing propositions from a model

Measurement

is the assignment of a number to a characteristic of an object or event, which can be compared with other objects or events

or the process of assigning a number to a performance or an attribute of a person

Probability theory

deals with the analysis of random phenomena

Dispersion (or variability)

characterizes the extent to which members of the distribution depart from its center and each other

variance, standard deviation, range

Grade point average (gpa) example

this single number describes the general performance of a student across the "range" of their course experiences

Central tendency (or location)

seeks to characterize the distribution's central or typical value

mean, median, and mode

Distribution (sample or population)

Index (statistics)

compound measure in statistics - a measure of changes in a representative group of individual data points, or in other words, a compound measure that aggregates multiple indicators. Indexes summarize and rank specific observations.

Inferential statistics

draw conclusions from data that are subject to random variation (e.g. observational errors, sampling variation).

Descriptive statistics

summarize data from a sample using indexes such as mean or standard deviation

Statistics

study of the collection, organization, analysis, interpretation, and presentation of data

two main statistical methods used in data analysis

When simplicity underlies complexity by Derek Cabrera

https://blog.cabreraresearch.org/when-simplicity-underlies-complexity#:~:text=That%20underlying%20complexity%2C%20there%20is%20simplicity.&text=It%20means%20that%20the%20process,outcomes%20may%20be%20terribly%20complex.

is to

tension

neutral

allies

is to

relates to

difference

one measures the dispersion

or how far apart the data is

one measures the center

or where the values tend to be centered

using the results of measurement and evaluation to identify performance and behavior problems and to prescribe how the problems can be corrected is an

to have meaning, you interpret test scores

this interpretation of measurement is an evaluation

inferences on mathematical statistics are made under the framework of

concerned with two sets of a distribution

feedback on

approximation of

descriptive statistics aims to summarize a sample, rather than use the data to learn about the population that the sample of data is thought to represent

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KT2: Assignment Instructions (Summer 2020)

Perspectives

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Perspectives

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Step #2

What - So What - Now What

(S) Systems

Step #1

Step #3: Pyramid Principle

Step #1b

(R) Relationships

(D) Distinctions

Systems Thinking... what is it?

(P) Perspectives

Step #1a

HHP (Blockchain) DSRP Example

idea B

idea A

Viewing perspective

View-only link

Present your ideas!

Blank map

Business model canvas

Mind map plus

Task board

Flow diagram

SWOT analysis

Perspectives on a system

Database schema

Cycle

User story map

Effort / value chart

User empathy map

Eisenhower Decision Matrix

Mental Models & Behavior

Changing Unhelpful Thinking & Behavior

Sales Pipeline Tracker

Cornell Notes

Bracket Diagram

Plot Structure Diagram

5 Whys

Org Chart

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KT2: Assignment Instructions (Summer 2020)

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Basic card

List card

Region

Relationship

Perspectives

Attributes

Waypoints

Add attribute...

Explain

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Step #2

What - So What - Now What

(S) Systems

Step #1

Step #3: Pyramid Principle

Step #1b

(R) Relationships

(D) Distinctions

Systems Thinking... what is it?

(P) Perspectives

Step #1a

idea B

idea A