ap exam big idea 3 data and information
TRANSCRIPT
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L.O: STUDENTS WILL REVIEW BIG IDEA 3: DATA
AND INFORMATION
DO NOW:READ PAGE 21-26
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EK 3.1.1A Computers are used in an iterative and interactive way when processing digital
information to gain insight and knowledge.
Computers are useful because of ITERATION; they can do things such as processing data over and over and over and over again. We learn things because of
this ability of computers.
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EK 3.1.1B Digital information can be filtered and cleaned
by using computers to process information.Computer can do all kinds of
wonderful stuff to digital data!
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EK 3.1.1C Combining data sources, clustering data, and data classification are part of the process of
using computers to process information.
Computer can do all kinds of wonderful stuff to digital data!
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EK 3.1.1D Insight and knowledge can be obtained from
translating and transforming digitally represented information.
We can learn things when
we study data
processed by computers
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EK 3.1.1E Patterns can emerge when data is
transformed using computational tools.According to these computer models,
snowstorm is coming!
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EK 3.1.2A Collaboration is an important part of solving data-
driven problems.
2 heads are better than 1
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EK 3.1.2B Collaboration facilitates solving computational
problems by applying multiple perspectives, experiences, and skill sets.
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EK 3.1.2C Communication between participants working on data-driven problems gives rise to enhanced insights and knowledge.
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EK 3.1.2D Collaboration in developing hypotheses and questions, and in testing hypotheses and answering questions, about data helps participants gain insight
and knowledge.
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EK 3.1.2E Collaborating face-to-face and using online collaborative tools can facilitate processing information to gain insight and
knowledge.
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EK 3.1.2F Investigating large data sets collaboratively
can lead to insight and knowledge not obtained when working alone
This is a LARGE DATA SET ( a large amount of data). It means nothing to a human working
alone, but using a computer , you can find out what it means, by turning it into graphs, tables,
diagrams etc!
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EK 3.1.3A Visualization tools and software can
communicate information about data.
Computers and computing software can turn confusing and indecipherable into meaningful information that
humans can understand!
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EK 3.1.3B Tables, diagrams, and textual displays can be used in communicating insight
and knowledge gained from data
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EK 3.1.3C Summaries of data analyzed computationally can be effective in communicating insight and knowledge
gained from digitally represented information.
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EK 3.1.3D Transforming information can be effective in communicating
knowledge gained from data
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EK 3.1.3E Interactivity with data is an aspect of
communicating.
Computers turn data into information!
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EK 3.2.1ALarge data sets provide opportunities and challenges for extracting information and
knowledge.
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EK 3.2.1B Large data sets provide opportunities for identifying trends, making connections in
data, and solving problems.
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EK 3.2.1C Computing tools facilitate the
discovery of connections in information within large data sets.
Computers turn ugly data into cute information!
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EK 3.2.1D Search tools are essential for
efficiently finding information.
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EK 3.2.1E Information filtering
systems are important tools for finding information
and recognizing patterns in the information.
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EK 3.2.1 Software tools, including spreadsheets
and databases, help to efficiently organize and find trends in information.
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EK 3.2.1G Metadata is data about data.
The recording date of the data
METADATA is information ABOUT the data:
The time the data was recordedThe scanner the data
was recorded
The number of columns of dataThe number of
rows of data
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The camera manufacturer and
camera model used to record the data (picture) The “author”.
(the photographer)
The date & time the data (picture) was
generated
The exposure time of the
data
EK 3.2.1H Metadata can be descriptive data about an image, a Web page, or
other complex objects.
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EK 3.2.2A Large data sets include data such as transactions, measurements, texts,
sounds, images, and videos.
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EK 3.2.2B The storing, processing, and curating of
large data sets is challenging.
We keep needing bigger and bigger memory flash drives to store evermore information!
Some day, even 1 Terabyte won’t have enough for an average person!
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EK 3.2.2C Structuring large data sets for analysis
can be challenging.
Oh my gosh! How can I organize this data so that it makes SENSE!
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EK 3.2.2D Maintaining privacy of large data sets
containing personal information can be challenging.
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EK 3.2.2E Scalability of systems is an important
consideration when data sets are large.
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EK 3.2.2G The effective use of large data sets requires computational solutions.
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EK 3.2.2H Analytical techniques to store,
manage, transmit, and process data sets change as the size of data sets
scale.
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EK 3.3.1A Digital data representations involve
trade-offs related to storage, security, and privacy concerns.
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EK 3.3.1B Security concerns engender trade-offs
in storing and transmitting information.I HOPE no
one can see my info!
I HOPE no one can see
my info!
I HOPE no one can see
my info!
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EK 3.3.1C There are trade-offs in using lossy and lossless compression techniques for storing and transmitting data.
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EK 3.3.1D Lossless data compression reduces the number of bits stored or transmitted
but allows complete reconstruction of the original data.
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EK 3.3.1E Lossy data compression can significantly reduce the number of bits stored or transmitted at the cost of being able to reconstruct only an approximation of the
original data.
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EK 3.3.1F Security and privacy concerns arise with data containing personal information.
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EK 3.3.1G Data is stored in many formats depending
on its characteristics (e.g., size and intended use).
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EK 3.3.1HThe choice of storage media affects both the methods and costs of
manipulating the data it contains.
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EK 3.3.1I Reading data and updating data have different storage requirements.
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Independent work:complete the data and information questions