Data Processing
Time 4.7 hrs

Difficulty Intermediate
Prerequisites Information Literacy
Departments Human Technologies
Authors Ross Parker
Groupings Individual
Pairs
Minimum Year Group None

### Blurb

In all likelihood, one day in the future part of your job will involve dealing with lots of data. This unit gives a quick overview of how data can be used effectively.

This work is shared under the following license: Creative Commons BY-SA-NC

### Outline

 The PitchWhy should I bother learning this? Want to be ready when your boss throws a stack of data at you? ResourcesWhat is needed to run this unit? Laptop Internet connection Spreadsheet software (Excel, Google Docs, LibreOffice Sheets, Apple Numbers, etc). Interdisciplinary Links Do not try and force this. What areas of other subjects might this reflect and/discuss language. For IB, links with ToK. Maths - connections exist via concepts such as number sorting, averages, distribution curves. Science - connections exist via concepts such as data collection, data sorting and graphing. Social Sciences - connections exist in terms of sample size, reliability and bias. Teacher ReflectionWhat was successful? What needs changing? Alternative Assessments and Lesson Ideas? What other Differentiation Ideas/Plans could be used? Despite the generally dry nature of data processing, the content used in this unit (Internet memes) makes this more appealing to students. CreditsAny CC attribution, thanks, credit, etc. Matrix thumbnail by macrovector on freepik under Freepik License. Data thumbnail image by DARPA on Wikimedia Commons shared under Public Domain.

5 mins
Want To Be Ready When Life Throws A Stack Of Data At You?
The Pitch
• Data is everywhere...we are practically drowning in it.
• Data can be enlightening or misleading, amazing or dispiriting, depending on what you know about using it.
• One day, when life (or your boss) throws a bunch of data your way...will you be ready to handle it?
5 mins
What Is Data
Theory
• Data:
• Data is the plural, datum is the singular.
• Data is a set of unorganised facts or measurements.
• If we organise data, we can end up with information.
• From information we can extract or distill knowledge, but this is harder than you might think.

• In this unit you will be assessed on your ability to turn data into knowledge, in the form of a graph.
15 mins
Learning From Data
Hands On
• The friendly people at Google have taken some public data sets, and turned them into information.
• Take some time to work with a partner, or on your own, to see if you can turn some of the Google Public Data Explorer information into knowledge.
• After around 10 minutes have a chat with your teacher, showing them the information you used, and the knowledge you extracted from it.
• This is not an easy task, and it is very easy to make incorrect assumptions.
40 mins
Building A Data Set
Information Gathering
• For the remainder of this unit you will be working to try and create information and knowledge from data.
• But first, we will need a data set.
• Our data set has been started by previous students, but you need to contribute to it using the form below.
• The topic we are collect data on is Internet memes, which are introduced in the video below:

• Please remember that an Internet meme is any unit of culture, spread from person to person on the Internet. It includes images, videos, emoticons, sayings, hashtags, fashion and much more.
• Take some time now to search the Internet for memes (avoiding anything inappropriate for school), with the aim of contributing at least four to our meme database using the form below:

5 mins
Potential Problems
Thinking Time
• By now you should have used and submitted the data collection form several times.
• Shortly, you will start looking at the data you collected.
• For now, can you think of any problems that might arise because of the design of the form, or the type of information we have been collecting?
• One example would be categories. Because there was no drop down menu of categories, and you could enter anything yourself, we will end up with a messy, inconsistent set of categories.
• What else might backfire when we look at the data?
5 mins
Accessing Our Data Set
Hands On
• Now that you have contributed to the data set, you can access our Internet Meme Data Set via this Google Drive link.
• Please make your own copy of this file in Google Drive, and keep it handy for use later.
45 mins
Hands On
• Before you start working on our data set, let's learn a little about spreadsheets.
• Spreadsheets are powerful tools for manipulating data: they are complex, but once mastered can be used in almost limitless ways.
• Databases are a partial alternative to spreadsheets: they are more powerful in some ways, and less powerful in others.
• Four commons spreadsheet applications are: Microsoft Excel, Google Drive Sheets, Apple Numbers, LibreOffice Calc.
• Now, please use Google Drive to create a new spreadsheet, and investigate the following terms using the image below:
• Tool bar
• Formula bar
• Sheets
• Column
• Row
• Cell

• You can double click on a cell, and enter some data into it.

• Cell Referencing: Every cell in a spreadsheet can be identified by a unique code. For example, the top-left most cell is referred to as A1. Try this quick exercise:
• Enter the values 1 through 10 into cells A1 through A10.
• In B1, entering the value =A1 and then press Enter.
• Now, grab the corner of B1 and drag it down to B10.
• What happened?
• Now, change the value of B1 to =\$A\$1 and then try to drag down to B10 again.
• Now what happened?
• What you just saw is the difference between relative and absolute referencing (this is something you might have seen in the Programming 101 unit, where Scratch offers some relative instructions and some absolute instructions).
• Cell updating: notice that if you update the value in one cell, all cells that refer to it are automatically updated.
20 mins
Processing: Sorting & Filter
Research
• Two of the most useful tools are sorting and filtering.
• Use this time to research and play around with these tools, aiming to learn as much as you can.
• Try to sort and filter your version of the Internet Meme Data Set...this will be useful for the next activity.
• Note, for this to work, you will need to unfreeze the top row of the data set.
30 mins
Processing: Removing Duplications
Hands On
• One of the problems with our Internet Meme Data Set is that some memes will be represented multiple times.
• To make our data set more useful, open your copy of it, and remove all of duplicate meme entries, leaving only one copy of each meme.
• The sort and filter tools might be useful here.
• Think about what you will do if the same meme has different values for one field, such as description or rating. How can you make sure you capture all data, but make it useful as well? Perhaps calculating an average might help in some cases.
40 mins
Processing: Forumlas
Hands On
• Cells can contain data, but they can also contain formulas, which can be used to manipulate data in other cells in numerous ways.
• Use this time to investigate, experiment with and apply formulas to your copy of the Internet Meme Database. How can you use formulas to extract information and knowledge from your data?
• A good example would be to use an averaging/mean formula to work out the average rating of all memes in the data set.
• This webpage might help you with some useful formulas (it is written for Microsoft Excel, but most should work in Google Drive too).
25 mins
Processing: Graphs
Hands On
• One way to turn data into knowledge, is to visualise it. This could take the form of an infographic, but a simpler start would be a graph.
• Google Drive can turn your data into a graph for you.
• Take some time now to work out what aspect of your data you want to graph (perhaps the frequency of meme ratings), and try to create the graph.
45 mins
Processing: The End
Hands On & Evidence
• The graph you started creating earlier will form one part of your assessment piece for this unit: please export it from Google Drive and put it into a Google or other word processing document. Add a title and some text to explain what you have learned from your data analysis and graph.
• This work should show that you can take some raw data, turn it into information, and then extract some knowledge from it.
• Submit this work as your evidence of learning in this unit.

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