Unit 5 (Data)

Question 1

Visualizations can help us:

Answer 1

Answer questions
Look at lots of data at once
See patterns that are “invisible” if you just look at the table

Question 2

Explain the difference between Correlation and Causation
* Correlation def
* Causation def

Answer 2

Correlation - similarities, patterns

Causation - this thing caused that thing

Question 3

When looking at visualizations, what are facts and opinions?
* fact question def
* opinion question def

Answer 3

What does the data show? - fact
Why might that be the case? - opinion

Question 4

Metadata are data about data:
* It can be changed without …..
* Used for …..(3 things)…. information
* Increases ……
* Allows data to be ….. and ……

Answer 4

• It can be changed without impacting the primary data
• Used for finding, organizing, and managing information
• Increases effective use of data by providing extra information
• Allows data to be structured and organized

Question 5

Programs (like the Data Visualizer) can help:
Charts and other visualizations can help:

Answer 5

process data so we can understand it and learn.
both find and communicate what we’ve learned from data

Question 6

Bar charts and histograms are two common chart types for exploring one column of data in a table. Explain
* Information we can get out of bar charts (what value(s) are …., what value(s) are …, what is the unique ….
* Information we can get out of histograms (what range of value(s) are …., what range of value(s) are ….., what range of values do or do not ….)

1 column data charts

Answer 6

Bar charts: Count how many times each value in the column appears and make a bar at that height. Aren’t very useful when every value is unique
* What value(s) are most common in this column?
* What value(s) are least common in this column?
* What is the unique list of values in this column?

Histogram: Similar to a bar chart, but first all numbers in a range or “bucket” are grouped together. For example, the chart below has a bucket size of 20 so the numbers 41, 48, and 53 would all be placed in the same bucket between 40 and 60.
* What range of value(s) are most common in this column?
* What range value(s) are least common in this column?
* What ranges of values do or do not appear in this column?

Question 7

The data analysis process
* The 4 steps
* when do you clean data?
* what would filtering allow the user to do?

Answer 7

Collect or Choose Data
Clean and/or Filter
* Cleaning when: Data is incomplete, Data is invalid, Multiple tables are combined into one. Also when data is messy and not inputted correctly
* Filtering data allows the user to look at a subset of the data.

Visualize and Find Patterns
New Information

Question 8

Cross tab charts definition, usefulness, and non usefulness
* finding the ….. in two columns
* finding ….. across 2 columns
* exploring two columns when one or both are …..
* not useful if either column has ……

Scatter plots definition, usefulness, and non usefulness
* seeing ….. and …… between 2 values
* …. data with lots of different ……
* not useful if it has lots of ……

2 column data charts

Answer 8

Cross Tab: Counts how often pairs of values in two columns appear.
* Finding the most / least common combinations of values in two columns
* Finding patterns across two columns
* Exploring two columns when one or both are strings.

Not useful: If either column has too many values (the chart would be enormous)

Scatter: Shows combinations of values from two columns
* Seeing patterns and trends between two values
* Numeric data with lots of different values

Not useful: Lots of repeated values

Question 9

Explain:
1. Open data
2. Citizen science and crowdsourcing
3. Big data

Answer 9

Open Data
* “sharing data with others so they can can analyze it”
* Open data is publicly available data shared by governments, organizations, and others

Citizen Science and Crowdsourcing
* “collecting data from others so you can analyze it”
* Crowdsourcing is the practice of obtaining input or information from a large number of people via the Internet.
* Citizen science is research where some of the data collection is done by members of the public using own computing devices which leads to solving scientific problems

Big data
* “Collect huge amounts of data so we can learn even more from it”
* The size of the datasets we analyzed impacts how much information can be extracted
* As a result, in business, science, and many other contexts people are working with increasingly big data sets
* When data gets too big it can no longer be processed on one computer. Cloud computing or parallel systems are sometimes used to help process all that information.