analytical modeling techniques - Answer-Predictive Explanatory
Prescriptive
Descriptive- - Answer-This is a preliminary stage of data processing that creates a summary of historical data to yield useful information and possibly prepare the data for further analysis. Ex.) What happened? Whats ha...
Descriptive- - Answer-This is a preliminary stage of data processing that creates a
summary of historical data to yield useful information and possibly prepare the data for
further analysis. Ex.) What happened? Whats happening? Well defined business
problems and opportunities.
Predictive - Answer-Predictive analytics is the use of data, statistical algorithms and
machine learning techniques to identify the likelihood of future outcomes based on
historical data. The goal is to go beyond knowing what has happened to providing a
best assessment of what will happen in the future. What will happen next? (2) Why will it
happen next?
Explanatory - Answer-this is about looking into the past and determining why a certain
thing happened. This type of analytics usually revolves around working on a dashboard.
Why did it happen? (2) How did it happen?
prescriptive - Answer-Prescriptive analytics answers the question of what to do by
providing information on optimal decisions based on the predicted future scenarios. The
key to prescriptive analytics is being able to use big data, contextual data and lots of
computing power to produce answers in real time. What should be done about it? (2)
Why should you do it?
Heuristics Vs. Analytics - Answer-Heuristics is faster, analytics is slower. Using
heuristics may lead to decision biases.
Exploratory visualization - Answer-Exploratory visualization is the process that involves
a discipline expert creating maps and other graphics while dealing with relatively
unknown geographic data.
confirmatory visualization - Answer-the part where you evaluate your evidence using
traditional statistical tools such as significance, inference, and confidence.
production visualization - Answer-know exactly what to look for because you already
understand your production environment. typically put on a dashboard.
Tufte's principles of data visualization - Answer-The chart should tell a story. The chart
should have graphical integrity. The chart should minimize graphical complexity.
, Data Visualization Principle - Answer-The chart should minimize graphical complexity.
The depictions should enable meaningful comparison. The chart should yield insight
beyond the text
Framing - Answer-the way you tell a story.
structure - Answer-For content: create and weave threads to form the fabric of the
story .Compelling narrative
engagement - Answer-Good storytelling is about keeping both you and your audience
emotionally engaged to follow your entire story to make the point memorable
•Challenging in analytics :know your audience...
principles of story telling - Answer-Framing, structure, engagement.
Data-ink ratio - Answer-The amount of "ink" devoted to data in a chart is called "Data
Ink". In for a chart to minimize graphical complexity, the data-ink ratio must be close to 1
and higher than 1. Deleting the grid lines in a chart increases the ratio.
chart junk - Answer-any unnecessary information or feature in a graph that detracts
from a viewer's ability to understand the data
Lie Factor - Answer-size of effect shown in graphic / size of effect in data. The chart
should have graphical integrity. It should not "lie" or mislead readers. must be close to
1.
Population - Answer-Population: the whole. a collection of persons, objects, or items
under study. Census: gathering data from the entire population
Sample - Answer-a portion of the whole/population. A subset of the population; must be
large enough to represent the whole.
qualitative data - Answer-Information describing color, odor, shape, or some other
physical characteristic
quantitative data analysis - Answer-Can be counted, measured, and expressed using
numbers
centrality distribution - Answer-Measures of central tendency yield information about the
center, or middle part, of a group of numbers.
Shape Distribution - Answer-describe the skewness of a set of data. . Common
Measures of skewness is called Kurtosis - a measure of whether the data are peaked or
flat relative to a normal distribution.
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