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Retrieve Value Given a set of specific cases, find attributes of those cases. What is the value of aggregation function F over a given set S of data cases? What is the sorted order of a set S of data cases according to their value of attribute A?
What is the range of values of attribute A in a set S of data cases? What is the distribution of values of attribute A in a set S of data cases? What is the correlation between attributes X and Y over a given set S of data cases? Which data cases in a set S of data cases are relevant to the current users' context?
Barriers to effective analysis[ edit ] Barriers to effective analysis may exist among the analysts performing the data analysis or among the audience. Distinguishing fact from opinion, cognitive biases, and innumeracy are all challenges to sound data analysis.
Confusing fact and opinion[ edit ] You are entitled to your own opinion, but you are not entitled to your own facts. Daniel Patrick Moynihan Effective analysis requires obtaining relevant facts to answer questions, support a conclusion or formal opinionor test hypotheses. Facts by definition are irrefutable, meaning that any person involved in the analysis should be able to agree upon them.
This makes it a fact. Whether persons agree or disagree with the CBO is their own opinion. As another example, the auditor of a public company must arrive at a formal opinion on whether financial statements of publicly traded corporations are "fairly stated, in all material respects.
When making the leap from facts to opinions, there is always the possibility that the opinion is erroneous. Cognitive biases[ edit ] There are a variety of cognitive biases that can adversely affect analysis.
For example, confirmation bias is the tendency to search for or interpret information in a way that confirms one's preconceptions.
In addition, individuals may discredit information that does not support their views. Analysts may be trained specifically to be aware of these biases and how to overcome them. In his book Psychology of Intelligence Analysis, retired CIA analyst Richards Heuer wrote that analysts should clearly delineate their assumptions and chains of inference and specify the degree and source of the uncertainty involved in the conclusions.
He emphasized procedures to help surface and debate alternative points of view. However, audiences may not have such literacy with numbers or numeracy ; they are said to be innumerate.
Persons communicating the data may also be attempting to mislead or misinform, deliberately using bad numerical techniques.Section 9 Step-by-Step Guide to Data Analysis & Presentation Try it – You Won’t Believe How Easy It Can Be (With a Little Effort) Sample Spreadsheet.
Jim Berry January 31st, Reblogged this on Marketing Online Updates and commented: Here are a few data analysis tools as demonstrated by Derrick Harris of GigaOM.
The importance of knowing the statistical data of your websites, blogs, social media activities and your overall social influence cannot be . Slide 2 Using Data Analysis to Detect and Deter Fraud PricewaterhouseCoopers March Disclaimer The views in this presentation are those of Mr.
Glynn. Data Analysis and Presentation Skills: the PwC Approach Final Project from PwC. In this Capstone Project, you'll bring together all the new skills and insights you've learned through the four courses.
You'll be given a 'mock' client problem and a.
Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence [Judith D. Singer, John B. Willett] on regardbouddhiste.com *FREE* shipping on qualifying offers. Change is constant in everyday life. Infants crawl and then walk, children learn to read and write, teenagers mature in myriad ways.
Transform Data into Insight and Intelligence using powerful methods of analysis, techniques and tools Learn to ask the right questions of your data using comparison, trend, ranking, variance, pareto and many other techniques Learn data analysis using easy to master drag and drop techniques - no.