## Data Analysis in Data Science: 10 Quotes

*“The errors which arise from the absence of facts are far more numerous and more durable than those which result from unsound reasoning respecting true data.” (Charles Babbage, “On the Economy of Machinery and Manufactures”, 1832)*

*“Not even the most subtle and skilled analysis can overcome completely the unreliability of basic data.” (Roy D G Allen, “Statistics for Economists”, 1951)*

*“The most important maxim for data analysis to heed, and one which many statisticians seem to have shunned is this: ‘Far better an approximate answer to the right question, which is often vague, than an exact answer to the wrong question, which can always be made precise.’ Data analysis must progress by approximate answers, at best, since its knowledge of what the problem really is will at best be approximate.” (John W Tukey, “The Future of Data Analysis”, Annals of Mathematical Statistics, Vol. 33, №1, 1962)*

*“The fact must be expressed as data, but there is a problem in that the correct data is difficult to catch. So that I always say ‘When you see the data, doubt it!’ ‘When you see the measurement instrument, doubt it!’ […]For example, if the methods such as sampling, measurement, testing and chemical analysis methods were incorrect, data. […] to measure true characteristics and in an unavoidable case, using statistical sensory test and express them as data.” (Kaoru Ishikawa, Annual Quality Congress Transactions, 1981)*

*“Data in isolation are meaningless, a collection of numbers. Only in context of a theory do they assume significance […]” (George Greenstein, “Frozen Star”, 1983)*

*“[…] data analysis in the context of basic mathematical concepts and skills. The ability to use and interpret simple graphical and numerical descriptions of data is the foundation of numeracy […] Meaningful data aid in replacing an emphasis on calculation by the exercise of judgement and a stress on interpreting and communicating results.” (David S Moore, “Statistics for All: Why, What and How?”, 1990)*

*“Data are generally collected as a basis for action. However, unless potential signals are separated from probable noise, the actions taken may be totally inconsistent with the data. Thus, the proper use of data requires that you have simple and effective methods of analysis which will properly separate potential signals from probable noise.” (Donald J Wheeler, “Understanding Variation: The Key to Managing Chaos” 2nd Ed., 2000)*

*“Doing data analysis without explicitly defining your problem or goal is like heading out on a road trip without having decided on a destination.” (Michael Milton, “Head First Data Analysis”, 2009)*

*“The discrepancy between our mental models and the real world may be a major problem of our times; especially in view of the difficulty of collecting, analyzing, and making sense of the unbelievable amount of data to which we have access today.” (Ugo Bardi, “The Limits to Growth Revisited”, 2011)*

*“Data analysis is not generally thought of as being simple or easy, but it can be. The first step is to understand that the purpose of data analysis is to separate any signals that may be contained within the data from the noise in the data. Once you have filtered out the noise, anything left over will be your potential signals. The rest is just details.” (Donald J Wheeler,” Myths About Data Analysis”, International Lean & Six Sigma Conference, 2012)*

*Originally published at **http://sql-troubles.blogspot.com**.*