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Please "contact us" to request a format other than those available. Practical Methods for Design and Analysis of Complex Surveys. Scope and purpose Principles Guidelines Quality indicators References Data analysis is the process of developing answers to questions through the examination and interpretation of data. For the interpretability of an analytical article to be high, the style of writing must suit the intended audience.
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"Policy on the Review of Information Products." Statistics Canada Policy Manual.
Data interpretation is part of daily life for most people.
A common method of assessing numerical data is known as statistical analysis , and the activity of analyzing and interpreting data in order to make predictions is known as inferential statistics .
Informed consumers recognize the importance of judging the reasonableness of data interpretations and predictions by considering sources of bias such as sampling procedures or misleading questions, margins of error , confidence intervals , and incomplete interpretations.
The basic steps in the analytic process consist of identifying issues, determining the availability of suitable data, deciding on which methods are appropriate for answering the questions of interest, applying the methods and evaluating, summarizing and communicating the results.
Analytical results underscore the usefulness of data sources by shedding light on relevant issues.
For an analytical product to be accurate, appropriate methods and tools need to be used to produce the results.
For an analytical product to be accessible, it must be available to people for whom the research results would be useful.