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. To be effective, the analyst needs to understand the relevant issues both current and those likely to emerge in the future and how to present the results to the audience.
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.Tags: Research Paper Citing Within PaperResearch Paper About Gay MarriageFrederick Douglass Essay ThesisCiting Sources In Apa Research PaperDracula Topics EssayEssay Reflections English ClassEssay On Arrange MarriagesCollected Essays Of Ralph EllisonEssay On Television Violence AndHow To Write A Creative Nonfiction Essay
For example, a telephone survey of one thousand car owners in the United States might be conducted to predict the popularity of various cars among all U. First and perhaps foremost, an unbiased sample must be used.
In other words, every person (or item) in the population should have an equal chance of being in the sample.
Because it is often difficult, or even impossible, to look at all the data (for example, to poll every high school student in the United States), data are generally obtained from a smaller unit, a subset of the population known as a sample . But there both an art and science to collecting high-quality data.
Then data from the sample are used to predict (or infer) what the characteristics of the population as a whole may be. Several key elements must be considered: bias, sample size, question design, margin of error, and interpretation. In order for data interpretation to be reliable, a number of factors must be in place.
Interpretation is the process of making sense of numerical data that has been collected, analyzed, and presented.
People interpret data when they turn on the television and hear the news anchor reporting on a poll, when they read advertisements claiming that one product is better than another, or when they choose grocery store items that claim they are more effective than other leading brands.Some Statistics Canada programs depend on analytical output as a major data product because, for confidentiality reasons, it is not possible to release the microdata to the public. Data analysis also plays a key role in data quality assessment by pointing to data quality problems in a given survey. Results of data analysis are often published or summarized in official Statistics Canada releases. A statistical agency is concerned with the relevance and usefulness to users of the information contained in its data. 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 repercussions of inaccurate or improperly interpreted data are wide-ranging.For example, every 10 years a major census is done in the United States. "Policy on the Review of Information Products." Statistics Canada Policy Manual. Data interpretation is part of daily life for most people.