A learner's guide to big numbers, statistics, and good decisions
ByMichael Milton
Publisher:O'Reilly MediaReleased: July 2009 Pages: 496
Today, interpreting data is a critical
decision-making factor for businesses and organizations. If your job
requires you to manage and analyze all kinds of data, turn to Head First Data Analysis,
where you'll quickly learn how to collect and organize data, sort the
distractions from the truth, find meaningful patterns, draw conclusions,
predict the future, and present your findings to others.
Whether you're a product developer researching the market viability of a new product or service, a marketing manager gauging or predicting the effectiveness of a campaign, a salesperson who needs data to support product presentations, or a lone entrepreneur responsible for all of these data-intensive functions and more, the unique approach in Head First Data Analysis is by far the most efficient way to learn what you need to know to convert raw data into a vital business tool.
You'll learn how to:
Whether you're a product developer researching the market viability of a new product or service, a marketing manager gauging or predicting the effectiveness of a campaign, a salesperson who needs data to support product presentations, or a lone entrepreneur responsible for all of these data-intensive functions and more, the unique approach in Head First Data Analysis is by far the most efficient way to learn what you need to know to convert raw data into a vital business tool.
You'll learn how to:
- Determine which data sources to use for collecting information
- Assess data quality and distinguish signal from noise
- Build basic data models to illuminate patterns, and assimilate new information into the models
- Cope with ambiguous information
- Design experiments to test hypotheses and draw conclusions
- Use segmentation to organize your data within discrete market groups
- Visualize data distributions to reveal new relationships and persuade others
- Predict the future with sampling and probability models
- Clean your data to make it useful
- Communicate the results of your analysis to your audience
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