How Long to Read Best Practices in Data Cleaning

How Long Does it Take to Read Best Practices in Data Cleaning?

It takes the average reader 4 hours and 40 minutes to read Best Practices in Data Cleaning by Jason W. Osborne

Assuming a reading speed of 250 words per minute. Learn more

Description

Many researchers jump from data collection directly into testing hypothesis without realizing these tests can go profoundly wrong without clean data. This book provides a clear, accessible, step-by-step process of important best practices in preparing for data collection, testing assumptions, and examining and cleaning data in order to decrease error rates and increase both the power and replicability of results. Jason W. Osborne, author of the handbook Best Practices in Quantitative Methods (SAGE, 2008) provides easily-implemented suggestions that are evidence-based and will motivate change...

How long is Best Practices in Data Cleaning?

Best Practices in Data Cleaning by Jason W. Osborne is 275 pages long, and a total of 70,125 words.

This makes it 93% the length of the average book. It also has 86% more words than the average book.

How Long Does it Take to Read Best Practices in Data Cleaning Aloud?

The average oral reading speed is 183 words per minute. This means it takes 6 hours and 23 minutes to read Best Practices in Data Cleaning aloud.

What Reading Level is Best Practices in Data Cleaning?

Best Practices in Data Cleaning is suitable for students ages 12 and up.

Note that there may be other factors that effect this rating besides length that are not factored in on this page. This may include things like complex language or sensitive topics not suitable for students of certain ages.

When deciding what to show young students always use your best judgement and consult a professional.

Where Can I Buy Best Practices in Data Cleaning?

Best Practices in Data Cleaning by Jason W. Osborne is sold by several retailers and bookshops. However, Read Time works with Amazon to provide an easier way to purchase books.

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