Download e-book for kindle: Practical Data Science with R by Nina Zumel, John Mount

By Nina Zumel, John Mount

ISBN-10: 1617291560

ISBN-13: 9781617291562

Functional info technology with R lives as much as its identify. It explains easy ideas with no the theoretical mumbo-jumbo and jumps correct to the genuine use instances you'll face as you gather, curate, and learn the information an important to the luck of your small business. You'll practice the R programming language and statistical research innovations to rigorously defined examples dependent in advertising, company intelligence, and choice support.

Business analysts and builders are more and more amassing, curating, examining, and reporting on an important enterprise facts. The R language and its linked instruments offer a simple approach to take on daily information technological know-how initiatives with no lot of educational conception or complicated mathematics.
Practical information technology with R indicates you ways to use the R programming language and helpful statistical concepts to daily enterprise occasions. utilizing examples from advertising, company intelligence, and determination aid, it indicates you ways to layout experiments (such as A/B tests), construct predictive types, and current effects to audiences of all levels.

This ebook is available to readers with no historical past in facts technological know-how. a few familiarity with easy data, R, or one other scripting language is assumed.

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Extra info for Practical Data Science with R

Sample text

B) a sample. (c) a population. (d) statistics. 4. The number of occurrences of a data value is called (a) the class limits. (b) the frequency. (c) the cumulative frequency. (d) the relative frequency. 5. A large collection of quantitative data may be condensed by (a) constructing classes. (b) computing class marks. (c) computing class limits. (d) constructing a group frequency distribution. 6. When constructing a frequency distribution for a small data set, it is wise to use (a) 5 to 20 classes.

C) 40. (d) 30. 20. 1000. 9000. 1111. (d) cannot be determined from the given information. 21. If the first five classes of a frequency distribution have a cumulative frequency of 50 from a sample of 58, the sixth and last class must have a frequency count of (a) 58. (b) 50. (c) 7. (d) 8. Graphical Displays 25 The following information relates to Questions 22 to 28. Hint: Read the exam scores distribution from smallest value to largest value. The following table shows the distribution of scores on a final elementary statistics examination for a large section of students.

Statistic 3. census 4. discrete 5. continuous 6. inferential 7. inferential 8. descriptive 9. population 10. midpoints 11. sample 12. smallest 13. frequency 14. the same 15. bar chart, histogram, pie chart, frequency polygon, stem-and-leaf plot 16. cumulative 17. qualitative 18. average 19. gaps 20. both types 21. leaves, stems 22. random 23. 5 to 10 classes 24. histogram 25. the actual Multiple-Choice Questions 1. 10. 19. 28. (b) 2. (d) (d) 11. (c) (b) 20. (d) (d) 29. (b) 3. 12. 21. 30. (c) (b) (d) (c) 4.

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Practical Data Science with R by Nina Zumel, John Mount


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