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portada Statistical Analysis With Swift: Data Sets, Statistical Models, and Predictions on Apple Platforms
Type
Physical Book
Publisher
Year
2021
Language
English
Pages
228
Format
Paperback
Dimensions
23.4 x 15.6 x 1.2 cm
Weight
0.33 kg.
ISBN13
9781484277645
Edition No.
1

Statistical Analysis With Swift: Data Sets, Statistical Models, and Predictions on Apple Platforms

Jimmy Andersson (Author) · Apress · Paperback

Statistical Analysis With Swift: Data Sets, Statistical Models, and Predictions on Apple Platforms - Andersson, Jimmy

Physical Book

£ 43.02

  • Condition: New
Origin: U.S.A. (Import costs included in the price)
It will be shipped from our warehouse between Friday, June 28 and Wednesday, July 10.
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Synopsis "Statistical Analysis With Swift: Data Sets, Statistical Models, and Predictions on Apple Platforms"

Chapter 1: Swift Primer- Introduction to Swift and its pros when working with large data sets- Provided data sets and how to load them using the Decodable protocol- Higher-Order Functions (map, filter, reduce, apply) Chapter 2: Introduction to Probability and Random Variables- What is a random variable?- Sample spaces- Laws and axioms of probability- Variable Independence- Conditional probability Chapter 3: Distributions and Random Numbers- Mass and density functions- Discrete distributions- Discrete uniform distribution- Bernoulli trials- Binomial distribution- Poisson distribution- Continuous distributions- Continuous uniform distribution- Exponential distribution- Normal distribution- Implement a random number generator that samples from a given distribution Chapter 4: Predicting House Sale Prices with Linear Regression- Central tendency measures- Variance measures- Association measures- Stratification of data- Linear regression Chapter 5: Hypothesis Testing- T Testing- Null and Alternative Hypotheses- P-value- Determining sample sizes Chapter 6: Data Compression Using Statistical Methods- Measurement scales- Calculate the distribution of example data- Compute a Huffman Tree- Encode the original data in a smaller package- &nb

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