Statistical Analysis with Swift: Data Sets, Statistical Models, and Predictions on Apple Platforms
內容描述
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
