Think Stats. 2nd Edition - Helion
ebook
Autor: Allen B. DowneyISBN: 978-14-919-0736-8
stron: 226, Format: ebook
Data wydania: 2014-10-16
Księgarnia: Helion
Cena książki: 92,65 zł (poprzednio: 107,73 zł)
Oszczędzasz: 14% (-15,08 zł)
If you know how to program, you have the skills to turn data into knowledge, using tools of probability and statistics. This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python.
By working with a single case study throughout this thoroughly revised book, you’ll learn the entire process of exploratory data analysis—from collecting data and generating statistics to identifying patterns and testing hypotheses. You’ll explore distributions, rules of probability, visualization, and many other tools and concepts.
New chapters on regression, time series analysis, survival analysis, and analytic methods will enrich your discoveries.
- Develop an understanding of probability and statistics by writing and testing code
- Run experiments to test statistical behavior, such as generating samples from several distributions
- Use simulations to understand concepts that are hard to grasp mathematically
- Import data from most sources with Python, rather than rely on data that’s cleaned and formatted for statistics tools
- Use statistical inference to answer questions about real-world data
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Spis treści
Think Stats. 2nd Edition eBook -- spis treści
- Think Stats
- Preface
- How I Wrote This Book
- Using the Code
- Contributor List
- Safari Books Online
- How to Contact Us
- 1. Exploratory Data Analysis
- A Statistical Approach
- The National Survey of Family Growth
- Importing the Data
- DataFrames
- Variables
- Transformation
- Validation
- Interpretation
- Exercises
- Glossary
- 2. Distributions
- Representing Histograms
- Plotting Histograms
- NSFG Variables
- Outliers
- First Babies
- Summarizing Distributions
- Variance
- Effect Size
- Reporting Results
- Exercises
- Glossary
- 3. Probability Mass Functions
- Pmfs
- Plotting PMFs
- Other Visualizations
- The Class Size Paradox
- DataFrame Indexing
- Exercises
- Glossary
- 4. Cumulative Distribution Functions
- The Limits of PMFs
- Percentiles
- CDFs
- Representing CDFs
- Comparing CDFs
- Percentile-Based Statistics
- Random Numbers
- Comparing Percentile Ranks
- Exercises
- Glossary
- 5. Modeling Distributions
- The Exponential Distribution
- The Normal Distribution
- Normal Probability Plot
- The lognormal Distribution
- The Pareto Distribution
- Generating Random Numbers
- Why Model?
- Exercises
- Glossary
- 6. Probability Density Functions
- PDFs
- Kernel Density Estimation
- The Distribution Framework
- Hist Implementation
- Pmf Implementation
- Cdf Implementation
- Moments
- Skewness
- Exercises
- Glossary
- 7. Relationships Between Variables
- Scatter Plots
- Characterizing Relationships
- Correlation
- Covariance
- Pearsons Correlation
- Nonlinear Relationships
- Spearmans Rank Correlation
- Correlation and Causation
- Exercises
- Glossary
- 8. Estimation
- The Estimation Game
- Guess the Variance
- Sampling Distributions
- Sampling Bias
- Exponential Distributions
- Exercises
- Glossary
- 9. Hypothesis Testing
- Classical Hypothesis Testing
- HypothesisTest
- Testing a Difference in Means
- Other Test Statistics
- Testing a Correlation
- Testing Proportions
- Chi-Squared Tests
- First Babies Again
- Errors
- Power
- Replication
- Exercises
- Glossary
- 10. Linear Least Squares
- Least Squares Fit
- Implementation
- Residuals
- Estimation
- Goodness of Fit
- Testing a Linear Model
- Weighted Resampling
- Exercises
- Glossary
- 11. Regression
- StatsModels
- Multiple Regression
- Nonlinear Relationships
- Data Mining
- Prediction
- Logistic Regression
- Estimating Parameters
- Implementation
- Accuracy
- Exercises
- Glossary
- 12. Time Series Analysis
- Importing and Cleaning
- Plotting
- Linear Regression
- Moving Averages
- Missing Values
- Serial Correlation
- Autocorrelation
- Prediction
- Further Reading
- Exercises
- Glossary
- 13. Survival Analysis
- Survival Curves
- Hazard Function
- Estimating Survival Curves
- Kaplan-Meier Estimation
- The Marriage Curve
- Estimating the Survival Function
- Confidence Intervals
- Cohort Effects
- Extrapolation
- Expected Remaining Lifetime
- Exercises
- Glossary
- 14. Analytic Methods
- Normal Distributions
- Sampling Distributions
- Representing Normal Distributions
- Central Limit Theorem
- Testing the CLT
- Applying the CLT
- Correlation Test
- Chi-Squared Test
- Discussion
- Exercises
- Index
- Colophon
- Copyright