This blog post highlights some of the most influential papers in the field of statistics. These papers cover a range of topics in statistical probability, including hypothesis testing, exploratory data analysis, rare events, resampling methods, time series analysis, model selection, multiple testing, and regression analysis.
Benjamini, Y., & Hochberg, Y. (1995). "Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing"
This paper presents the Benjamini-Hochberg procedure for controlling the false discovery rate in multiple hypothesis testing, which has become a standard approach in many fields.
Box, G. E. P., & Jenkins, G. M. (1970). "Time Series Analysis: Forecasting and Control"
This influential book presents the Box-Jenkins methodology for time series analysis, which has become a standard approach for modeling and forecasting time series data.
Cohen, J. (1994). "The Earth is Round (p < .05)"
Cohen's paper discusses the over-reliance on p-values in scientific research and emphasizes the need for a more nuanced interpretation of statistical significance.
Efron, B. (1979). "Bootstrap Methods: Another Look at the Jackknife"
This paper introduces the bootstrap method, a powerful resampling technique for estimating the sampling distribution of a statistic and assessing its variability.
Fisher, R. A. (1922). "On the Mathematical Foundations of Theoretical Statistics"
This seminal paper by Fisher lays the foundation for modern statistical theory, introducing concepts such as maximum likelihood estimation and hypothesis testing.
Gigerenzer, G. (2004). "Mindless statistics"
This paper criticizes the mindless use of null hypothesis significance testing in research and proposes a more thoughtful approach to statistical analysis.
Neyman, J., & Pearson, E. S. (1933). "On the Problem of the Most Efficient Tests of Statistical Hypotheses"
This paper introduces the Neyman-Pearson lemma, a fundamental result in hypothesis testing that provides a basis for the construction of most powerful tests.
Taleb, N. N. (2007). "The Black Swan: The Impact of the Highly Improbable"
In this book, Taleb discusses the extreme impact of rare and unpredictable outlier events and the human tendency to find simplistic explanations for these events retrospectively, introducing the concept of the Black Swan.
Tibshirani, R. (1996). "Regression Sbrinkage and Selection via the Lasso"
This paper introduces the Lasso method, a widely used technique for variable selection and regularization in linear regression models.
Tukey, J. W. (1977). "Exploratory Data Analysis"
This influential book by Tukey introduces the concept of exploratory data analysis, emphasizing the importance of visualizing and summarizing data before applying formal statistical methods.
References
- Benjamini, Y., & Hochberg, Y. (1995). Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society. Series B(Methodological), 57(1), 289-300. https://doi.org/10.1111/j.2517-6161.1995.tb02031.x
- Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day.
- Cohen, J. (1994). The Earth is Round (p < .05). American Psychologist, 49(12), 997-1003. https://doi.org/10.1037/0003-066X.49.12.997
- Efron, B. (1979). Bootstrap Methods: Another Look at the Jackknife. The Annals of Statistics, 7(1), 1-26. https://doi.org/10.1214/aos/1176344552
- Fisher, R. A. (1922). On the Mathematical Foundations of Theoretical Statistics. Philosophical Transactions of the Royal Society of London. Series A, Containing Papers of a Mathematical or Physical Character, 222, 309-368. https://doi.org/10.1098/rsta.1922.0009
- Gigerenzer, G. (2004). Mindless statistics. Journal of Socio-Economics, 33(5), 587-606. https://doi.org/10.1016/j.socec.2004.09.033
- Neyman, J., & Pearson, E. S. (1933). On the Problem of the Most Efficient Tests of Statistical Hypotheses. Philosophical Transactions of the Royal Society of London. Series A, Containing of a Mathematical or Physical Character, 231, 289-337. https://doi.org/10.1098/rsta.1933.0009
- Taleb, N. N. (2007). The Black Swan: The Impact of the Highly Improbable. Random House.
- Tibshirani, R. (1996). Regression Shrinkage and Selection via the Lasso. Journal of the Royal Statistical Society. Series B (Methodological), 58(1), 267-288. https://doi.org/10.1111/j.2517-6161.1996.tb02080.x
- Tukey, J. W. (1977). Exploratory Data Analysis. Addison-Wesley.
