Ian Talks Statistics A-Z

Ian Talks Statistics A-Z

Ian Eress

Published by Ian Eress, 2023.

While every precaution has been taken in the preparation of this book, the publisher assumes no responsibility for errors or omissions, or for damages resulting from the use of the information contained herein.

IAN TALKS STATISTICS A-Z

First edition. March 2, 2023.

Copyright © 2023 Ian Eress.

ISBN: 979-8215619148

Written by Ian Eress.

Table of Contents

A

B

C

D

E

F

G

H

I

J

K

L

M

N

O

P

Q

R

S

T

U

V

W

X

Y

Z

INDEX

For Caitlyn

A

Aalen, Odd Olai (1947–1987): Odd Olai Aalen is a Norwegian statistician who is known for his contributions to the field of survival analysis, particularly in the development of the nonparametric Aalen-Johansen estimator and the theory of counting processes.

Survival analysis is a statistical method used to analyze the time until an event of interest occurs, like the death or failure of a mechanical component. The Aalen-Johansen estimator is a non-parametric method used to estimate the probability of experiencing a certain event, given that the individual has survived up to a particular time point. This estimator is particularly useful in situations where there may be competing risks, like multiple potential causes of death.

Aalen has also developed methods for analyzing longitudinal data, like the landmark method for estimating dynamic treatment regimes and the joint model for longitudinal and time-to-event data. These methods are useful for understanding how treatments or interventions may affect outcomes over time.

In addition to his research contributions, Aalen has also played a significant role in the development of statistics in Norway and internationally. He has served as president of the International Biometric Society and has received numerous awards for his contributions to the field of statistics.

Abbey, Helen (1915–2001): Helen Abbey is an Australian statistician who has made significant contributions to the field of survey methodology, particularly in the development of weighting methods for complex surveys and the analysis of nonresponse and measurement errors.

Survey methodology is the scientific process of collecting, analyzing, and interpreting data from a sample of individuals or households to estimate the characteristics of a larger population. In complex surveys, like those conducted by national statistical agencies, the sample design and data collection methods can be quite intricate, and the resulting data can be subject to biases due to nonresponse, measurement error, and other factors.

Abbey has developed methods for weighting survey data to adjust for these biases and improve the accuracy of estimates. She has also contributed to the development of imputation methods for handling missing data in surveys and the analysis of measurement errors in survey responses.

In addition to her research contributions, Abbey has played a significant role in promoting the use of statistics in Australia and internationally. She has served as president of the Statistical Society of Australia and has received numerous awards for her contributions to the field of statistics and survey methodology.

Abbott, Edith (1876–1957): Edith Abbott was an American economist, social worker, and statistician who made significant contributions to the field of social statistics and was a pioneer in the use of statistics in social work research.

Abbott's work in social statistics focused on the collection and analysis of data related to social problems, like poverty, unemployment, and crime. She recognized the importance of accurate and reliable data in understanding and addressing these issues, and worked to develop methods for collecting and analyzing such data.

Abbott was also a leading figure in the development of social work research. She believed that social workers needed to be trained in research methods and to use data and statistics to inform their practice. She played a key role in the establishment of the Social Service Review, a leading journal in the field of social work research, and served as its editor for many years.

In addition to her contributions to statistics and social work research, Abbott was a strong advocate for social justice and worked to promote the welfare of vulnerable populations. She was the first woman appointed to the faculty of the University of Chicago's School of Social Service Administration and was also the first woman to be appointed to the President's Committee on Social Security.

Abbott's work in statistics and social work has had a lasting impact on both fields, and she is widely recognized as a trailblazer and pioneer in the use of data and statistics in the social sciences.

Abelson, Robert P. (1928–2005): Robert P. Abelson was an American psychologist and statistician who made significant contributions to the field of social psychology, particularly in the areas of hypothesis testing, causal inference, and research design.

Abelson's work in statistics focused on developing methods for evaluating the evidence for and against hypotheses, and for making causal inferences in observational studies. He was a strong advocate for the use of multiple methods and sources of data to support causal claims and emphasized the importance of carefully designing studies and analyzing data in a rigorous and transparent manner.

One of Abelson's most influential contributions to statistics and psychology was the development of the null hypothesis significance testing (NHST) framework, which is widely used in psychology and other social sciences to evaluate statistical evidence for or against hypotheses. Abelson argued that NHST, while useful in certain contexts, was sometimes misused and overinterpreted and that researchers needed to be more cautious and thoughtful in their use of statistical tests.

Abelson also made significant contributions to research design, advocating for the use of experimental and quasi-experimental methods to establish causal relationships between variables. He emphasized the importance of carefully selecting comparison groups and controlling for potential confounding factors and argued that causal inference required a combination of statistical and theoretical reasoning.

In addition to his contributions to statistics and psychology, Abelson was also a highly regarded educator and mentor and was known for his engaging and accessible writing style. His work has had a lasting impact on the fields of statistics, psychology, and social science research, and he is widely recognized as one of the leading thinkers in these areas.

Abramovitz, Moses (1912–2000): Moses Abramovitz was an American economist who made significant contributions to the field of economic growth and development, particularly in the areas of productivity growth, technological change, and statistical analysis.

Abramovitz's work in statistics focused on developing methods for measuring and analyzing productivity growth and technological change, which are key drivers of economic growth and development. He recognized the importance of accurately measuring these variables and understanding their underlying causes, and worked to develop new statistical methods and frameworks for analyzing them.

One of Abramovitz's most influential contributions to statistics and economics was his development of the residual method for measuring total factor productivity (TFP), which measures the extent to which technological progress and other factors contribute to economic growth beyond the growth of inputs like labor and capital. This method is still widely used in empirical studies of productivity growth and economic development.

Abramovitz also made significant contributions to the study of economic growth and development, arguing that technological change and productivity growth were key drivers of long-run economic growth. He emphasized the importance of investment in research and development and other forms of innovation and argued that policies that encouraged innovation and entrepreneurship were critical for promoting economic growth and development.

In addition to his research contributions, Abramovitz was a highly regarded teacher and mentor, and his work has had a lasting impact on the fields of economics, statistics, and economic development. He is widely recognized as one of the leading thinkers in these areas, and his work continues to inform research and policy debates in these fields today.

Achenwall, Gottfried (1719–1772): Gottfried Achenwall was an 18th-century German philosopher, economist, and statistician who is considered one of the founders of modern statistics.

Achenwall's work in statistics focused on developing methods for collecting, analyzing, and interpreting data, particularly in the areas of social and economic statistics. He was a strong advocate for the use of empirical evidence and data in decision-making and believed that statistics could provide a scientific basis for understanding social and economic phenomena.

One of Achenwall's most important contributions to statistics was his development of a classification system for statistical data, which organized data according to various attributes like time, place, and category. This system was widely adopted and helped to standardize the collection and reporting of statistical data across different fields and regions.

Achenwall also made significant contributions to the development of statistical theory and methodology, particularly in the areas of probability and sampling. He was one of the first statisticians to recognize the importance of randomness and chance in statistical analysis and helped to develop methods for sampling and inference that are still widely used today.

In addition to his contributions to statistics, Achenwall was also a prominent philosopher and economist and wrote extensively on topics like natural law, political economy, and education. He was a highly influential figure in his time and helped to lay the groundwork for the development of modern statistics as a scientific discipline.

ADaMSoft: ADaMSoft is an open-source software package designed for statistical analysis and data mining. It was developed by the ADaMSoft Team, a group of researchers and statisticians from various academic institutions around the world.

ADaMSoft provides a wide range of statistical analysis tools and methods. This includes regression analysis, hypothesis testing, clustering, classification, and data visualization. The software is designed to be user-friendly and accessible to both novice and advanced users and includes a graphical user interface and a command-line interface for more advanced users.

One of the key features of ADaMSoft is its flexibility and extensibility. The software is designed to work with a wide range of data formats. This includes CSV, Excel, SPSS, and SAS, and can also be easily integrated with other software packages and programming languages like R and Python.

ADaMSoft is also designed to be highly efficient and scalable and includes parallel processing capabilities for large datasets and computationally intensive tasks. This makes it well-suited for use in a wide range of applications. This includes scientific research, business analytics, and data-driven decision-making.

Overall, ADaMSoft is a powerful and versatile statistical analysis tool that provides a wide range of features and capabilities for both novice and advanced users. Its open-source nature and community-driven development make it a popular choice among researchers and statisticians around the world.

Adelstein, Abraham Manie (1916–1992): Abraham Manie Adelstein was an American statistician who made significant contributions to the fields of biostatistics and public health.

Adelstein's work focused on developing statistical methods and models for analyzing data related to public health issues, particularly in the areas of cancer research and epidemiology. He was a pioneer in the development of methods for analyzing survival data, which are used to study the length of time that patients survive after a particular treatment or diagnosis.

One of Adelstein's most important contributions to biostatistics was his development of the Adelstein estimator, a method for estimating the survival function of a population based on incomplete or censored data. This method has become a widely used tool for analyzing survival data and has helped to advance our understanding of the effectiveness of different treatments and interventions for various diseases.

In addition to his research contributions, Adelstein was also a dedicated teacher and mentor and played a significant role in training the next generation of biostatisticians and public health researchers. He was a respected member of the statistical community and received numerous awards and honors for his contributions to the field.