"Astrostatistics is a discipline which spans astrophysics, statistical analysis and data mining."
Data acquisition, processing, management, analysis, visualization, and modeling techniques applied to astronomy data sets.
Probability Theory: The branch of mathematics concerned with the analysis of random phenomena.
Statistics: The science of collecting, analyzing, and interpreting data.
Descriptive Statistics: The branch of statistics that includes methods for summarizing and describing data using numerical measures such as mean, median, and mode.
Inferential Statistics: The branch of statistics that includes methods for making generalizations and predictions about a population based on data from a sample.
Sampling Methods: The techniques used to select a subset of individuals from a population to obtain information on the entire population.
Large Scale Data Analysis: The approaches and techniques that are employed to analyze big data sets.
Hypothesis Testing: A statistical method used to evaluate and test hypotheses in data analysis.
Regression Analysis: A statistical method that examines the relationship between two or more variables by studying their correlation.
Time Series Analysis: A statistical method for analyzing data collected over time, used to identify patterns and trends in data.
Machine Learning: A branch of artificial intelligence that involves the development of algorithms and models that enable computers to learn from data.
Data Visualization: The graphical representation of data to give information on patterns and trends in the data.
Data Cleaning and Preparation: The process that involves reducing noise and inconsistencies in data, as well as organizing it into a proper format for analysis.
Statistical Programming in R: A popular statistical programming language used for data analysis and visualization.
Bayesian Statistics: A statistical approach that involves the use of probability to express uncertainty in statistical inference.
Cluster Analysis: A statistical method used to identify groups or clusters within a dataset.
Multivariate Analysis: A branch of statistics that involves the analysis of data on more than two variables.
Spatial Data Analysis: The branch of statistics that deals with the analysis of data in a form that includes spatial or geographic information.
Network Analysis: A statistical method used to study the relationships and interactions between objects or individuals in a network.
Data Mining: The process of discovering patterns in large data sets using statistical methods.
Exploratory Data Analysis: A preliminary analysis of data to summarize its main characteristics and detect patterns.
Descriptive Statistics: It includes the analysis and summarization of data to gain meaningful insights into the data characteristics. Through this analysis, we can understand the central tendency and dispersion of the data.
Inferential Statistics: Inferential statistics involves using observed data to make assumptions about broader populations.
Predictive Analytics: This branch of data science creates models that can predict future outcomes based on past data.
Machine Learning: It is a subset of artificial intelligence that uses algorithms and statistical models to find patterns in the data and make predictions.
Text Mining and Natural Language Processing (NLP): It is the analysis of text and language data, including finding patterns and extracting meaning from unstructured data.
Social Network Analysis: This type uses statistical models to understand the connections between individuals within a social network.
Big Data Analytics: This type involves analyzing vast amounts of data that are too large to be handled by traditional data processing software.
Data Visualization: This type of data science is responsible for creating visual representations of data to help people understand complex information.
Astroinformatics: This field of data science is concerned with large scale data in astronomy, astrophysics and space science using statistics, machine learning, computer science and computational methods.
"It is used to process the vast amount of data produced by automated scanning of the cosmos, to characterize complex datasets, and to link astronomical data to astrophysical theory."
"Astrostatistics is a discipline which spans astrophysics, statistical analysis and data mining."
"It is used to process the vast amount of data produced by automated scanning of the cosmos."
"It is used to... characterize complex datasets."
"...to link astronomical data to astrophysical theory."
"Many branches of statistics are involved in astronomical analysis including nonparametrics, multivariate regression and multivariate classification, time series analysis, and especially Bayesian inference."
"The field is closely related to astroinformatics."
"...especially Bayesian inference."
"...to link astronomical data to astrophysical theory."
"It is used to process the vast amount of data produced by automated scanning of the cosmos."
"Many branches of statistics are involved in astronomical analysis..."
"...time series analysis..."
"...multivariate regression and multivariate classification..."
"It is used... to process... data mining."
"...to link astronomical data to astrophysical theory."
"Many branches of statistics are involved..."
"...to characterize complex datasets, and to link astronomical data to astrophysical theory."
"Many branches of statistics are involved... including nonparametrics..."
"The field is closely related to astroinformatics."