Fisher's least significant differenceIn statistics, Fisher's least significant difference (LSD) is a procedure used to identify statistically significant differences between the means of multiple groups. Developed by Ronald Fisher in 1935, it was the first post-hoc test designed to be performed following a significant analysis of variance (ANOVA) result.
Data dredgingData dredging, also known as data snooping or p-hacking, is the misuse of data analysis to find patterns in data that can be presented as statistically significant, thus dramatically increasing and understating the risk of false positives. This is done by performing many statistical tests on the data and only reporting those that come back with significant results. Thus data dredging is also often a misused or misapplied form of data mining.
Analysis of varianceCollection of statistical modelsAnalysis of variance (ANOVA) is a family of statistical methods used to compare the means of two or more groups by analyzing variance. Specifically, ANOVA compares the amount of variation between the group means to the amount of variations within each group. If the between-group variation is substantially larger than the within-group variation, it suggests that the group means are likely different. This comparison is done using an F-test.
Multiple comparisons problemMultiple comparisons, multiplicity or multiple testing problem occurs when many statistical tests are performed on the same dataset. Each test has its own chance of a Type I error (false positive), so the overall probability of making at least one false positive increases as the number of tests grows. In statistics, this occurs when one simultaneously considers a set of statistical inferences or estimates a subset of selected parameters based on observed values.
StatisticsStatistics (from German: Statistik, orig. "description of a state, a country") is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. In applying statistics to a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a statistical model to be studied.
Scientific misconductScientific misconduct is the violation of ethical and professional standards in research, including fabrication, falsification, plagiarism, and other practices that compromise the integrity of the design, conduct, analysis, reporting, or publication of scientific or research findings. Basic definitions and urgency of dealing with misconductVarious research ethics bodies provide definitions of scientific misconduct.Family-wise error rateFamily-wise error rate (FWER) is a term from statistics for the probability of making one or more false discoveries, or type I errors when performing multiple hypotheses tests. FWER is a metric that quantifies the risk caused by multiple testing. It's the probability of making one or more Type I errors across all tests in a family of comparisons.Newman–Keuls methodThe Newman–Keuls or Student–Newman–Keuls (SNK) method is a stepwise multiple comparisons procedure used to identify sample means that are significantly different from each other. It was named after Student (1927), D. Newman, and M. Keuls. This procedure is often used as a post-hoc test whenever a significant difference between three or more sample means has been revealed by an analysis of variance (ANOVA).Holm–Bonferroni methodIn statistics, the Holm–Bonferroni method, also called the Holm method or Bonferroni–Holm method, is used to counteract the problem of multiple comparisons. It is intended to control the family-wise error rate (FWER) and offers a simple test uniformly more powerful than the Bonferroni correction. It is named after Sture Holm, who codified the method, and Carlo Emilio Bonferroni.
Research ethicsResearch ethics is a discipline within the study of applied ethics. Its scope ranges from general scientific integrity and misconduct to the treatment of human and animal subjects. The social responsibilities of scientists and researchers are not traditionally included and are less well defined. The discipline is most developed in medical research.APA styleAPA style (also known as APA format) is a writing style and format for academic documents such as scholarly journal articles and books. It is commonly used for citing sources within the field of behavioral and social sciences, including sociology, education, nursing, criminal justice, anthropology, and psychology. It is described in the style guide of the American Psychological Association (APA), titled the Publication Manual of the American Psychological Association.Statistical hypothesis testA statistical hypothesis test is a method of statistical inference used to decide whether the data provides sufficient evidence to reject a particular hypothesis. A statistical hypothesis test typically involves a calculation of a test statistic. Then a decision is made, either by comparing the test statistic to a critical value or equivalently by evaluating a p-value computed from the test statistic. Roughly 100 specialized statistical tests are in use.Post hocPost hoc (sometimes written as post-hoc) is a Latin phrase, meaning "after this" or "after the event".
Data dredgingData dredging, also known as data snooping or p-hacking, is the misuse of data analysis to find patterns in data that can be presented as statistically significant, thus dramatically increasing and understating the risk of false positives. This is done by performing many statistical tests on the data and only reporting those that come back with significant results. Thus data dredging is also often a misused or misapplied form of data mining.Analysis of varianceCollection of statistical modelsAnalysis of variance (ANOVA) is a family of statistical methods used to compare the means of two or more groups by analyzing variance. Specifically, ANOVA compares the amount of variation between the group means to the amount of variations within each group. If the between-group variation is substantially larger than the within-group variation, it suggests that the group means are likely different. This comparison is done using an F-test.Multiple comparisons problemMultiple comparisons, multiplicity or multiple testing problem occurs when many statistical tests are performed on the same dataset. Each test has its own chance of a Type I error (false positive), so the overall probability of making at least one false positive increases as the number of tests grows. In statistics, this occurs when one simultaneously considers a set of statistical inferences or estimates a subset of selected parameters based on observed values.StatisticsStatistics (from German: Statistik, orig. "description of a state, a country") is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. In applying statistics to a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a statistical model to be studied.Scientific misconductScientific misconduct is the violation of ethical and professional standards in research, including fabrication, falsification, plagiarism, and other practices that compromise the integrity of the design, conduct, analysis, reporting, or publication of scientific or research findings. Basic definitions and urgency of dealing with misconductVarious research ethics bodies provide definitions of scientific misconduct.Family-wise error rateFamily-wise error rate (FWER) is a term from statistics for the probability of making one or more false discoveries, or type I errors when performing multiple hypotheses tests. FWER is a metric that quantifies the risk caused by multiple testing. It's the probability of making one or more Type I errors across all tests in a family of comparisons.Newman–Keuls methodThe Newman–Keuls or Student–Newman–Keuls (SNK) method is a stepwise multiple comparisons procedure used to identify sample means that are significantly different from each other. It was named after Student (1927), D. Newman, and M. Keuls. This procedure is often used as a post-hoc test whenever a significant difference between three or more sample means has been revealed by an analysis of variance (ANOVA).Holm–Bonferroni methodIn statistics, the Holm–Bonferroni method, also called the Holm method or Bonferroni–Holm method, is used to counteract the problem of multiple comparisons. It is intended to control the family-wise error rate (FWER) and offers a simple test uniformly more powerful than the Bonferroni correction. It is named after Sture Holm, who codified the method, and Carlo Emilio Bonferroni.Research ethicsResearch ethics is a discipline within the study of applied ethics. Its scope ranges from general scientific integrity and misconduct to the treatment of human and animal subjects. The social responsibilities of scientists and researchers are not traditionally included and are less well defined. The discipline is most developed in medical research.APA styleAPA style (also known as APA format) is a writing style and format for academic documents such as scholarly journal articles and books. It is commonly used for citing sources within the field of behavioral and social sciences, including sociology, education, nursing, criminal justice, anthropology, and psychology. It is described in the style guide of the American Psychological Association (APA), titled the Publication Manual of the American Psychological Association.Statistical hypothesis testA statistical hypothesis test is a method of statistical inference used to decide whether the data provides sufficient evidence to reject a particular hypothesis. A statistical hypothesis test typically involves a calculation of a test statistic. Then a decision is made, either by comparing the test statistic to a critical value or equivalently by evaluating a p-value computed from the test statistic. Roughly 100 specialized statistical tests are in use.Post hocPost hoc (sometimes written as post-hoc) is a Latin phrase, meaning "after this" or "after the event".*As an Amazon Associate I earn from qualifying purchases.