A statistical model used to determine whether there are any statistically significant differences between the means of three or more independent groups.
ANOVA, which stands for Analysis of Variance, is a statistical technique used to compare the means of three or more samples to determine if at least one sample means significantly differs from the others. It is widely used in various fields such as business, medicine, and social sciences to test hypotheses on data sets.
Cluster Analysis is a method of statistical analysis that involves grouping individuals or objects by common characteristics of interest to the researcher. This technique is extensively used in various fields like marketing, finance, and sociology to identify patterns or behaviors among different groups for targeted actions.
Cross tabulation, also known as contingency table analysis, is a statistical technique used to establish an interdependent relationship between two or more tables of values, without identifying a causal relationship. This method is widely utilized in data analysis to compare and understand the relationship between two categorical variables.
Descriptive statistics is used to summarize or describe the main features of a collection of data in a quantitatively meaningful way. It does not infer any elements beyond the provided data sample.
Extrapolation involves estimating unknown values by extending or projecting trends or patterns observed in existing data beyond the known data set.
The concept of factorial is used both in statistics and mathematics to describe either a certain type of experimental design or the product of all positive integers up to a given number.
In empirical research, a hypothesis is an assertion made about some property of the elements being studied. It serves as a guiding assumption early in an investigation, directing the search for supporting data. At the conclusion of the study, the hypothesis is tested and determined to be true or false depending on whether the proposed property accurately characterizes the elements.
The least squares method, also known as least squares regression, is a statistical technique used for estimating cost behavior by plotting observed cost levels against various activity levels and calculating the best fit line.
A statistical calculation used to analyze data points by creating a series of averages of different subsets of the full data set. It is particularly used in finance and business to assess trends over a certain period.
Multicollinearity refers to the presence of independent variables in regression analysis that are associated with each other, having some degree of correlation. This phenomenon can complicate the interpretation of model coefficients and lead to unreliable results.
Multiple regression is a statistical method used to examine the relationship between one dependent variable and two or more independent variables. This technique helps in understanding how multiple factors simultaneously affect the dependent variable.
Negative correlation is an inverse association between two variables, where one variable increases while the other decreases. It is represented by correlation coefficients less than 0.
A 'Number Cruncher' refers to both a person who spends much time calculating and analyzing numerical data as well as a computer specifically designed to perform extensive numerical calculations.
An ordinal scale organizes observations into ordered categories, distinguishing them by relative amounts such as ranks.
A statistical procedure applied to time series data to eliminate the effect of seasonal variations, providing a more accurate representation of underlying trends and cyclical movements.
Computer programs that perform functions helpful to accountants, particularly managerial accountants, by creating, changing, storing, and using mathematical models. Examples include SPSS/PC and Systat.
A two-tailed test, also known as a two-sided or nondirectional test, is a method in hypothesis testing that examines whether two estimates of parameters are equal without considering which one is smaller or larger. This type of test rejects the null hypothesis if the test statistic is significantly small or large.
