Although the terms ANOVA and ANCOVA sound similar, they are different techniques and possess different meanings. When one or more samples are involved, ANOVA is an effective technique for conducting research in a variety of disciplines such as business, economics, psychology, biology, and education. It is frequently confused with ANCOVA, as both are used to examine the variance in the mean values of the dependent variable caused by controlled independent variables after accounting for the effects of the uncontrolled independent variable.
ANOVA is a statistical technique used to compare and contrast the means of two or more populations. ANCOVA is a statistical method for comparing one variable in two or more populations while controlling for other variables. Check out the article to learn about the differences between ANOVA and ANCOVA.
Definition of ANOVA
ANOVA, which stands for analysis of variance, is defined as a statistical technique used to determine the difference in means between two or more populations by examining the amount of variation within the samples that corresponds to the amount of variation between the samples. It divides the total amount of variation in the dataset into two parts: that attributed to chance and that attributed to specific causes.
It is a method of analyzing the variables that are hypothesized or have an effect on the dependent variable. It can also be used to investigate the differences between different categories within factors that have a wide range of possible values. There are two kinds of it:
One way ANOVA: When a single factor with many possible values is used to investigate the difference between different categories.
Two way ANOVA: When two factors are investigated concurrently in order to measure the interaction of the two factors on the values of a variable.
Definition of ANCOVA
ANCOVA, which stands for Analysis of Covariance, is an extended form of ANOVA that removes the effect of one or more interval-scaled extraneous variables from the dependent variable prior to conducting research. It is a hybrid of ANOVA and regression analysis in which one variable in two or more populations is compared while the variability of other variables is taken into account.
The technique used is known as ANCOVA when a set of independent variables includes both factor (categorical independent variable) and covariate (metric independent variable). The difference in dependent variables caused by the covariate is offset by adjusting the mean value of the dependent variable within each treatment condition.
When the metric independent variable is linearly related to the dependent variable but not to the other factors, this technique is appropriate. It is predicated on the following assumptions:
- There is some connection between the dependent and uncontrolled variables.
- The relationship is linear and consistent from one group to the next.
- The population is divided into various treatment groups at random.
- In terms of variability, groups are homogeneous.
Differences Between ANOVA and ANCOVA
In terms of the distinction between ANOVA and ANCOVA, the following points are significant:
- Analysis of Variance, or ANOVA, is a technique for identifying the variance among the means of multiple groups for homogeneity. ANCOVA is a statistical procedure used before conducting research to remove the impact of one or more metric-scaled undesirable variables from the dependent variable.
- ANOVA employs both linear and non-linear models. ANCOVA, on the other hand, only employs a linear model.
- ANOVA only considers categorical independent variables, i.e., factors. ANCOVA, on the other hand, includes a categorical and a metric-independent variable.
- In ANOVA, a covariate is not considered, but in ANCOVA, it is.
- ANOVA distinguishes between group variations that are solely related to treatment. ANCOVA, on the other hand, divides group variations to treatment and covariate.
- ANOVA reveals within-group differences, particularly individual differences. ANCOVA, on the other hand, divides within-group variance into individual differences and covariates.
As a result of the preceding discussion, you should be able to distinguish between the two statistical techniques. The ANOVA method is used to compare the means of two groups. ANCOVA, on the other hand, is a more advanced type of analysis of variance that combines ANOVA and regression analysis.