Question

Explain the difference between ANOVA and ANCOVA in your own words. Both analysis tests are important but there are distinct differences. When is one used over the other?

Why is comparing two means an important part of the statistical analysis process? Give specific examples and explain in detail.

Answer 1

Here' the answer to the question with full concept. Please don't hesitate to give a "thumbs up" in case you're satisfied with the answer

Please see difference in ANOVA and ANCOVA and the use cases for each:

Analysis of Covariance or ANCOVA is basically an analyses with single response variable, or a continuous independent variables, and no factors at all. This kind of analysis can also be known as regression analysis. output tables are different in this . Also, regression requires that a user dummy codes factors, while GLM handles dummy coding through the "contrasts" option.

Analysis of Variance or ANOVA can test as many as three or more groups for mean differences based on a continuous response variable. The Factor is the variable that distinguishes this group membership. Catrgorical variables like Ethnicity, gender , and stage of life ( teen, adoloscent, adult, aged) of people are some of these "factors".

Comparing two means an important part of the statistical analysis process because we have to get answers to questions like : whether a sample belongs to a particular population, or is there a statisticalcally significant difference between two samples,

For example, in regression ANOVA is used to in deciding the significance of independent variable

In this case we compare the coefficient of mean with 0, to check if there is a linear relation between the dependent and independent variable

Another example, is comparison of means of 2 populations - like is the average age at which men and women marry the same, and does it vary from country to country. In this case I can run ANOVA on age of men and women when they marry, keeping factor as countries in this case.