Purposive sampling might not satisfy the assumption of independence of observations because the sampling method involves selecting specific individuals based on certain characteristics or criteria, which may introduce bias into the selection process. Unlike random sampling, purposive sampling does not ensure that each individual in the population has an equal chance of being selected, which may limit the generalizability of the results. Therefore, it is important to carefully consider the potential sources of bias and other factors that may affect the validity of the results when using purposive sampling in your study. ANCOVA assumes homogeneity of regression slopes, which means that the impact of the covariate on the outcome variable should be similar for all groups. You should check this assumption before running ANCOVA on your data.

I checked the homogenity ofslopes and it is satified.

Thanks for your input

I do not believe that random sampling is required for independent observations. The latter is an issue of whether the selection of any one member of sample is related to the selection of other members of the sample, for example when you sample students from a single classroom.

Also, ANCOVA does allow for differences in regression slopes in the form of an interaction effect between your categorical variable and your continuous variable. Whether or not you have such an interaction effect is an empirical question.

Thanks for your output David.

Purposive sampling is a non-probability sampling technique that involves selecting a sample based on the researcher’s judgment or knowledge of the population. This technique is often used when the population is small or difficult to access.

Independence of observations is an important assumption in many statistical analyses. It means that the observations are not related to each other in any way. In other words, the value of one observation does not affect the value of another observation.