To determine the impact of two extraction methods on physicochemical parameters and phytochemical composition, you can perform a two-sample t-test or ANOVA (analysis of variance) followed by post-hoc testing such as Tukey's honestly significant difference (HSD) test or Bonferroni correction. The choice of test depends on the number of variables you are comparing and whether the data meets the assumptions of normality and homogeneity of variance.

If you are comparing only two variables, a two-sample t-test is appropriate. However, if you are comparing more than two variables, ANOVA is more appropriate. Before performing any statistical analysis, you should first check for normality and homogeneity of variance using appropriate tests such as the Shapiro-Wilk test and Levene's test, respectively.

If the data is normally distributed and homogenous, you can proceed with the two-sample t-test or ANOVA. If the data is not normally distributed or homogenous, you may need to perform non-parametric tests such as the Mann-Whitney U test or Kruskal-Wallis test.

It's important to note that statistical analysis is just one part of the process and it should be used in conjunction with other methods such as visual inspection of the data and scientific reasoning to draw valid conclusions.

Lamia fatima thank you very much for your answer your explanation is very helpful for me.

According to the type of dataset, their graphical analysis methods, tests of normality and variance hemogenity of data and other indices in descriptive or quantitative statistics, it can be used the parametric and non-parametric methods. In fact, everything depends on the scale and objectives of the research study.

Thank you very much sir @Hamid