Inferential statistics is a branch of statistics extracting properties of a population from observations. The multivariate analysis deals with issues regarding more than one independent or dependent variable. The majority of the discussions of multivariate analysis are located at the intersection with inferential statistics.

Yes, it is possible to use statistics (inferential) without generalising your results. This is mostly common in situations where data were collected from samples that weren't selected randomly. If samples were selected purposively, then generalisation is made to the respondents and not the population. The argument is that a biased sample may not contain statistic (without 's') that reflects the population parameter; hence you don't generalise to the entire population in such situations.

Yes. You can

There are two main types of statistical analysis: descriptive and inferential. Descriptive statistics are used to describe data, while inferential statistics are used to infer conclusions and assumptions about the same information. This can be done for one variable as well as for two or more variables. For example:

- For one numeric variable, you can use a one sample t-test.

- For one categorical variable, you can use a one sample non-parametric test.

- For two categorical variables, you can use the chi-square independence test.

- Inference in the Multiple-Regression Model ..... And so on

Regards

To measure the relationship, the multiple correlation coefficient is used

respected researcher

It is better when we have one independent variable, and two dependent variables, to consider the factors in the independent variable, as if they are independent variables, and we measure their effect separately on the two dependent variables, as well as on the factors consisting of the two dependent variables as also dependent variables by themselves.

Thank you so much

I agree with most of the responses. I only add a modest suggestion. Dependent and independent variables are only found in research at the explanatory level, being causality studies, and it is assumed that the relationship between these variables has been previously demonstrated in a study at the relational level. The latter does not have to be done by the same author who is conducting the explanatory study.

creative researcher

If you mean in your research about demographic variables, the matter is different here, you must use the binary Two-Way Variance Analysis for multiple comparisons, so that you can extract the differences between the independent and dependent variables.