yes.

Paired T test is applied to assess the mean difference of two sets of observation i.e. ( before and after ).

Common applications of the paired sample t-test include case-control studies or repeated-measures designs.

I found this answer very relevant to the question:

Statistical methods for numerical variable

there are two groups: 1. comparison group(T-test and ANOVA)

2. correlation and regression

t-test(paired and un paired )

UNPAIRED: the data are independent that is one nominal level variable (two different groups/categorical)with two group as independent variable that are mutually exclusive .eg. chomper mean birth weight between males and females

by independent of data we mean that the data value of each study subject rises independently uninfluenced by and uncorrelated with the data values of the other subjects. the distribution of the dependent variable /numerical variable normal(normally distributed). the test also assume that the variance (of the dependent variable) in the two groups are equal. the assumption is called the requirement of homogeneity of variance

PAIRED: data s are side to be paired , if the study subjects from one population can be matched or paired with particular subjects in the second population. paired data rise naturally from studies of twins and paired objects such as eyes or ears of the same individual.

advantage of paired data is that smaller size are needed b/c of the similarity , hence decries variability with in paired .paired data also arises in studies where observation are taken before and after the intervention on the same study subject.

paired data can be analysis the d/c b/n each member of the pair and tests to determine if the difference are significantly d/t from zero/ the data are normally distributed. eg. com paired mean blood pressure of diabetic patients before and after some intervention/treatment . one group matched twice rather than two independent group.

but your out come variable is categorical (case and control) not possible to use independent 2 samples or paired samples T test (it is wrong method of analysis)

The dependent /outcome/ response variable is categorical the appropriate method of analysis.

your out come variable is categorical , the baste method of analysis of your study or data is:

1. chi squared test of Independence( to check the association between categorical dependent variable and continuous or categorical independent variable)

2.matched paired test(cross-sectional , case control the data s are independent sample / before and after the study cross over or matched case control studies) each cell represent the number of pair in which both member of pair experienced the same value with the two equal to the number of pair

3. in paired sample we use MCNemar's test is the proper method of analysis to test the hypothesis

4. conditional logistic regression ( bi variate and multivariable analysis of logistic regression ) to check or to identify factors that affect the dependent variable(case and control) through controlled factors(independent variable) and confounding.the crud and a dusted OR together with the corresponding Confidence interval computed. A good fit as measured by Housmer lemeshow's test.

How to Select the Appropriate statistical Analise Selection criteria for statistical tests

First, you have to define the level of measurement of each variable to be included in the analysis.

Second, to select the correct statistical analysis, you have to clarify what you want to find out.

Third, sample size calculation or power analysis is directly related to the statistical test that is chosen.

The selection of a statistical test is based on the purpose of the test, the experimental design, and the type of variable (generally, measurement or rank).