Sample Study of Descriptive-Comparative Design

Descriptive-Comparative research designs are appropriate for collecting descriptive information about a population of subjects of a study. They are appropriate for descriptive studies, like profile studies, exploratory studies, and doing small case studies. They are also ideal for diagnostic studies or situation analysis. However, they are not recommended for evaluation studies intended to determine the effect or impact of a certain intervention or treatment. 

The test of difference is a statistical measure that aims to determine if there is a significant difference among variables. In the test of the difference, you are comparing one variable to the other, like comparing which schools are performing well in terms of licensure examinations, comparing which department has the high job satisfaction rate, and etc.

The statistical measure depends on the nature of the sample and hypothesis testing procedure. The nature of the sample depends on whether the samples are dependent or independent or whether the samples are only two or more than two samples. The nature of the sample involves whether the samples are independent or different samples being compared to (i.e. male or female; school A, school B, or school C, and section 1 or section 2) and dependent or the same samples being compared at (i.e. grades of the students before and after a certain intervention or awareness of the students before and after the awareness seminar). The nature of the sample also depends on the number of samples, whether there are two or more than 2 samples.

Moreover, the statistical measure depends on whether the hypothesis testing is a parametric or non-parametric test. A parametric test is a hypothesis testing procedure based on the fulfillment of certain assumptions, like normality, linearity, homogeneity, etc. On the other hand, it does not require fulfilling the mentioned assumptions.

The application of statistical measures for the test of difference depends on the following:

      1.     Nature of the sample

1.1.           Independent or dependent sample

1.2.           2 samples or more than 2 samples

      2.     Nature of hypothesis testing procedure

           2.1 Parametric or Non-parametric test

Below are some statistical tests for exploring differences between groups:

Example 1

Research Title: 

Peer Mentoring Program on Academic Performance of the First Year Students of St. Francis College: A Comparative Study

Statement of the Problem:

1. What is the level of the academic performance of the respondents?

2. Is there a significant difference in academic performance before and after the peer mentoring program was implemented?

Hypothesis:

There is no significant difference in academic performance before and after the peer mentoring program was implemented.

Conceptual Paradigm:

Research Design: Descriptive - Comparative

Statistical Analysis: T-test for Dependent Samples for Parametric Test*; Wilcoxon Signed Rank test for Non-parametric test

Instrument: Academic performance of the respondents before and after the peer mentoring program was implemented.

Example 2

Research Title: Competence of Radiologic Technologists Employed in Private and Public Hospitals

Statement of the Problem:

1. What is the demographic profile of the respondents when grouped according to:

   1.1 Age

   1.2 Number of years in service

   1.3 Marital status

2. What is the level of competence among the respondents employed in private and public hospitals in terms of:

   2.1 Knowledge

   2.2 Skills

   2.3 Attitude

3. Is there a significant difference in the level of competence among respondents when grouped according to:

   3.1 Private hospital

   3.2 Public hospital

4. Does the demographic profile of the respondents significantly moderates when grouped according to:

   4.1 Age

   4.2 Number of years in service

   4.3 Marital status

Hypothesis:

1. There is no significant difference in the level of competence among respondents when grouped according to:

   1.1 Private hospital

   1.2 Public hospital

2. The demographic profile of the respondents does not significantly moderate when grouped according to:

   2.1 Age

   2.2 Number of years in service

   2.3 Marital status

Conceptual Paradigm:

Research Design: Descriptive - Comparative

Statistical Analysis: T-test for Independent Samples for Parametric Test*; Mann-Whitney U test for Non-parametric test

Instrument: Questionnaire to determine the level of competence of the respondents

Example 3

Research Title: Physical Therapy Licensure Examination Results Among Tertiary Schools in Davao City: A Comparative Study

Statement of the Problem:

1. What is the level of licensure examination results in Physical Therapy among tertiary schools in Davao City?

2. Is there a significant difference in the level of licensure examination results in Physical Therapy among tertiary schools in Davao City?

Hypothesis:

There is no significant difference in the level of licensure examination results in Physical Therapy among tertiary schools in Davao City.

Conceptual Paradigm:

Research Design: Descriptive - Comparative

Statistical Analysis: Analysis of Variance (ANOVA) for Parametric Test*; Kruskal Wallis for Nonparametric test

Instrument: Licensure examination result

*The following assumptions should be fulfilled first before using Parametric Test:

1. Homogeneity of variance.

2. The sampling distribution of the means should be normally distributed. 

                                                            

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Also Read

 How to Transform Data for Normality

 Descriptive-Correlation Research Design