IndexLiterature ReviewQuantitative Analysis of School Dropout RateConclusionLiterature ReviewCounseling research helps in shaping our society, from the way we raise our children to the way we treat our criminals and military enemies. Counselors in schools often offer counseling programs in three essential areas; academic, personal or social, as well as professional. The counseling services and programs offered enable students to seek solutions to their emotional, social or behavioral problems, develop clear concentration and a sense of direction. Effective counseling programs are not only important to the school environment but also act as an essential element in improving students' academic performance (American Counseling Association, n.d.). Just like all other education professionals, school counselors are indispensable in demonstrating effective testing practice. Say no to plagiarism. Get a tailor-made essay on "Why Violent Video Games Shouldn't Be Banned"? Get an Original Essay Some of the achievements of both school counselor and students in counseling programs include; positive influence on students' academic performance, reduction of students' test anxiety, reduction of dropout rate, reduction of classroom disorder. For example, a consulting study conducted in a Missouri high school shows that schools that implemented model orientation programs resulted in their students earning higher grades, that their teaching program was effective in preparing students for their future and that their environment was conducive to learning (American Counseling Association , n.d.). This article examined counseling research and program evaluation conducted in schools to determine the effectiveness of counseling programs in schools. Simply put, quantitative research refers to the generation of numerical data or information that can be numerically transformed into numbers. For example, to determine the influence of the counseling program on the school dropout rate. Qualitative research, on the other hand, refers to the generation of non-numerical data. For example, to determine the influence of the counseling program on the level of student discipline. The main objective of qualitative research is to offer a complete and exhaustive explanation of the effects of counseling in schools (Explorable.com, 2009), while the main objective of quantitative research is to focus more on counting and classifying characteristics and building statistical models. and illustrations to clarify the observations made. Sampling is one of the data collection methods that can be applied in this consultancy research. Sampling refers to a subset of the population, selected using “probability” or “non-probability” methods (Ladner.S, 2008). Both qualitative and quantitative research methods can apply sampling in their studies; however, the application method is different in both. Research that is qualitative in nature often uses non-probability sampling methods where the researcher aims for a detailed idiographic understanding as opposed to a more general nomothetic understanding (Blackstone.A, n.d.). Non-probability sampling can be defined as methods for which the chances of a person being selected to become a member of a sample are still uncertain (Blackstone.A, n.d.). Some of the types of non-probability sampling methods include;purposive sampling, snowball sampling, quota sampling and convenience sampling. On the other hand, quantitative researchers use probability sampling in their studies. In probability sampling, the probabilities of a person being selected to form members of the sample are known (Saylordorg.github, n.d.). There are several probability sampling techniques; random sampling, systematic sampling, stratified sampling and cluster sampling. The researcher's goal is to make generalizations about groups that are large compared to the study samples. Generalization in this case refers to the idea that the results of a study will tell us something about a larger group than the sample from which the results were obtained (Saylordorg.github, n.d.). Therefore, quantitative sampling is more interested in numbers while qualitative sampling is more interested in deep understanding of the study phenomenon. Both deductive and inductive reasoning are distinct approaches that can be applied when conducting scientific research. In deductive reasoning, quantitative researchers conduct a test of a theory by collecting and evaluating empirical evidence to see whether it is true or not. For example, starting a school counseling program leads to improved student achievement. On the other hand, in inductive reasoning qualitative researchers begin with data collection and analysis, then build a theory to explain the research findings (Crossman. A, 2017). For example, improved student performance is the result of initiating a school counseling program. According to Dr. Deborah Gabriel, 2013, the deductive approach often begins with a hypothesis while the inductive approach uses research findings to narrow the scope of study. From the literature review, an example of a qualitative effect is the influence of school counseling programs on academic studies. performance, level of discipline of students and test anxiety in students, i.e. non-numerical data. On the other hand, an example of the quantitative effect of school counseling programs is the reduction of student dropout rate, that is, numerical data. Researchers can apply qualitative research methods in this counseling research. This is because in qualitative research, literature review is used in providing evidence for the purpose of the study with the aim of identifying the underlying problem to be addressed in the research topic. To effectively examine the effectiveness of the school counseling program on student achievement, a detailed understanding of the phenomenon and sufficient learning from the population sample, coupled with qualitative research designs, is required. Data was collected through observations, notes, interviews and tabulations. . Qualitative data usually involved non-numerical information such as; improved academic performance, improvements in anxiety tests, improved student discipline levels and reduced classroom disruption. On the other hand, quantitative data involved numerical information such as; number of students who improved their academic performance, reduced the dropout rate and percentage scores of students on exams. The following tables show examples of data collected from the research. Content analysis refers to the procedure of categorizing verbal and nonverbal data, with the goal of classifying, summarizing, and tabulating the data (Surrey, n.d.). It involves coding and classifying data in order to make sense of the data collected and to highlight significant information, characteristics and research findings. The analysis of.