Overview of Quantitative Research.pdf

Overview of Quantitative Research Practical Research 2 Jeffrey P. Paris Quantitative research is a systematic investigation that primarily focuses on quantifying relationships, behaviors, or phenomena through statistical, mathematical, or computational techniques. This method i...

Overview of Quantitative Research Practical Research 2 Jeffrey P. Paris Quantitative research is a systematic investigation that primarily focuses on quantifying relationships, behaviors, or phenomena through statistical, mathematical, or computational techniques. This method is widely used in various fields, including social sciences, health sciences, and market research, to objectively measure variables and analyze numerical data to derive conclusions or test hypotheses (Creswell, 2014). Creswell, J. W. (2014). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches. SAGE Publications.  Overall Goal Confirm or test Quantitative theory or hypothesis Understand Qualitative or explore idea  Hypothesis Quantitative It incorporates the use of a hypothesis. Qualitative It does not involve the use of a hypothesis.  Analysis Quantitative Qualitative Analyzed through the use Analyzed through of statistical methods such summarizing, categorizing, as Spearman’s Rho, and interpreting. Pearson’s R, ANOVA, Chi- (Thematic Analysis). Square, etc.  Samples Quantitative Qualitative It does not It requires a large require a large number of number of respondents. participants.  Instrument It utilizes closed-ended Quantitative questions. It employs open-ended Qualitative questions.  Key Characteristics of Quantitative Research  Objective Measurement Quantitative research aims for objectivity using instruments and procedures that produce reliable and replicable data. This helps minimize researcher bias (Creswell, 2014).  Structured Tools It employs structured research instruments such as surveys, questionnaires, and tests to gather quantifiable data. These tools ensure consistency and accuracy in data collection (Bryman, 2016).  Large Sample Sizes Quantitative studies often involve large sample sizes to ensure that the findings are generalizable to a larger population. This enhances the external validity of the research (Polit & Beck, 2017).  Statistical Analysis The data collected are subjected to statistical analysis to identify patterns, relationships, or trends. Statistical methods help in testing hypotheses and making inferences about the population (Babbie, 2010).  Hypothesis Testing Quantitative research is often hypothesis-driven. Researchers begin with a specific hypothesis and use statistical methods to test its validity (Kerlinger & Lee, 2000).  Replication The structured methodology of quantitative research allows for replication of the study by other researchers, which is essential for verifying results and establishing reliability (Neuman, 2014).  Data Presentation Results are typically presented in the form of tables, graphs, and charts. This visual representation helps in summarizing and interpreting the data effectively (Creswell, 2014).  Generalizability Due to the use of random sampling and large sample sizes, the findings from quantitative research can often be generalized to the larger population from which the sample was drawn (Polit & Beck, 2017).  Types of Quantitative Research Non-experimental Experimental Descriptive True Experimental Quasi- Correlational Experimental Causal-Comparative Non-experimental Research Non-experimental quantitative research designs involve collecting numerical data without manipulating variables. These methods are used to describe characteristics, determine relationships, and make comparisons among variables.  The Art of Observation: Descriptive Research Aims to accurately and systematically describe a population, situation or phenomenon Aims to describe characteristics of functions of a specific group or phenomenon without manipulating variables  The Art of Observation: Descriptive Research When to use: 1. When the goal is to provide a detailed description of a phenomenon or population. 2. When you need to gather information on the current status or characteristics of subjects. 3. When exploring new areas where not much information is available, and you need to establish a baseline.  The Art of Observation: Descriptive Research A study describing the eating habits of teenagers in urban areas. Researchers might collect data on what teens eat, when they eat, and how much they consume, without trying to change their behavior. A study describing the percentage of students who prefer online learning versus in-person classes.  The Art of Observation: Descriptive Research Surveying students to determine their study habits. Observing classroom behaviors to describe teaching methods. Assessing the demographic characteristics of a population. Describing the average levels of stress among employees in a company.  Connecting the Dots: CORRELATIONAL RESEARCH Seeks to determine the relationship between two or more variables, examining whether and how they change without manipulating them. When the objective is to determine if there is a relationship between two or more variables.  Connecting the Dots: CORRELATIONAL RESEARCH A study investigating the relationship between hours spent on social media and levels of anxiety in young adults. Researchers might find a correlation, but they can't conclude that one causes the other. Investigating whether there's a relationship between the number of hours spent studying and exam scores. Studying the relationship between study habits and academic performance.  Connecting the Dots: CORRELATIONAL RESEARCH Studying the correlation between hours spent studying and academic performance. Investigating the relationship between physical activity and mental health. Examining the relationship between socioeconomic status and academic achievement. Predicting job satisfaction based on work environment factors.  The "What If" Approach: CAUSAL-COMPARATIVE RESEARCH Ex Post Facto Research Seeks to identify cause-and-effect relationships by comparing groups that differ on a particular variable, with the difference being the effect of some previously occurring cause. To explore cause-and-effect relationships by comparing groups that differ on a certain variable of interest.  The "What If" Approach: CAUSAL-COMPARATIVE RESEARCH A study comparing the academic performance of students who attended preschool versus those who didn't. Researchers can't go back in time to randomly assign preschool attendance, but they can analyze existing data to infer potential effects. Suppose you notice that students who eat breakfast regularly tend to have better grades. A causal-comparative study might investigate whether breakfast is causing better grades, or if there's something else at play.  The "What If" Approach: CAUSAL-COMPARATIVE RESEARCH Examining why students who participate in extracurricular activities tend to have higher GPAs than those who don’t. Comparing the academic performance of students who attended different types of pre-school programs. Investigating the effects of different diets on health outcomes by comparing groups with different dietary habits.  The "What If" Approach: CAUSAL-COMPARATIVE RESEARCH Investigating the impact of different teaching methods on student achievement by comparing classes taught with different approaches. Examining the effects of smoking on lung capacity by comparing smokers and non-smokers. Investigating the impact of childhood trauma on adult mental health by comparing adults with and without trauma histories. Examining the differences in educational outcomes between students who attended public vs. private schools. Comparing the Effectiveness of Group Work Versus Individual Study on Students' Understanding of Complex Subjects  The Influence of Reading Habits on Critical Thinking Skills Among Senior High School Students The Role of Procrastination in Increasing Stress Levels Among HUMSS Students  The Effect of Different Teaching Styles on Students' Motivation and Engagement Levels Investigating the Impact of School Uniforms on Students' Academic Performance and Discipline The Effect of Implementing a School Wellness Program on Students' Physical and Mental Health  Analyzing the Impact of Different Study Techniques on Exam Performance Among High School Students The Relationship Between Social Media Usage and Academic Performance Among Senior High School Students Exploring the Correlation Between Students' Use of Educational Technology and Their Learning Outcomes Examining the Relationship Between Parental Involvement and Students' Self-Efficacy Non-experimental Experimental Descriptive True Experimental Quasi- Correlational Experimental Causal-Comparative  Experimental Research An experiment is a procedure carried out to support, refute, or validate a hypothesis. This type of research involves the manipulation of one variable (independent variable) to determine its effect on another variable (dependent variable) while controlling for other potential variables that might influence the outcome.  Experimental Research A study conducted with a scientific approach using two sets of variables. The first set acts as a constant (controlled group), which you use to measure the differences of the second set (experimental group). A true experimental design is a type of research that seeks to establish cause- and-effect relationships by manipulating one or more independent variables and observing the effect on one or more dependent variables while controlling for other potential variables. True Experimental Design Key Features: 1. Random Assignment: Participants are randomly assigned to either the experimental group or the control group. This helps ensure that any differences observed are due to the manipulation of the independent variable and not other factors. 2. Control Group: A group that does not receive the experimental treatment or receives a standard treatment for comparison. Key Features: 3. Manipulation: The researcher actively manipulates the independent variable to observe its effect on the dependent variable. 4. Control of Confounding Variables: Efforts are made to control other variables that could influence the outcome, ensuring that the observed effects are due to the manipulation of the independent variable.  A study investigating the effect of a new teaching method on student performance where students are randomly assigned to either the new method group or a traditional method group. A quasi-experimental design resembles an experimental design but lacks random assignment. This type of design is often used when random assignment is not feasible or ethical. Quasi-Experimental Design Key Features: 1. No Random Assignment: Participants are not randomly assigned to groups. Instead, existing groups or naturally occurring groups are used. 2. Comparison Group: Similar to the control group in true experiments, but the groups may not be equivalent at the start due to the lack of random assignment. Key Features: 3. Manipulation: The independent variable is still manipulated, but the lack of random assignment makes it harder to rule out confounding variables. 4. Control of Confounding Variables: Researchers attempt to control for confounding variables, but this control is typically less rigorous than in true experimental designs. A study examining the impact of a new curriculum in two different schools where one school adopts the new curriculum and the other continues with the standard curriculum without randomly assigning students to schools.  Feature True Experimental Quasi-Experimental Random Assignment Yes No Yes (comparison Control Group Yes group) Manipulation Yes Yes Control of Confounding High control Lower control Variables Internal Validity Higher Lower