Quantitative methods are a research approach that uses numerical data and statistical analysis to answer research questions. The main objective is to measure variables, test hypotheses, and discover patterns or relationships between variables objectively. This approach is deductive in nature, meaning the researcher starts from a theory or hypothesis and then tests it using data collected in the field.

In practice, quantitative methods are divided into several types depending on the objectives, design, and form of data used. Below is a complete explanation of the various types of quantitative methods.

1. Quantitative Descriptive Method

The quantitative descriptive method aims to describe a phenomenon or the characteristics of a particular population based on numerical data. This research does not aim to test hypotheses but only presents a factual and systematic description of the object being studied.

Data is collected from the population or sample using techniques such as surveys, questionnaires, or structured observations. After that, the data is processed and analyzed using descriptive statistics such as mean, percentage, and standard deviation. This research is widely used to understand characteristics, tendencies, or the frequency of occurrence of a symptom in a particular population.

2. Comparative Method

The comparative method is a quantitative method used to compare two or more groups based on one or more variables. This research aims to determine whether there are significant differences between those groups.

This method relies on inferential statistical techniques such as t-tests, ANOVA, or MANOVA to determine whether there are meaningful differences. It is important in comparative research that the variables being compared are quantitative and can be measured objectively.

3. Correlational Method

The correlational method is used to determine the extent of the relationship or association between two or more variables. The goal is not to find cause and effect, but to measure the strength and direction of the relationship between variables.

The relationship in question can be positive, negative, or no relationship at all. Correlation analysis uses statistical techniques such as Pearson correlation, Spearman correlation, or bivariate correlation. In correlational studies, it is important to note that even though two variables are correlated, it does not mean one causes the other.

Read More : Types of Methods in Qualitative Research

4. Experimental Method

The experimental method is a quantitative method used to determine the cause-and-effect relationship between the independent and dependent variables by giving a specific treatment. The researcher controls and manipulates the independent variable, then observes its impact on the dependent variable.

This method is divided into several designs, such as true experiment (with randomization), quasi-experiment (without randomization), and pre-experiment (without a control group). The experimental method is considered the most valid method to directly and measurably determine the effect of a treatment.

5. Survey Method

The survey method is one form of quantitative approach used to collect data from large samples using instruments such as questionnaires or structured interviews. Surveys can be conducted directly or online and are often used in social, educational, and marketing research.

The main characteristic of the survey method is data collection in large quantities in a relatively short time. Once the data is collected, statistical analysis is conducted to examine trends, distributions, and possible relationships between variables.

6. Regression Method

The regression method is used to predict the value of one variable based on the value of another related variable. Regression not only measures the strength of the relationship between variables but also forms a predictive model that can be used for estimation.

There are various types of regression, such as simple linear regression, multiple linear regression, logistic regression, and others. The choice of regression type depends on the type of variables being studied and the purpose of the analysis.

7. Time Series Method

The time series method is a quantitative approach used to analyze data over a certain time span in sequence. The main goal of this method is to identify patterns, trends, or fluctuations in the data over time.

This approach is very useful for making future predictions (forecasting) and analyzing changes over time. Time series analysis is generally used in economics, business, finance, and climate studies.

Each type of quantitative method has its own uniqueness, advantages, and limitations. Therefore, it is important for researchers to understand the characteristics of each method in order to choose the most appropriate approach according to their research goals and design. Mastery of the appropriate quantitative methods will help produce research that is valid, reliable, and makes a real contribution to the advancement of scientific knowledge.

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