5 Examples of Quantitative Research Methods & When to Use Them

Quantitative research is a systematic investigation that focuses on collecting and analyzing numerical data to answer research questions. It involves the use of statistical methods to quantify relationships, patterns, and trends within the data. This type of research aims to be objective and generalizable, often seeking to establish cause-and-effect relationships or test hypotheses.

Key Characteristics of Quantitative Research:

• Numerical Data: Quantitative research relies on the collection of numerical data, which can be measured and analyzed using statistical tools. This data can come from various sources, such as surveys, experiments, or existing databases.

• Statistical Analysis: The use of statistical analysis is central to quantitative research. Statistical methods allow researchers to analyze and interpret numerical data, identify patterns, and draw conclusions about the relationships between variables.

• Objectivity: Quantitative research strives for objectivity by minimizing researcher bias and focusing on measurable data. The use of standardized instruments and procedures helps to ensure that data collection and analysis are consistent and unbiased.

Bias exists in all research. It is your job as the researcher to expect it, to know where and how to find it, and to offer recommendations and interpretations for it. Be wary of research that isn’t transparent about potential bias, errors, and weaknesses.

-  Annie Pettit, Independent Insights Consultant, AP Consulting 

Why is Quantitative Research Important?

Quantitative research is essential for various fields. Businesses use it to understand markets and customers; healthcare uses it for evidence-based practices; social sciences use it to study societal behaviors; and education uses it to evaluate teaching methods and student performance.

Quantitative research uses numerical data to reach valuable conclusions. Organizations can make objective, data-driven decisions and improve outcomes using this method.

“Quantitative research is inherently no more nor less important than qualitative research. In fact, great researchers strive to incorporate both so as to generate a deeper and more complete understanding of human behavior”, explains Annie Pettit, Independent Insights Consultant, AP Consulting, who we reached out to for this piece. 

Annie continues by saying “Similarly, there is no firm rule that qualitative research must precede quantitative research nor vice versa. The type of research you begin with depends on the research problem at hand. If you must understand an issue so you can measure it, then qual must come first. But if you need to see how important an issue is for a range of target audiences before you delve into understanding specific groups, then quant must come first.”

On the other hand, James Redden, CEO APAC/US at 2CV, describes quantitative research as important in order to generalize about a wider population. He further explains, “while qualitative research is crucial for understanding the issues and play and why people may behave or think a certain way, only strong quantitative research with sizeable sample sizes can provide companies with an accurate understanding of a whole market or segment – this hence gives clients the confidence to move forward with decisions.”

What Are the 5 Examples of Quantitative Research Methods?

1. Survey Research (Questionnaires, online polls)

Surveys, conducted via questionnaires, online polls, or interviews, are essential research tools. They enable researchers to collect diverse data on various topics from different populations. Questionnaires ensure standardized data collection, while online polls offer broader reach. Interviews, though time-consuming, provide deeper insights.

When to Use?

Surveys are an efficient way to collect data from many people, making them particularly useful for gathering information on opinions, behaviors, and experiences surrounding a specific topic. For example, a company launching a new product could use surveys to gauge potential customer interest and preferences.

Best Scenarios

Questionnaires offer flexible formats (structured or open-ended), making them suitable for diverse research objectives but can be time-consuming. Online polls, with closed-ended questions, are quick and easy, resulting in high engagement but limited depth.

Practical Examples for Different Industries 

Surveys can be used in a variety of ways across different industries. Hospitals can leverage surveys to enhance patient care by assessing their satisfaction with the services and facilities provided. Educational institutions can collect student feedback through polls to improve their courses and programs.  Retail businesses can make informed decisions about inventory and marketing strategies by understanding customer preferences through surveys.

Limitations and Strengths of Survey Research

Questionnaires offer detailed insights but can be time-consuming to analyze and require careful design. Online polls are quicker and easier, but may lack depth and can have accessibility issues. Consider the pros and cons of each method before choosing.

2. Experimental Research (Controlled experiments, A/B testing)

Experimental research is a type of quantitative research method that involves manipulating one variable to determine if it causes a change in another variable, typically conducted in controlled settings to establish cause-and-effect relationships.

Redden at 2CV, declares his love for experimental approaches to research by explaining how it “provides insights into how a certain stimulus (e.g., an advertisement or brand logo) influences how a customer thinks (e.g., likelihood to purchase), but without asking them directly.” 

He continues by adding, “This is a solid method to understand how stimulus genuinely affects the outcomes you are looking for, and avoids the potential pitfalls of asking people directly, which is prone to bias, as sometimes what we say does not align with our actual behavior.”

When to Use?

Experimental research is used to establish cause-and-effect relationships by controlling variables and observing the effects of specific changes. It is ideal for testing hypotheses and understanding how modifying one aspect impacts outcomes.

Best Scenarios

Controlled experiments, often lab-based, allow precise manipulation of variables, but may not reflect real-world complexity. A/B testing, used online, compares two versions of a product to optimize performance, but external factors can influence results. The choice between the two depends on research goals, desired control, and context.

Practical Examples for Different Industries 

Tech companies use A/B testing for website layout changes, healthcare companies use controlled experiments for new drug testing, and education sectors use A/B testing to compare online learning platforms.

Limitations and Strengths of Experimental Research

Controlled experiments reliably establish causal relationships due to their controlled environment, but their findings may not generalize to broader contexts. A/B testing is applicable to real-world scenarios and allows for quick adjustments, but external variables and inadequate sample sizes can lead to inconclusive results.

3. Correlational Research (Examining Relationships Between Variables)

Correlational research is a type of research that seeks to understand the connection or relationship between two or more variables. This method is particularly useful when you want to examine how changes in one variable might relate to changes in another. 

When to Use?

Researchers often use correlational research when it is not feasible or ethical to conduct experiments. For instance, if you are interested in studying the relationship between physical activity levels and heart health, you might use a correlational approach to gather data about individuals’ exercise habits and their heart-related health metrics without interfering with their lifestyles.

Best Scenarios 

Correlational research is best used to explore relationships in existing data or when ethical concerns prevent experimentation. For example, researchers could examine the link between stress and sleep quality using survey data, as inducing high stress would be unethical.

Practical Examples in Different Industries

Examples of correlational research include the relationship between attendance and grades in education, the correlation between ad spending and sales in marketing, and the connection between temperature and ice melt in environmental science.

Strengths and Limitations of Correlational Research

Correlational research can quickly identify relationships between variables, often using pre-existing data. However, correlation does not imply causation, and results can be misleading due to outliers or confounding variables.

"while qualitative research is crucial for understanding the issues and play and why people may behave or think a certain way, only strong quantitative research with sizeable sample sizes can provide companies with an accurate understanding of a whole market or segment" 

- James Redden, CEO APAC/US at 2CV

4. Longitudinal Research (Tracking data over time)

Longitudinal research is a valuable method used in various fields to collect data over an extended period. This approach enables researchers to observe changes, developments, and trends that occur over time. 

When to Use?

Longitudinal research tracks changes over time. It's used in medical studies to assess disease progression or treatment effectiveness, in education to track student performance, and in social sciences to understand shifts in public opinion or behaviors.

Best Scenarios

Longitudinal research is ideal for studying long-term effects. For example, it can be used in healthcare to study the long-term effects of new medications, in education to assess the impact of early childhood interventions on academic success, and in market research to track consumer purchasing behavior over time.

Practical Examples in Different Industries

Different industries utilize longitudinal research to address their unique needs. In public health, researchers might conduct a longitudinal study on smoking behavior among adolescents to understand how habits evolve from teenage years into adulthood. In education, a study might follow students from primary school through high school to assess how their attitudes towards learning change. In the field of marketing, companies could conduct longitudinal surveys on customer satisfaction to measure how their perceptions of a brand evolve over time.

Strengths and Limitations of Longitudinal Research

Longitudinal studies, like all research methods, have both advantages and disadvantages. A major strength is their ability to track trends over time, offering a deeper understanding of changes compared to cross-sectional studies. They also allow researchers to create timelines and examine how changes in one variable may affect another.

Longitudinal research can be expensive, time-consuming, and challenging to maintain over extended periods. Participants may drop out, impacting the data's validity. Additionally, external factors can influence results, making it difficult to pinpoint the effects of specific variables.

5. Descriptive Research (Analyzing Trends and Statistical Summaries)

Descriptive research is a method that is particularly useful when one wishes to gain a clear understanding of a particular phenomenon or to identify patterns within data. 

When to Use?

This method is most appropriate when the goal is to summarize and describe the characteristics of a specific population or situation without attempting to make predictions or establish cause-and-effect relationships. It is ideally used in situations where you want to gather comprehensive data that highlights existing trends or behaviors.

Best Scenarios

Descriptive research is used to analyze trends and prevalence within a specific context. A retail company could use it to analyze customer purchasing trends, or a health organization could use it to assess the prevalence of certain health conditions.

Practical Examples in Different Industries

Descriptive research can identify patterns and trends. For example, schools can use it to track student performance, and businesses can use it to understand customer demographics and create targeted advertising.

Strengths and Limitations of Descriptive Research

Descriptive research provides a broad overview of a topic, revealing trends and patterns. It's simpler than experimental designs, but can't determine causality and may be affected by sample size or selection bias.