What makes quantitative research reliable

For example, if one of the instruments measures anxiety and the other instrument measures IQ level then there will be divergence. The entire research process should establish validity. This is important in order to ensure the capability of the instrument survey, interview, etc.

Notify me of follow-up comments by email. Sign in. Importance of determining validity in a research Traditionally, the establishment of instrument validity was limited to the sphere of quantitative research.

Construct validity and construction of an initial concept For example, the construct validity would determine whether the subject has high anxiety score in a survey. Further, it uses three different parameters to check validity: Homogeneity; research instrument measures one construct such as anxiety levels. Convergence; the research instrument measures concepts which are similar to other instruments, in order to determine the convergence is results. Theoretical evidence; when the findings are in sync with the theoretical evidence.

Determining the required variable with content validity For example, to determine the anxiety level on different parameters the content validity helps to determine the role of every factor that contributes towards anxiety. Criterion validity in comparing different measuring instruments Criterion validity helps to review the existing measuring instruments against other measurements. The following table show different validity applied in research. Determining validity in quantitative research Source: Drost, ; p Offer ID is invalid The entire research process should establish validity.

References Creswell, J. Determining Validity in Qualitative Inquiry. Theory Into Practice , 39 3 , pp. Drost, E. Validity and Reliability in Social Science Research. Education Research and Perspectives , 38 1 , pp. Fraser, S. Coping with complexity: educating for capability. BMJ , , pp. Glyn Winter, The Qualitative Report , 4 4. Kothari, C. Research Methodology: An introduction. In Research Methodology: Methods and Techniques. Leung, L. Validity, reliability, and generalizability in qualitative research.

Journal of family medicine and primary care , 4 3 , pp. Lincoln, Y. Following are five popularly used secondary quantitative research methods:. Some distinctive characteristics of quantitative research are:. There are many advantages of quantitative research. Some of the major advantages of why researchers use this method in market research are:. Here are some best practices to conduct quantitative research. Though you're welcome to continue on your mobile screen, we'd suggest a desktop or notebook experience for optimal results.

Survey software Leading survey software to help you turn data into decisions. Research Edition Intelligent market research surveys that uncover actionable insights. Customer Experience Experiences change the world. Deliver the best with our CX management software.

Workforce Powerful insights to help you create the best employee experience. What is quantitative research? Gather research insights Quantitative outcome research is mostly conducted in the social sciences using the statistical methods used above to collect quantitative data from the research study.

They are: Primary quantitative research methods Secondary quantitative research methods Primary quantitative research methods There are four different types of quantitative research methods: Primary quantitative research is the most widely used method of conducting market research.

They are: A. Techniques and Types of Studies There are multiple types of primary quantitative research. They can be distinguished into the four following distinctive methods, which are: Survey Research: Survey Research is the most fundamental tool for all quantitative outcome research methodologies and studies. There are two types of surveys , either of which can be chosen based on the time in-hand and the kind of data required: Cross-sectional surveys: Cross-sectional surveys are observational surveys conducted in situations where the researcher intends to collect data from a sample of the target population at a given point in time.

Cross-sectional surveys are popular with retail, SMEs, healthcare industries. Information is garnered without modifying any parameters in the variable ecosystem. Using a cross-sectional survey research method, multiple samples can be analyzed and compared. Multiple variables can be evaluated using this type of survey research. The only disadvantage of cross-sectional surveys is that the cause-effect relationship of variables cannot be established as it usually evaluates variables at a particular time and not across a continuous time frame.

In cross-sectional surveys, the same variables were evaluated at a given point in time, and in longitudinal surveys, different variables can be analyzed at different intervals of time. Longitudinal surveys are extensively used in the field of medicine and applied sciences. In situations where the sequence of events is highly essential, longitudinal surveys are used. Researchers say that when there are research subjects that need to be thoroughly inspected before concluding, they rely on longitudinal surveys.

Correlational research: A comparison between two entities is invariable. Example of Correlational Research Questions: The relationship between stress and depression.

The equation between fame and money. The relation between activities in a third-grade class and its students. Causal-comparative research: This research method mainly depends on the factor of comparison.

The effect of good education on a freshman. The effect of substantial food provision in the villages of Africa. Experimental research: Also known as true experimentation, this research method is reliant on a theory. Systematic teaching schedules help children who find it hard to cope up with the course. It is a boon to have responsible nursing staff for ailing parents. Gather research insights B. Data collection methodologies The second major step in primary quantitative research is data collection.

Data collection methodologies: Sampling methods There are two main sampling methods for quantitative research: Probability and Non-probability sampling.

There are four main types of probability sampling: Simple random sampling: As the name indicates, simple random sampling is nothing but a random selection of elements for a sample. This sampling technique is implemented where the target population is considerably large.

Stratified random sampling: In the stratified random sampling method, a large population is divided into groups strata , and members of a sample are chosen randomly from these strata. The various segregated strata should ideally not overlap one another. Cluster sampling: Cluster sampling is a probability sampling method using which the main segment is divided into clusters, usually using geographic and demographic segmentation parameters.

Systematic sampling: Systematic sampling is a technique where the starting point of the sample is chosen randomly, and all the other elements are chosen using a fixed interval. This interval is calculated by dividing the population size by the target sample size.

There are five non-probability sampling models: Convenience sampling: In convenience sampling , elements of a sample are chosen only due to one prime reason: their proximity to the researcher. These samples are quick and easy to implement as there is no other parameter of selection involved. Consecutive sampling: Consecutive sampling is quite similar to convenience sampling, except for the fact that researchers can choose a single element or a group of samples and conduct research consecutively over a significant period and then perform the same process with other samples.

Quota sampling: Using quota sampling , researchers can select elements using their knowledge of target traits and personalities to form strata. Snowball sampling: Snowball sampling is conducted with target audiences, which are difficult to contact and get information.

It is popular in cases where the target audience for research is rare to put together. Using surveys for primary quantitative research A Survey is defined as a research method used for collecting data from a pre-defined group of respondents to gain information and insights on various topics of interest.

Fundamental levels of measurement — nominal, ordinal, interval and ratio scales There are four measurement scales that are fundamental to creating a multiple-choice question in a survey. Use of different question types To conduct quantitative research, close-ended questions have to be used in a survey. Survey Distribution and Survey Data Collection In the above, we have seen the process of building a survey along with the survey design to conduct primary quantitative research.

Some of the most commonly used methods are: Email: Sending a survey via email is the most widely used and most effective method of survey distribution. The response rate is high in this method because the respondents are aware of your brand.

You can use the QuestionPro email management feature to send out and collect survey responses. Buy respondents: Another effective way to distribute a survey and conduct primary quantitative research is to use a sample.

Since the respondents are knowledgeable and are on the panel by their own will, responses are much higher. Embed survey on a website: Embedding a survey in a website increases a high number of responses as the respondent is already in close proximity to the brand when the survey pops up.

Social distribution: Using social media to distribute the survey aids in collecting a higher number of responses from the people that are aware of the brand. SMS survey: A quick and time-effective way of conducting a survey to collect a high number of responses is the SMS survey. QuestionPro app: The QuestionPro App allows users to circulate surveys quickly, and the responses can be collected both online and offline. Survey example An example of a survey is short customer satisfaction CSAT survey template that can quickly be built and deployed to collect feedback about what the customer thinks about a brand and how satisfied and referenceable the brand is.

Using polls for primary quantitative research Polls are a method to collect feedback with the use of close-ended questions from a sample. Data analysis techniques The third aspect of primary quantitative research design is data analysis.

Organizations use this statistical analysis technique to evaluate their performance internally and externally to develop effective strategies for improvement. Conjoint Analysis: Conjoint Analysis is a market analysis method to learn how individuals make complicated purchasing decisions.

Cross-tabulation: Cross-tabulation is one of the preliminary statistical market analysis methods which establishes relationships, patterns, and trends within the various parameters of the research study. It is used for understanding the potential of a target market. Secondary quantitative research methods Secondary quantitative research or desk research is a research method that involves using already existing data or secondary data.

However, reliability on its own is not enough to ensure validity. Even if a test is reliable, it may not accurately reflect the real situation. Validity is harder to assess than reliability, but it is even more important.

To obtain useful results, the methods you use to collect your data must be valid: the research must be measuring what it claims to measure. This ensures that your discussion of the data and the conclusions you draw are also valid.

Reliability can be estimated by comparing different versions of the same measurement. Validity is harder to assess, but it can be estimated by comparing the results to other relevant data or theory. Methods of estimating reliability and validity are usually split up into different types. The validity of a measurement can be estimated based on three main types of evidence.

Each type can be evaluated through expert judgement or statistical methods. To assess the validity of a cause-and-effect relationship, you also need to consider internal validity the design of the experiment and external validity the generalizability of the results. Scribbr editors not only correct grammar and spelling mistakes, but also strengthen your writing by making sure your paper is free of vague language, redundant words and awkward phrasing.

See editing example. The reliability and validity of your results depends on creating a strong research design , choosing appropriate methods and samples, and conducting the research carefully and consistently. Validity should be considered in the very earliest stages of your research, when you decide how you will collect your data. Ensure that your method and measurement technique are high quality and targeted to measure exactly what you want to know. They should be thoroughly researched and based on existing knowledge.

For example, to collect data on a personality trait, you could use a standardized questionnaire that is considered reliable and valid. If you develop your own questionnaire, it should be based on established theory or findings of previous studies, and the questions should be carefully and precisely worded.

To produce valid generalizable results, clearly define the population you are researching e. Ensure that you have enough participants and that they are representative of the population. Reliability should be considered throughout the data collection process. Plan your method carefully to make sure you carry out the same steps in the same way for each measurement. This is especially important if multiple researchers are involved. For example, if you are conducting interviews or observations, clearly define how specific behaviours or responses will be counted, and make sure questions are phrased the same way each time.

When you collect your data, keep the circumstances as consistent as possible to reduce the influence of external factors that might create variation in the results. For example, in an experimental setup, make sure all participants are given the same information and tested under the same conditions.

Showing that you have taken them into account in planning your research and interpreting the results makes your work more credible and trustworthy. Have a language expert improve your writing. Check your paper for plagiarism in 10 minutes.

Do the check. Generate your APA citations for free! APA Citation Generator. Reliability vs validity Reliability Validity What does it tell you?