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Table of Contents

- What is quantitative research easy definition?
- What is quantitative research with examples?
- Why is it a quantitative research?
- What makes a good quantitative research?
- How do you do quantitative research?
- Why quantitative research is reliable?
- What are some examples of quantitative?
- What are two examples of quantitative research?
- How can quantitative data be collected?
- Which of these is an example of quantitative data?
- Whats does quantitative mean?
- What are 2 examples of qualitative data?
- What are two types of quantitative data?
- What is quantitative data used for?
- How do you interpret quantitative data?
- How do you interpret survey results in quantitative research?
- What are the advantages of quantitative data?

Quantitative research is the process of collecting and analyzing numerical data. It can be used to find patterns and averages, make predictions, test causal relationships, and generalize results to wider populations.

Quantitative research collects information from existing and potential customers using sampling methods and sending out online surveys, online polls, questionnaires, etc., the results of which can be depicted in the form of numerical.

The purpose of quantitative research is to generate knowledge and create understanding about the social world. Quantitative research is used by social scientists, including communication researchers, to observe phenomena or occurrences affecting individuals. Social scientists are concerned with the study of people.

Its main characteristics are: The data is usually gathered using structured research instruments. The results are based on larger sample sizes that are representative of the population. The research study can usually be replicated or repeated, given its high reliability.

The main methods used in quantitative research are:

- Survey. Survey methods collects data gathered from responses given by the participants through questionnaires.
- Tracking.
- Experiments.
- Structured interviews.
- Validity.
- Internal validity.
- External validity.
- Lack of detail.

Pertinent in later stages of research: Quantitative research is usually recommended in later stages of research because it produces more reliable results. Consistent with data: With quantitative research, you may be getting data that is precise, reliable and consistent, quantitative and numerical.

Quantitative Information – Involves a measurable quantity—numbers are used. Some examples are length, mass, temperature, and time. Quantitative information is often called data, but can also be things other than numbers. Qualitative Information – Involves a descriptive judgment using concept words instead of numbers.

Quantitative data collection methods include various forms of surveys – online surveys, paper surveys, mobile surveys and kiosk surveys, face-to-face interviews, telephone interviews, longitudinal studies, website interceptors, online polls, and systematic observations.

There are several methods by which you can collect quantitative data, which include:

- Experiments.
- Controlled observations.
- Surveys: paper, kiosk, mobile, questionnaires.
- Longitudinal studies.
- Polls.
- Telephone interviews.
- Face-to-face interviews.

Here are some example of quantitative data: A jug of milk holds one gallon. The painting is 14 inches wide and 12 inches long. The new baby weighs six pounds and five ounces.

1 : of, relating to, or expressible in terms of quantity. 2 : of, relating to, or involving the measurement of quantity or amount. 3 : based on quantity specifically, of classical verse : based on temporal quantity or duration of sounds.

Examples of qualitative data include sex (male or female), name, state of origin, citizenship, etc. A more practical example is a case whereby a teacher gives the whole class an essay that was assessed by giving comments on spelling, grammar, and punctuation rather than score.

There are two types of quantitative data, which is also referred to as numeric data: continuous and discrete. As a general rule, counts are discrete and measurements are continuous. Discrete data is a count that can’t be made more precise. Typically it involves integers.

Quantitative data are used when a researcher is trying to quantify a problem, or address the “what” or “how many” aspects of a research question. It is data that can either be counted or compared on a numeric scale.

Identification. Quantitative data interpretation includes studying the results from various questions in a survey. The results are usually displayed numerically and by percentage in the data tables. For example, a small company may conduct a customer satisfaction survey by phone.

How to Analyze Survey Results

- Understand the four measurement levels.
- Select your research question(s).
- Analyze quantitative data first.
- Use cross-tabulation to better understand your target audience.
- Understand the statistical significance.
- Take into consideration causation versus correlation.

Quantitative Research Pros: Larger sample: A broader study can be made, involving more subjects and enabling more generalization of results. Objectivity and accuracy: Few variables are involved as data relates to close-ended information.