Data collection in quantitative research

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Data collection in quantitative research

But information is not something that is handed to anyone on a silver platter. It starts with a small raw fact or figure — or a set of raw facts and figures — that are not organized and, all too often, without meaning or context.

Data collection in quantitative research

By itself, and in its raw form, data may seem useless. Data will cease to be useless once it undergoes processing, where it will be organized, structured and given context through interpretation and analysis. Processing gives it meaning, effectively turning it into information that will eventually be of great use to those who need it.

Collectively, all information will make up bodies of knowledge that will, in turn, benefit various users of this knowledge. Therefore, no matter how data may seem random and useless, it is actually considered to be the most important and basic unit of any information structure or body of knowledge.

That is why, in all of these processes that involve the usage of information and knowledge, one of the very first steps is data collection. The approach to applying the methods may also vary, customized to suit the purpose and prevailing circumstances, without compromising the integrity, accuracy and reliability of the data.

There are two main types of data that users find themselves working with — and having to collect.

DATA COLLECTION METHODS

These are data that deal with quantities, values or numbers, making them measurable. Thus, they are usually expressed in numerical form, such as length, size, amount, price, and even duration. The use of statistics to generate and subsequently analyze this type of data add credence or credibility to it, so that quantitative data is overall seen as more reliable and objective.

These data, on the other hand, deals with quality, so that they are descriptive rather than numerical in nature. Unlike quantitative data, they are generally not measurable, and are only gained mostly through observation.

Quantitative and Qualitative Data collection methods

Narratives often make use of adjectives and other descriptive words to refer to data on appearance, color, texture, and other qualities.

In most cases, these two data types are used as preferences in choosing the method or tool to be used in data collection. As a matter of fact, data collection methods are classified into two, and they are based on these types of data.

Thus, we can safely say that there are two major classifications or categories of data collection methods: But for many, that still does not mean much. Depending on the perspective of the user and the purpose of the information, there are many concrete benefits that can be gained from data gathering.

In general terms, here are some of the reasons why data collection is very important.This part of our detailed tutorial on market research planning looks at a type of primary research called quantitative data collection where research is often formal and structured and data is gathered in numerical form and thus can be analyze using statistical methods.

Data collection methods for impact evaluation vary along a continuum. At the one end of this continuum are quantatative methods and at the other end of the continuum are .

DATA COLLECTION METHODS

Quantitative Data Collection Methods Data can be readily quantified and generated into numerical form, which will then be converted and processed into useful information mathematically.

The result is often in the form of statistics that is meaningful and, therefore, useful. Chapter 13, “Data Collection in Quantitative Research” Once a sampling design is complete, the next step is to collect the data, and this is the focus of Chapter The chapter describes how to develop a data collection plan, and provides information about the different types of instruments that can be used, such as structured observation.

Data collection in quantitative research

Quantitative Data. This module describes quantitative data and examines common methods of data collection in quantitative studies.

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Learning Objectives: Define quantitative data and its characteristics. Explain the difference between discrete and continuous data. List examples of quantitative data.

Describe common methods of quantitative data . This is a research or data collection method that is performed repeatedly, on the same data sources, over an extended period of time. It is an observational research method that could even cover a span of years and, in some cases, even decades.

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