For more details tap Learn More. 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.
To that end, various approaches, tools and methodologies aimed at gathering or collecting data have been formulated. Whether it is business, marketing, humanities, physical sciences, social sciences, or other fields of study or discipline, data plays a very important role, serving as their respective starting points.
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.
Depending on the discipline or field, the nature of the information being sought, and the objective or goal of users, the methods of data collection will vary.
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. 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: 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. The first question that we will address is: Learning and building knowledge is a natural inclination for human beings. Even at a very young age, we are in search for answers to a lot of things. Take a look at toddlers and small children, and they are the ones with so many questions, their curious spirit driving them to repeatedly ask whatever piques their interest.
A toddler curious about a white flower in the backyard will start collecting data. He will approach the flower in question and look at it closely, taking in the color, the soft feel of the petals against his skin, and even the mild scent that emanates from it. He will then run to his mother and pull her along until they got to where the flower is. And now the little boy even has a name for it.
Suddenly, he felt a prickle in his fingers, followed by a sharp pain that made him yelp. When he looked down at his palm, he saw two puncture marks, and they are bleeding. The little boy starts to cry, thinking how roses, no matter how pretty and good-smelling, are dangerous and can hurt you. The same goes in case of a marketing research, for example.
A company wants to learn a few things about the market in order to come up with a marketing plan, or tweak an already existing marketing program. Leaders cannot make decisive strategies without facts to support them.
Planners cannot draw up plans and designs without a basis. Entrepreneurs could not possibly come up with a business idea — much less a viable business plan — out of nothing at all. All that decision-makers are left with is their intuition and gut feeling , but even gut feeling and instinct have some basis on facts.
Decision-making processes become smoother, and decisions are definitely better, if there is data driving them. In business, one of the most important decisions that must be made is on resource allocation and usage. If they collect the relevant data, they will be able to make informed decisions on how to use business resources efficiently.
Just as having data will improve decision-making and the quality of the decisions, it will also improve the quality of the results or output expected from any endeavor or activity. For example, a manufacturer will be able to produce high quality products after designing them using reliable data gathered.
Consumers will also find the claims of the company about the product to be more reliable because they know it has been developed after conducting significant amount of research. Through collecting data, monitoring and tracking progress will also be facilitated. This gives a lot of room for flexibility, so response can be made accordingly and promptly.
Adjustments can be made and improvements effected. The most common approach to doing quantitative market research is a survey or questionnaire. Surveys can include interviews, which can be carried out using several different methodologies including face-to-face, telephone, online or computer assisted interviews. What is quantitative research? Quantitative research is a structured way of collecting and analyzing data obtained from different sources.
Quantitative research involves the use of computational, statistical, and mathematical tools to derive results. It is conclusive in its purpose as it tries to quantify the problem and understand how prevalent it is by looking for projectable results to a larger population.
Both types of research vary widely in not only their results, but all other aspects as well. While qualitative data provides a subjective overview of marketing problems, quantitative defines a structured cause-and-effect relationship between the problem and factors.
For example, a quantitative data collection methodology such as a sample survey of high school students who participated in a special science enrichment program can yield data obtained through qualitative research to be more trustworthy and informative. A particular case in point is the use of traditional test results.
Data Collection is an important aspect of any type of research study. Inaccurate data collection can impact the results of a study and ultimately lead to invalid results. The Quantitative data collection Regardless of the kinds of data involved,data collection in a qualitative study takes a great deal of mihtorg.ga researcher needs to.
Quantitative data collection may include ANY method that will result in numerical values. Common examples of quantitative data collection strategies may include: Data Colection – Quantitative Research – This resources provides links to information relating to a variety of ways to collect quantitative data. Overview of Qualitative And Quantitative Data Collection Methods Much of the workings of the world today are controlled and powered by information, giving credence to that famous quote, “information is power”.
Quantitative research can be described as ‘entailing the collection of numerical data and exhibiting the view of relationship between theory and research as deductive, a predilection for natural science approach, and as having an objectivist conception of social reality’. In other words, quantitative studies mainly examine relationships. Quantitative methods emphasize objective measurements and the statistical, mathematical, or numerical analysis of data collected through polls, questionnaires, and surveys, or by manipulating pre-existing statistical data using computational techniques. Quantitative research focuses on gathering.