Quantitative and qualitative data collection methods

Of qualitative and quantitative data collection of the workings of the world today are controlled and powered by information, giving credence to that famous quote, “information is power”. By itself, and in its raw form, data may seem will cease to be useless once it undergoes processing, where it will be organized, structured and given context through interpretation and analysis. Collectively, all information will make up bodies of knowledge that will, in turn, benefit various users of this t data, there won’t be any information. 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 that end, various approaches, tools and methodologies aimed at gathering or collecting data have been meaning of data r 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 is described as the “process of gathering and measuring information on variables of interest, in an established systematic fashion that enables one to answer queries, stated research questions, test hypotheses, and evaluate outcomes. 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 are two main types of data that users find themselves working with – and having to tative data. 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 ative data. 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. Narratives often make use of adjectives and other descriptive words to refer to data on appearance, color, texture, and other 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: the quantitative data collection methods and the qualitative data collection ance of data the definition of “data collection” alone, it is already apparent why gathering data is important: to come up with answers, which come in the form of useful information, converted from for many, that still does not mean ing 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. Collection aids in the search for answers and ng and building knowledge is a natural inclination for human beings.

Qualitative and quantitative data collection

There’s no way that they will be able to do these things without collecting the relevant collection facilitates and improves decision-making processes, and the quality of the decisions s cannot make decisive strategies without facts to support them. Similarly, businesses won’t be able to formulate marketing plans, and implement strategies to increase profitability and growth, if they have no data to start t data, there won’t be anything to convert into useful information that will provide the basis for decisions. All that decision-makers are left with is their intuition and gut feeling, but even gut feeling and instinct have some basis on on-making processes become smoother, and decisions are definitely better, if there is data driving them. According to a survey by helical it, the success rate of decisions based on data gathered is higher by 79% than those made using pure intuition 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 collection improves quality of expected results or 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 h collecting data, monitoring and tracking progress will also be facilitated. Adjustments can be made and improvements we move to the next question, and that is on the manner of collecting data. Why does it have to be systematic, and not just done on the fly, using whatever makes the data gatherer comfortable? Why do you have to pick certain methodologies of data collection when you can simply be random with it? You cannot afford to be random and haphazard about how you gather data when there are large amounts of investment at collection methods will help ensure the accuracy and integrity of data collected. Using the right data collection method – and using it properly – will allow only high quality data to be gathered. In this context, high quality data refers to data that is free from errors and bias arising from subjectivity, thereby increasing their reliability. High quality and reliable data will then be processed, resulting to high quality s of data ’ll now take a look at the different methods or tools used to collect data, and some of their pros (+) and cons (-). You may notice some methods falling under both categories, which means that they can be used in gathering both types of data.

Qualitative data collection atory in nature, these methods are mainly concerned at gaining insights and understanding on underlying reasons and motivations, so they tend to dig deeper. This lack of measurability leads to the preference for methods or tools that are largely unstructured or, in some cases, maybe structured but only to a very small, limited lly, qualitative methods are time-consuming and expensive to conduct, and so researchers try to lower the costs incurred by decreasing the sample size or number of -to-face personal is considered to be the most common data collection instrument for qualitative research, primarily because of its personal approach. The interviewer will collect data directly from the subject (the interviewee), on a one-on-one and face-to-face interaction. This is ideal for when data to be obtained must be highly interview may be informal and unstructured – conversational, even – as if taking place between two casual to close friends. The questions asked are mostly unplanned and spontaneous, with the interviewer letting the flow of the interview dictate the next questions to be r, if the interviewer still wants the data to be standardized to a certain extent for easier analysis, he could conduct a semi-structured interview where he asks the same series of open-ended questions to all the respondents. Questionnaires often utilize a structure comprised of short questions and, in the case of qualitative questionnaires, they are usually open-ended, with the respondents asked to provide detailed answers, in their own words. Since questionnaires are designed to collect standardized data, they are ideal for use in large populations or sample sizes of respondents. On the other hand, the large number of respondents (and data), combined with the high level and amount of detail provided in the answers, will make data analysis quite tedious and -based questionnaires. The lesser amount of detail provided means the researcher may end up with mostly surface data, and no depth or meaning, especially when the data is groups method is basically an interview method, but done in a group discussion setting. When the object of the data is behaviors and attitudes, particularly in social situations, and resources for one-on-one interviews are limited, using the focus group approach is highly recommended. Ideally, the focus group should have at least 3 people and a moderator to around 10 to 13 people maximum, plus a ing on the data being sought, the members of the group should have something in common. Other parameters such as the age, employment status, and income bracketdo not have to be similar across the members of the focus topic that data will be collected about will be presented to the group, and the moderator will open the floor for a debate. There may be a small group of respondents, but the setup or framework of data being delivered and shared makes it possible to come up with a wide variety of answers. The data collector may also get highly detailed and descriptive data by using a focus group. He must be highly capable and experienced in controlling these types of method involves the use of previously existing and reliable documents and other sources of information as a source of data to be used in a new research or investigation.

This is likened to how the data collector will go to a library and go over the books and other references for information relevant to what he is currently researching on. The researcher will gain better understanding of the field or subject being looked into, thanks to the reliable and high quality documents used as data sources. Unfortunately, this relies heavily on the quality of the document that will be used, and the ability of the data collector to choose the right and reliable documents. If he chooses wrong, then the quality of the data he will collect later on will be this method, the researcher takes a participatory stance, immersing himself in the setting where his respondents are, and generally taking a look at everything, while taking down from note-taking, other documentation methods may be used, such as video and audio recording, photography, and the use of tangible items such as artifacts, mementoes, and other tools. Data is more reliable and representative of what is actually happening, since they took place and were observed under normal circumstances. The participation may end up influencing the opinions and attitudes of the researcher, so he will end up having difficulty being objective and impartial as soon as the data he is looking for comes in. This may lead to the results becoming is a research or data collection method that is performed repeatedly, on the same data sources, over an extended period of time. The study aimed to gather data on the characteristics of gifted children – and how they grow and develop – over their lifetime. This is ideal when seeking data meant to establish a variable’s pattern over a period of time, particularly over an extended period of time. Over the extended period, attitudes and opinions of the subjects are likely to change, which can lead to the dilution of data, reducing their reliability in the this qualitative method, data is gathered by taking a close look and an in-depth analysis of a “case study” or “case studies” – the unit or units of research that may be an individual, a group of individuals, or an entire organization. This methodology’s versatility is demonstrated in how it can be used to analyze both simple and complex r, the strength of a case study as a data collection method is attributed to how it utilizes other data collection methods, and captures more variables than when a single methodology is used. In analyzing the case study, the researcher may employ other methods such as interviewing, floating questionnaires, or conducting group discussions in order to gather data. Reliability of the data may be put at risk when the case study or studies chosen are not representative of the sample or . Quantitative data collection can be readily quantified and generated into numerical form, which will then be converted and processed into useful information mathematically. Unlike qualitative methods, these quantitative techniques usually make use of larger sample sizes because its measurable nature makes that possible and the open-ended questions asked in qualitative questionnaires, quantitative paper surveys pose closed questions, with the answer options provided.

While data analysis is still possible, it will be restricted by the lack of al one-on-one interviews may also be used for gathering quantitative data. In collecting quantitative data, the interview is more structured than when gathering qualitative data, comprised of a prepared set of standard interviews can take the following forms:Face-to-face interviews: much like when conducting interviews to gather qualitative data, this can also yield quantitative data when standard questions are asked. The net for data collection may be cast wider, since there is no need to travel through distances to get the data. This is called capi, or computer-assisted personal interviewing where, in a face-to-face interview, the data obtained from the interviewee will be entered directly into a database through the use of a computer. The direct input of data saves a lot of time and other resources in converting them into information later on, because the processing will take place immediately after the data has been obtained from the source and entered into the database. The use of computers, databases and related devices and technologies does not come cheap. It also requires a certain degree of being tech-savvy on the part of the data tative is straightforward enough. Data may be collected through systematic observation by, say, counting the number of users present and currently accessing services in a specific area, or the number of services being used within a designated quantitative data is being sought, the approach is naturalistic observation, which mostly involves using the senses and keen observation skills to get data about the “what”, and not really about the “why” and “how”. It is a quite simple way of collecting data, and not as expensive as the other methods. These methods involve manipulation of an independent variable, while maintaining varying degrees of control over other variables, most likely the dependent ones. Usually, this is employed to obtain data that will be used later on for analysis of relationships and tative researches often make use of experiments to gather data, and the types of experiments are:Laboratory experiments. This is your typical scientific experiment setup, taking place within a confined, closed and controlled environment (the laboratory), with the data collector being able to have strict control over all the variables. This takes place in a natural environment, “on field” where, although the data collector may not be in full control of the variables, he is still able to do so up to a certain extent. This time, the data collector has no control over the independent variable whatsoever, which means it cannot be manipulated. Therefore, what can only be done is to gather data by letting the independent variable occur naturally, and observe its can probably name several other data collection methods, but the ones discussed are the most commonly used approaches.

At the end of the day, the choice of a collection method is only 50% of the whole process. The correct usage of these methods will also have a bearing on the quality and integrity of the data being your thoughts and experience. Get regular tips and tricks on topics such as marketing, financing, strategy, and management, so you can start and grow your company more er the #1 mistake 87% of job applicants your email, click "i'm in" and you'll get the proven step-by-step process you can use to get 4x more job tative and qualitative research skillsyouneed:A - z list of learning skills. Types of learning tanding your preferences to aid al thinking al thinking and fake g a dissertation or uction to research tative and qualitative research ative research iews for ative data from tative research ng and sample s and survey ational research and secondary ing research ing qualitative statistical tical analysis: identifying ariate our new research methods of the skills you need guide for ng, coaching, mentoring and ability skills for ibe to our free newsletter and start improving your life in just 5 minutes a 'll get our 5 free 'one minute life skills' and our weekly 'll never share your email address and you can unsubscribe at any tative and qualitative research also: surveys and survey ch methods are split broadly into quantitative and qualitative you choose will depend on your research questions, your underlying philosophy of research, and your preferences and pages introduction to research methods and designing research set out some of the issues about the underlying page provides an introduction to the broad principles of qualitative and quantitative research methods, and the advantages and disadvantages of each in particular tative research is “explaining phenomena by collecting numerical data that are analysed using mathematically based methods (in particular statistics). Tative research is perhaps the simpler to define and data produced are always numerical, and they are analysed using mathematical and statistical methods. If there are no numbers involved, then it’s not quantitative phenomena obviously lend themselves to quantitative analysis because they are already available as numbers. However, even phenomena that are not obviously numerical in nature can be examined using quantitative e: turning opinions into you wish to carry out statistical analysis of the opinions of a group of people about a particular issue or element of their lives, you can ask them to express their relative agreement with statements and answer on a five- or seven-point scale, where 1 is strongly disagree, 2 is disagree, 3 is neutral, 4 is agree and 5 is strongly agree (the seven-point scale also has slightly agree/disagree). Scales are called likert scales, and enable statements of opinion to be directly translated into numerical development of likert scales and similar techniques mean that most phenomena can be studied using quantitative is particularly useful if you are in an environment where numbers are highly valued and numerical data is considered the ‘gold standard’. It is important to note that quantitative methods are not necessarily the most suitable methods for investigation. It is also possible that assigning numbers to fairly abstract constructs such as personal opinions risks making them spuriously s of quantitative most common sources of quantitative data include:Surveys, whether conducted online, by phone or in person. Which may either involve counting the number of times that a particular phenomenon occurs, such as how often a particular word is used in interviews, or coding observational data to translate it into numbers; ary data, such as company pages on survey design and observational research provide more information about these ing quantitative are a wide range of statistical techniques available to analyse quantitative data, from simple graphs to show the data through tests of correlations between two or more items, to statistical significance. Other techniques include cluster analysis, useful for identifying relationships between groups of subjects where there is no obvious hypothesis, and hypothesis testing, to identify whether there are genuine differences between page statistical analysis provides more information about some of the simpler statistical ative research is any which does not involve numbers or numerical often involves words or language, but may also use pictures or photographs and any phenomenon can be examined in a qualitative way, and it is often the preferred method of investigation in the uk and the rest of europe; us studies tend to use quantitative methods, although this distinction is by no means ative analysis results in rich data that gives an in-depth picture and it is particularly useful for exploring how and why things have r, there are some pitfalls to qualitative research, such as:If respondents do not see a value for them in the research, they may provide inaccurate or false information. Qualitative researchers therefore need to take the time to build relationships with their research subjects and always be aware of this gh ethics are an issue for any type of research, there may be particular difficulties with qualitative research because the researcher may be party to confidential information. It is important always to bear in mind that you must do no harm to your research is generally harder for qualitative researchers to remain apart from their work. See our page on reflective practice for s of qualitative gh qualitative data is much more general than quantitative, there are still a number of common techniques for gathering it.

Data, including diaries, written accounts of past events, and company reports; ations, which may be on site, or under ‘laboratory conditions’, for example, where participants are asked to role-play a situation to show what they might pages on interviews for research, focus groups and observational research provide more information about these ing qualitative e qualitative data are drawn from a wide variety of sources, they can be radically different in are, therefore, a wide variety of methods for analysing them, many of which involve structuring and coding the data into groups and themes. The best way to work out which ones are right for your research is to discuss it with academic colleagues and your page analysing qualitative data provides more information about some of the most common y, it is important to say that there is no right and wrong answer to which methods you mes you may wish to use one single method, whether quantitative or qualitative, and sometimes you may want to use several, whether all one type or a mixture. It is your research and only you can decide which methods will suit both your research questions and your skills, even though you may wish to seek advice from ng and sample iews for g a research proposal | writing a ing qualitative data | simple statistical @skillsyouneed.