Data collection methods in quantitative research
Are a variety of techniques that can to collect data in a quantitative research r, all of them are geared towards numerical data can be collected by means of:In quantitative research, the data are recorded systematically, and these are then organised so that they can d into a computer on the icon below at the data collection methods used in the quantitative you have to work out collection method would allow you to answer your research question or or disprove your you have done this to action (i. You have chosen the correct methods, then add this ew 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”. Professionals, researchers, organizations, businesses, industries and even governments cannot function without information serving as “fuel” for decision-making, strategizing, gaining and storing information is not something that is handed to anyone on a silver platter. 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.
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Data collection in quantitative research
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. 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. 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.
For example, a researcher conducting a study on the recovery of married mothers from alcoholism will choose women who are (1) married, (2) have kids, and (3) recovering alcoholics. 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. Taking a look into other documents or researches as a source will provide a glimpse of the subject being looked into from different perspectives or points of view, allowing comparisons and contrasts to be made. 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. Validity may arise due to the risk that the researcher’s participation may have an impact on the naturalness of the setting. 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.
It is an observational research method that could even cover a span of years and, in some cases, even decades. 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. The long period may become a setback, considering how the probability of the subjects at the beginning of the research will still be complete 10, 20, or 30 years down the road is very low. 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 face-to-face setup allows the researcher to make clarifications on any answer given by the interviewee. 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 collection this page is to describe important data collection methods used collection is an of any type of research study. Inaccurate data collection the results of a study and ultimately lead to invalid collection methods for impact evaluation vary along a the one end of this continuum are quantatative methods and at end of the continuum are qualitative methods for data tative and qualitative data collection quantitative data collection methods, rely sampling and structured data collection instruments that e experiences into predetermined response categories. They s that are easy to summarize, compare, and tative research is testing hypotheses derived from theory and/or being able to size of a phenomenon of interest. Depending on the research question,Participants may be randomly assigned to different this is not feasible, the researcher may collect data on situational characteristics in order to statistically control influence on the dependent, or outcome, variable. Intent is to generalize from the research participants to a tion, the researcher will employ probability sampling to tative data gathering strategies include:And recording well-defined events (e. Http:///info/srms/ a structured interview,the researcher asks a standard set of nothing more. To -face interviews have a distinct enabling the researcher to establish rapport with potential therefor gain their interviews yield highest in survey also allow the researcher to clarify s and when appropriate, seek follow-up information. Interviews are less time consuming and ive and the researcher has ready access to anyone on the hasa antages are that the response rate is not as the face-to- face interview but cosiderably higher than sample may be biased to the extent that t phones are part of the population about whom the to draw er assisted personal interviewing (capi): is a form al interviewing, but instead of completing a questionnaire, iewer brings along a laptop or hand-held computer to enter ation directly into the database. This method saves time processing the data, as well as saving the interviewer from hundreds of questionnaires. However, this type of data can be expensive to set up and requires that interviewers er and typing -pencil-questionnaires can be sent to a of people and saves the researcher time and truthful while responding to the questionnaires regarding in particular due to the fact that their responses are they also have ty of the people who receive 't return them and those who do might not be representative of ally selected sample. Often make use of checklist and rating s help simplify and quantify people's behaviors and ist is a list of behaviors,characteristics, entities that te researcher is looking the survey participant simply checks whether each item on the list ed, present or true or vice versa. Data collection methods play an in impact evaluation by providing information useful to processes behind observed results and assess changes in tions of their rmore qualitative methods to improve the quality of survey-based quantitative helping generate evaluation hypothesis; strengthening the survey questionnaires and expanding or clarifying quantitative gs. These methods are characterized by the following attributes:They tend to be open-ended and have less structured protocols (i. Researchers may change the data collection strategy by adding, refining,Or dropping techniques or informants).
Their findings are not generalizable to any specific population,Rather each case study produces a single piece of evidence that used to seek general patterns among different studies of the less of the kinds of data involved,data collection in a takes a great deal of researcher needs to record ially useful data thououghly,accurately, and systematically, notes,sketches,audiotapes,photographs and other suitable collection methods must observe the ethical principles of qualitative methods most commonly used in evaluation can be three broad categories:The following link provides more information on the above three ent ways of collecting evaluation data are useful for es, and each has advantages and disadvantages. Various influence your choice of a data collection method: the want to investigate, resources available to you, your timeline,And more. Http:///evaluation/sity of southern zing your social sciences research zing your social sciences research paper: quantitative purpose of this guide is to provide advice on how to develop and organize a research paper in the social of research flaws to ndent and dependent ry of research terms. Choosing a research ing a topic ning a topic ing the timeliness of a topic idea. An oral g with g someone else's to manage group of structured group project survival g a book le book review ing collected g a field informed g a policy g a research tative 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 numerical data and generalizing it across groups of people or to explain a particular , earl r. London: sage publications, teristics of quantitative goal in conducting quantitative research study is to determine the relationship between one thing [an independent variable] and another [a dependent or outcome variable] within a population. Quantitative research designs are either descriptive [subjects usually measured once] or experimental [subjects measured before and after a treatment]. A descriptive study establishes only associations between variables; an experimental study establishes tative research deals in numbers, logic, and an objective stance. Quantitative research focuses on numeric and unchanging data and detailed, convergent reasoning rather than divergent reasoning [i. The generation of a variety of ideas about a research problem in a spontaneous, free-flowing manner]. Main characteristics are:The data is usually gathered using structured research results are based on larger sample sizes that are representative of the research study can usually be replicated or repeated, given its high cher has a clearly defined research question to which objective answers are aspects of the study are carefully designed before data is are in the form of numbers and statistics, often arranged in tables, charts, figures, or other non-textual t can be used to generalize concepts more widely, predict future results, or investigate causal cher uses tools, such as questionnaires or computer software, to collect numerical overarching aim of a quantitative research study is to classify features, count them, and construct statistical models in an attempt to explain what is to keep in mind when reporting the results of a study using quantitative methods:Explain the data collected and their statistical treatment as well as all relevant results in relation to the research problem you are investigating. Interpretation of results is not appropriate in this unanticipated events that occurred during your data collection. Explain your handling of missing data and why any missing data does not undermine the validity of your n the techniques you used to "clean" your data a minimally sufficient statistical procedure; provide a rationale for its use and a reference for it.
Keep figures small in size; include graphic representations of confidence intervals whenever tell the reader what to look for in tables and : when using pre-existing statistical data gathered and made available by anyone other than yourself [e. Government agency], you still must report on the methods that were used to gather the data and describe any missing data that exists and, if there is any, provide a clear explanation why the missing data does not undermine the validity of your final , earl r. Los angeles, ca: sage, research design for quantitative designing a quantitative research study, you must decide whether it will be descriptive or experimental because this will dictate how you gather, analyze, and interpret the results. An experimental design includes subjects measured before and after a particular treatment, the sample population may be very small and purposefully chosen, and it is intended to establish causality between introduction to a quantitative study is usually written in the present tense and from the third person point of view. It covers the following information:Identifies the research problem -- as with any academic study, you must state clearly and concisely the research problem being s the literature -- review scholarship on the topic, synthesizing key themes and, if necessary, noting studies that have used similar methods of inquiry and analysis. If necessary, define unfamiliar or complex terms, concepts, or ideas and provide the appropriate background information to place the research problem in proper context [e. Methods section of a quantitative study should describe how each objective of your study will be achieved. Be sure to provide enough detail to enable the reader can make an informed assessment of the methods being used to obtain results associated with the research problem. The methods section should be presented in the past population and sampling -- where did the data come from; how robust is it; note where gaps exist or what was excluded. Collection – describe the tools and methods used to collect information and identify the variables being measured; describe the methods used to obtain the data; and, note if the data was pre-existing [i. Note that no data set is perfect--describe any limitations in methods of gathering analysis -- describe the procedures for processing and analyzing the data. If appropriate, describe the specific instruments of analysis used to study each research objective, including mathematical techniques and the type of computer software used to manipulate the finding of your study should be written objectively and in a succinct and precise format. In quantitative studies, it is common to use graphs, tables, charts, and other non-textual elements to help the reader understand the data. Further information about how to effectively present data using charts and graphs can be found tical analysis -- how did you analyze the data?
The discussion should be presented in the present retation of results -- reiterate the research problem being investigated and compare and contrast the findings with the research questions underlying the study. Describe any limitations or unavoidable bias in your study and, if necessary, note why these limitations did not inhibit effective interpretation of the your study by to summarizing the topic and provide a final comment and assessment of the y of findings – synthesize the answers to your research questions. Do not report any statistical data here; just provide a narrative summary of the key findings and describe what was learned that you did not know before conducting the endations – if appropriate to the aim of the assignment, tie key findings with policy recommendations or actions to be taken in research – note the need for future research linked to your study’s limitations or to any remaining gaps in the literature that were not addressed in your , thomas r. Doing quantitative research in the social sciences: an integrated approach to research design, measurement and statistics. Kennesaw state ths of using quantitative tative researchers try to recognize and isolate specific variables contained within the study framework, seek correlation, relationships and causality, and attempt to control the environment in which the data is collected to avoid the risk of variables, other than the one being studied, accounting for the relationships the specific strengths of using quantitative methods to study social science research problems:Allows for a broader study, involving a greater number of subjects, and enhancing the generalization of the results;. Generally, quantitative methods are designed to provide summaries of data that support generalizations about the phenomenon under study. In order to accomplish this, quantitative research usually involves few variables and many cases, and employs prescribed procedures to ensure validity and reliability;. Well establshed standards means that the research can be replicated, and then analyzed and compared with similar studies;. Los angeles, ca: sage, tions of using quantiative tative methods presume to have an objective approach to studying research problems, where data is controlled and measured, to address the accumulation of facts, and to determine the causes of behavior. As a consequence, the results of quantitative research may be statistically significant but are often humanly specific limitations associated with using quantitative methods to study research problems in the social sciences include:Quantitative data is more efficient and able to test hypotheses, but may miss contextual detail;. Development of standard questions by researchers can lead to "structural bias" and false representation, where the data actually reflects the view of the researcher instead of the participating subject;. Research is often carried out in an unnatural, artificial environment so that a level of control can be applied to the exercise. University of southern are here: my-peer toolkit » evaluation » data collection collection ative and quantitative are usually collected through qualitative and quantitative methods. Qualitative approaches aim to address the ‘how’ and ‘why’ of a program and tend to use unstructured methods of data collection to fully explore the topic.
They use a systematic standardised approach and employ methods such as surveys1 and ask questions such as ‘what activities did the program run? Quantitative approaches however are limited in their capacity for the investigation and explanation of similarities and unexpected differences. It is important to note that for peer-based programs quantitative data collection approaches often prove to be difficult to implement for agencies as lack of necessary resources to ensure rigorous implementation of surveys and frequently experienced low participation and loss to follow up rates are commonly experienced there a way to achieve both the depth and breadth that qualitative and quantitative methods may achieve individually? One answer is to consider a mixed methods approach as your design, combining both qualitative and quantitative research data, techniques and methods within a single research methods approaches may mean a number of things: ie a number of different types of methods in a study or at different points within a study, or, using a mixture of qualitative and quantitative methods. Methods encompass multifaceted approaches that combine to capitalise on strengths and reduce weaknesses that stem from using a single research design. Using this approach to gather and evaluate data may assist to increase the validity and reliability of the of the common areas in which mixed-method approaches may be used include:Initiating, designing, developing and expanding interventions;. Of the challenges of using a mixed methods approach include:Delineating complementary qualitative and quantitative research questions;. However this may be mediated by identifying key issues early and ensuring the participation of experts in qualitative and quantitative methods are useful in highlighting complex research problems such as disparities in health and can also be transformative in addressing issues for vulnerable or marginalised populations or research which involves community participation. Using a mixed-methods approach is one way to develop creative options to traditional or single design approaches to research and s are a good way of gathering a large amount of data, providing a broad perspective. If possible the use of an already designed and validated survey instrument will ensure that the data being collected is accurate. They can range from in-depth, semi-structured to unstructured depending on the information being to face interviews are advantageous since:Detailed questions can be r probing can be done to provide rich cy requirements of participants is not an verbal data can be collected through x and unknown issues can be se rates are usually higher than for self-administered antages of face to face interviews include:They can be expensive and time ng of interviewers is necessary to reduce interviewer bias and are administered in a standardised are prone to interviewer bias and interpreter bias (if interpreters are used). Issues maybe one interviews according to bowling6, yield just as accurate data as face to face one interviews are advantageous as they:Are cheaper and faster than face to face interviews to less resources than face to face to clarify not require literacy antages of telephone interviews include:Having to make repeated calls as calls may not be answered the first ial bias if call backs are not made so bias is towards those who are at suitable for short accessible to the population with a appropriate for exploring sensitive groups or group discussions are useful to further explore a topic, providing a broader understanding of why the target group may behave or think in a particular way, and assist in determining the reason for attitudes and beliefs. Thick description also includes the complexities experienced in addition to the commonalities found, which assists in maintaining data use of documentation provides an ongoing record of activities. It is the process of engaging with art that often elicits valuable success of such an approach can often rely on the interest levels of the participants; the task needs to be defined clearly, emphasising the reasoning behind are multiple forms of creative strategies which you can explore ulation is used to address the validity of the data.
Triangulation methods use multiple forms of data collection, such as focus groups, observation and in-depth interviews to investigate the evaluation objectives. Utilising multiple data collection methods leads to an acceptance of reliability and validity when the data from the various sources are comparable and consistent. North ryde: l tors for collection tion case the my-peer ght © 2010 western australian centre for health promotion research.