Data is classified into two broad categories; Quantitative and Qualitative, based on the techniques employed in the field to gather and analyze data/facts. Researchers need to choose the most suitable methods that can be helpful in collecting relevant and viable data/facts, suiting the monitoring and evaluation of the given project. There is a distinction between quantitative and qualitative methods of data collection and analysis. This is elaborated in the discussion below.
Quantitative techniques in M&E
Crafting for quantitative methods, largely depend on the kind of data we need and the nature of the project under evaluation and monitoring. Evaluators can opt to use secondary data or primary data as per the needs of the project.
Quantitative methods directly measure the status or change of a specific variable, for example, changes in crop yield, kilometers of road built or the amount of money spent on purchasing items. Basically, this methods incline to numerical data whereby the collection involves the formulation of structured questionnaires that form the solid part of getting facts from sampled respondents. Upon getting the questionnaires filled, data is then coded into specified programs and softwares, to attach meaning to every number used, and then the analysis proceeds. In regard to the presentation of the outputs, answers such as; How many? How frequent and how much forms base for the numerical results. The successful completion of a project depends on how fruitful the quantitative methods applied were and the nature of data collected, analyzed and presented. In knowing how the study was conducted, monitoring and process evaluation reveals the quality of the program and techniques used, viability of collected facts, the barriers encountered in the field and whether the set objectives were achieved. All these help in streamlining the intended purpose of the project.
Qualitative Techniques in M&E
As we monitor and evaluate projects, we use many different kinds of qualitative methods, and each of these methods gives us different kinds of data. Based on our evaluation statement or performance monitoring plan, we apply different techniques on particular scenarios to elicit certain kinds of data. We might develop emic or etic perspectives depending on where we get data from.
Qualitative methods gather information by asking people to explain what they observe, do, believe or feel. This is more of textual descriptions rather than numerical values. Qualitative methods can also be called “informal” as they have an open-ended approach to gathering facts. Respondents get subjected to provide views based on how they understand the topic of concern. Sample of questions mostly answered are; “Why do you think this happened?” or “How do you think this will affect you? People’s attitudes/behaviours, beliefs, opinions, experiences and priorities can be known through the kind of facts collected hence, making qualitative methods to be unique in a way. For any project conducted, it is easy to monitor and evaluate the progress based on how both respondents and researchers behave. The qualitative methods mostly used in collecting facts include; Interviews, focus groups, case studies, The KAP (knowledge, attitude and practice) survey and observations. In getting to understand more about data collection and analysis in M&E, enroll at Sirmirt Company for the coming training.
Technology has rocked today’s world and every company; be it big or small is yawning to embrace new invented tactics, methods and even programs with hopes of replacing the once re-known tedious manual processes and systems. Among the many shocking innovations, ODK and Kobo toolbox are inclusive as they add value to the field of research. For many years, NGOs, private corporates, government parastatals, ministries, and even students have been relying on hard copy questionnaires, which at some point are prone to numerous errors, leading to collection of ineffective data. The invention of ODK and Kobo has solved the menace as the use of electronic questionnaires is the way to go. The use of pen, bulky papers and unreserved methods has been replaced by structuring of electronic questionnaire which get uploaded to online servers like On.io and survey CTO, then get accessed by ODK or Kobo toolkit and one is able to conduct a research by filling the questionnaires upon asking respondents questions.
Over the years, the manual systems have been expensive, costing companies and even students or individual researchers a lot, but with the coming of ODK and Kobo, there is hope of reducing these expenses. Large amounts of data can be collected at a minimal cost an instance that has made companies to adopt the technique. The user friendly nature of ODK and Kobo enables researchers to gather facts without getting tired nor losing any valuable data as opposed to when using hard copy questionnaires. It is time for technology to be given room, hence, NGOs, private and public companies, students and any research related entity should try ODK and Kobo if viable and quality facts are to be collected.
The use of ODK or Kobo not only cut costs but also, provides error free and quality data which is directly subjected to analyzing tools and programs. There are no regrets by any company or individual who has applied ODK or Kobo in conducting a study. In getting the skills of formulating electronic questionnaires, uploading them to online servers, and then retrieving these forms for a given research, Sirmirt Data Services has got experienced professionals who will impart the knowledge to anyone interested.
Data Science continues to evolve as one of the most promising, in-demand aspect necessary for companies to adopt. As technology advances, data science keeps on developing, prompting organization to subscribe to new innovative methods, strategies, programs and systems in order to be abreast with any changes experienced.
The types of data analytics each company needs to embrace are;
Descriptive analytics answers the question of what happened. For example, a nurse or a doctor needs to know how many patients were hospitalized last month; and a manufacturer – a rate of the products returned for a past month.
At this stage, historical data can be measured against other data to answer the question of why something happened. Companies go for diagnostic analytics as it gives in-depth insights into a particular problem. At the same time, a company should have detailed information at their disposal otherwise data collection may turn out to be individual for every issue and time-consuming.
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Predictive analytics tells what is likely to happen. It largely depend on the findings of descriptive and diagnostic analytics to figure out tendencies, exceptions, and to predict future trends, facilitating forecasting.
The purpose of prescriptive analytics is to literally prescribe what action to take to eliminate a future problem or take full advantage of a promising trend.
What do we mean when we talk about Descriptive statistics? Data is split among various parameters, then groups of these models get created, and finally in-depth explanations is attached. Basically, the descriptive statistics is more of a summary, entailing all aspects to do with a given data set. The programs that can be of use in giving outputs that describes data eminently, include; SPSS, Minitab, Excel, STATA, and R-language. Measures of central tendency and measures of variability are the two types of descriptive statistics used in elaborating features of a given data set, so that people can understand the information presented.