How does data collection affect data analysis

Data collection and data collection: what are the differences?

A data acquisition or data collection is often necessary for a scientific work. But what are the differences between these two methods? The terms are often used synonymously with one another. However, this is wrong, as the following article shows. This not only gives a definition for the two terms, but also deals with further topic-relevant questions (for example, why data actually needs to be collected).

Definition: data collection vs. data collection

  • The Data collection aims to collect mathematically inaccessible data. In contrast to data collection, data collection does not take place simultaneously at any time; the data obtained must be interpreted subjectively. Due to different research conditions, a direct comparison with other data is rarely or only partially possible.
  • The Data acquisition collects mathematically directly accessible data. The acquisition is always carried out simultaneously or in the correct chronological order; objective data are obtained so that a comparison with similar research is possible.
The aim of recording or collecting data is to collect information that is used to answer a research question. Accordingly, the methods are an important part of everyday scientific life.

When to collect data

There are generally two reasons for data collection / data collection:
  1. There is no data that can be used to answer a research question.
  2. There is data, but not enough to answer the research question.
The following “academic fields of application” of data collection and data acquisition can be derived from these two reasons.

Primary and secondary research

In addition to the above distinctions, a distinction can also be made between primary research and secondary research. In the former, the required data is re-recorded, which has the advantage that the survey can be tailored to the research question, so that the data obtained are very precise. In addition, the timely collection / recording means that the data sets are usually more up-to-date than in the case of desk research. Since the researcher can influence the survey conditions, comparisons can be made between similar researches.
In contrast, secondary research uses existing data from other research. This type of work is therefore less complex, cheaper and also takes less time. As the data collected has usually already been subjected to an analysis, the researcher has an orientation aid with regard to his / her results. Another advantage of desk research is that you can access difficult-to-access data. Primary research is left behind here, as some experts are not available to academics for an interview or the like.

The extent of the data collection

Furthermore, a distinction is made between the partial and full survey:
While in the latter case the population is recorded (e.g. census), the partial survey only records a segment of this. Representative samples are made in order to be able to draw conclusions about the population. The full census is only suitable for small populations. Simply for the reason that the effort would otherwise be much too great or because a survey can no longer be realized above a certain level.

How often is the data collected?

Data can be recorded or collected once, several times or sequentially:
  1. The one-time acquisition takes place, for example, as part of a bachelor thesis.
  2. Become repeated surveys carried out, either the survey object or the survey unit is varied (e.g. two surveys of a population on different topics).
  3. In the sequential survey the object and the survey unit remain the same. The aim is to determine developments over time (e.g. in election polls).

Overview of some research methods

This section briefly introduces some methods of data collection and data collection.
  • A questionnaire can consist of open-ended or multiple-choice questions. The data is recorded in writing and relatively quickly.
  • In a one-on-one interview, the researcher asks a person about a specific topic.
  • Several people are interviewed in the expert interview. The prerequisite for a person to be able to participate as a test subject is that he or she has many years of specialist knowledge.
  • The observation enables the recording of verbal and non-verbal data.
  • Tests and measurements are particularly suitable for quantitative surveys.
  • Document analysis has the advantage that internally and externally accessible data can be recorded quickly and cheaply (for example as part of the needs analysis for a company).
  • In the case study (in German: case study), the data is often obtained through the use of different survey methods.

The quality criteria for data collection / data acquisition

Last but not least, it should be noted that the data collection / data acquisition must meet certain criteria (quality criteria) in order to be considered scientifically sound:
  1. Objectivity: The information must be recorded objectively, i.e. independently of the researcher.
  2. Reliability: A reliable evaluation of the data is only possible if it is collected under the same conditions.
  3. Validity: The information collected must be relevant to the research question and allow conclusions to be drawn for it.

Data acquisition and data collection - summary

This article highlighted the differences between data collection and data collection. You now know in which scientific work these can be used and which forms and methods there are for collecting data. Furthermore, in this post you have gained an overview of the quality criteria for data acquisition and collection.
  • Tip: Anyone who would like to carry out data acquisition or data collection should look further into specialist literature on the topic.
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