Quantitative methods involve describing and recording behaviour and changes in numerical form as precisely as possible.
|Number of units of analysis||Many|
|Assumptions||Clear idea of relevant links|
|Starting point||Verifying ideas|
|Focus||Researchers’ knowledge is central|
Due to their standardised form of questioning and observation, quantitative methods are suitable for researching large samples and for applying statistical evaluation methods to measure and quantify facts in an objective manner. They are ideal for comparing objective data over time and for interpreting change. Quantitative data collection methods make it possible to examine a large amount of information using predefined methods. The information gained can be analysed and compared using statistical methods and analytical techniques.
Quantitative data is collected using the following techniques:
- Structured observation, measurement, counting
- Analysis of secondary data (statistics, process data)
- Various forms of surveys and experiments
The choice of sample size depends on how precise the results of the survey are supposed to be. The easiest thing, therefore, is if all the units of analysis can be surveyed. This is known as a total population survey. In a total population survey, there is no need for any statistical tests on the significance of differences because the data is not based on a sample that is extrapolated to the whole population. It can be seen from the table below that a total population survey is the best option for units of analysis containing less than 300 cases. It also shows that 300 surveyed units allow one to make relatively reliable statements about large populations.
|N = size of population||n =||n =|
|Size of population||Minimum sample size with a margin for error of +/-3 percentage points||Minimum sample size with a margin for error of +/-5 percentage points|
|1 000 000||1066||384|
With quantitative data collection methods, analysis is carried out using various statistical methods and figures including frequency, percentages and means, as well as more complex statistical methods.
|Precisely quantifiable results||No flexibility during the investigation due to the standardisation of the investigation situation. The questions are determined in advance, and it is not possible to listen to the individual test people.|
|Makes it possible to ascertain statistical links||Does not reveal what caused a result or an attitude such as dissatisfaction. The use of open questions is recommended in order to reduce this problem.|
|Makes it possible to investigate a large sample and obtain representative results||Gives no suggestions for improvement. This disadvantage can be reduced by including open questions.|
|High external validity through large sample|
|Greater objectivity and comparability|