Structure, methods, evaluation: With the recipe for research projects of the Lecturer for Empirical Methods and SPSS Claus Braunecker, you research like a pro
The thought of having to do your own research project makes you sweat? You can breathe, empiricism is much easier than her reputation announces. After all, research is like cooking a four-course meal: it depends on adding the right ingredients at the right time. And just as with food, you can not know how it tasted until you prepare and eat it.
Structure is everything: research projects need red threads
For each research project, a red thread is really important: all phases of the empirical survey depend on it in turn – from the first research idea to the presentation of the results and the summary. This applies to surveys as well as to focus groups, content analyzes, expert interviews or scientific observations. So, in a row, and every research and statistics muddled part of the past belongs to the past.
Step 1: The interest in knowledge
You can only research if you know exactly what you want to research. That should be clarified. Each research project initially has a general interest in cognition. From this research questions or hypotheses are derived. This takes place in the economy from factual contexts, in science in the course of detailed literature searches. The research questions formulate the exact details to be investigated.
A little tip: It is better to ask, “What influence do the ingredients of a dish have on the taste?” Instead of: “Do the ingredients have any influence?” – otherwise you can only answer your research question with a yes or no.
The difference between research question and hypothesis
Hypotheses in turn use findings from the literature, from preliminary studies or parallel surveys and make a guess based on it. There you formulate: “The more cream added, the better it tastes” or: “If cream is added, then the taste changes.” Only when you have worked out your research questions or hypotheses, you can consider in accordance with how you can achieve the most efficient results.
Note: you answer research questions, hypotheses are examined.
Step 2: The Setting
How to set up your investigation, you can either after you have the research questions or hypotheses set up or in parallel to think. Just be sure: The determination of the appropriate research methodology steers your entire project including evaluation and presentation of results.
Qualitatively or quantitatively research
On the one hand, you can do something qualitatively – in search of verbal content – or on the other quantitatively – in search of numbers.
Definition Qualitative Research: In qualitative settings, you are looking for verbal answers to questions such as “What does a dish have to contain to make it taste great?”.
Definition Quantitavie Research: Quantitative empiricism, on the other hand, aims at the collection of numbers in the form of percentages, averages or the like. For example, you might ask, “Did you like this dish?” Or “Please rate this dish with a grade.”
Step 3: The population
If you do not think carefully about who or where you want to find out, it will not work. In interaction with the setting of a survey is the exact definition of your population: Who – in a survey – or where exactly – in an observation or content analysis – should be examined at all? Unfortunately, many make the mistake of not making this determination or not sufficiently accurate. This leads to results that are not or poorly usable, because it is not clear what they apply to. If you do not get turnips in Munich, you can not say that there are none in Europe.
Full survey or sample?
Once you have clearly defined the population, you can consider whether a full survey – of the entire population – is possible. If this is not the case, you will draw a sample and examine only a part of the population. You choose this part randomly, according to certain characteristics or arbitrarily – depending on how your setting requires it.
Step 4: The survey
Now we go to the actual survey by questionnaire, guide, coding scheme or protocol sheet. Your questions or survey dimensions must be absolutely accurate here. This means that here no contradictions or blurring of your research questions or hypotheses may arise. Also, the level of measurement is critical to how much you can read out of the data later. For example, if you merely ask, “Did you like this dish?” You can read far less about the results than “Please judge this dish with a grade,” or “How many times a year would you like to eat this dish ? “
Step 5: Pretest and evaluation
At the pretest, the survey instrument is checked for suitability. If it does not work satisfactorily, it has to be reworked. After collecting it goes to the evaluation.
Note: Data analyzes are initially carried out technically. Only then do you interpret.
Step 6: Collect, evaluate and interpret data
When collecting the data, do you check whether you have collected enough data? Has the full census really been fully collected, or does the sample show satisfactory returns? – Otherwise, your results may not be representative. If the data are then available, their technical evaluation follows. Here you use – especially in quantitative surveys – best a statistical evaluation program such as SPSS. Again, this is easy to learn and use with an instruction manual.
Result section: First evaluate, then discuss
When evaluating, you first describe your results in descriptive statistics, then you sample them for your population – the significance checks. Now you can start to interpret the results, ie answering your research questions or testing your hypotheses. If necessary, you will carry out in-depth data analyzes. Finished?
Now it is still necessary to prepare and present the results as boldly as possible, so that everyone – even those who are hearing about your investigation for the first time – can quickly get used to it. Not so hard, right?