In my previous blog, "Qualitative and Quantitative Research: What's What?" I explained the difference between qualitative and quantitative research. In this blog, I will discuss what kinds of research topics call for a qualitative approach and which ones, on the contrary, require a quantitative approach.

Do you want to demonstrate a change in attitude resulting from an activity, project, or program? Do you want to show significant differences and be able to generalize to the masses? And do you want to be able to make numerical statements about a specific target group? Then a quantitative method of research fits best.

Examples of research questions answered through quantitative research:

• What is the effect of project X on target group Y?
• To what extent are visitors/participants satisfied?
• Does the attitude towards subject X change with target group Y?

Do you need more in-depth information? Do you want to know what's behind it? And are you looking for motives?  Then qualitative research is the best method. You want answers to the Why and How Questions.

Examples of research questions answered through qualitative research:

• How can we improve our project?
• Why do people visit our museum?
• How do people experience visiting us?

Qualitative and quantitative research are not necessarily independent. Sometimes a research question requires a mix of both methods, where you want to know the effect; are visitors satisfied? And why are they satisfied?

When you conduct interviews, you can find out a lot. You collect primarily qualitative data. (There are some tricks to collect quantitative data as well.) Before you start an interview, it is crucial that you have well-defined interview questions. Because you don't ask questions just for fun: respondents have to answer the central question of your research. That is why I am giving you tips on how to design your interview questions as well as possible:

1. 1. Have clearly worded main and sub-questions ready.
   2. Ask questions that connect to your main and sub-questions. To ensure all of them can be answered, mark behind each question which main or sub-question the question connects to.
   3. Put the questions in a logical order that avoids overlap.
   4. Include introductory text in your interview questions. This text should state why participants are being interviewed and how long the interview will take.
   5. Formulate your questions so that the interviewee understands them. You can test this by practicing the protocol with your colleagues. This way, you will also notice if your questions are asked in the proper order.
   6. Make sure to ask your questions objectively. This will prevent biases that will cause the research to produce the wrong answers and will allow for continued questioning during your interview. Prejudice occurs when you ask leading questions such as "Don't you agree?", "Would you...?" or "Is it true that...?".
   7. Make sure there is room to ask more in-depth questions. In-depth questions start with 'why', 'how', 'what' and 'who'. In these questions, you will find the 'gold nuggets' that will provide special insights for your research.
   8. Write a closing text explaining what will be done with the survey results.

   Finally, I would like to inform you that remaining objective during the interview is essential. Your own opinion plays no role in this; make sure the interviewee can tell their own story.

   More tips to prepare for your interview? Then please read my blog '15 tips for a good interview'.

Suppose you want to research a target group of as many as 10,000 people. Do you have to interview all 10,000 people to get the right results? Certainly not; only a part of the research population needs to participate in your research to get representative results. Let me explain what representativeness means and when the results are deemed characteristic.

Representativeness means the degree to which the respondents in a sample group are a good reflection of the target group of your research. Therefore, your research is representative, which means that the conclusion of your research is true for 'everyone' in your research population.

A sample

If you have a research population of 10,000 people, you will ultimately need to interview 400 people to arrive at the opinion of the larger group. This does not mean that you only need to approach 400 people. You have to deal with a response rate. This is the percentage of people who participate in your survey. Your response rate depends on the subject you are researching, how easy and fun it is to participate in your research, and what people get in return. I often use a response rate of 30% because I usually research fun subjects, and I am experienced in making it easy to participate in a survey. I also ask the client for a nice gift for the people who participate in the survey. Tips to increase your response rate

Because not everyone will participate in your survey, you will need to have a larger sample group. If you need 400 respondents and assume a response rate of 30%, you will need to interview a sample group of 400/30%=1,333.

When you conduct a survey, you must keep in mind that the smaller the research population is, the larger the number of respondents will be to arrive at the desired representative results. Sometimes, however, respondents' input is more valuable than the number of participants. In this case, you're referring to qualitative research, and it can be more important to focus on the research results than the representativeness in some cases.

If you want to know how many respondents you need for your research population: go to a sample calculator. These will often immediately tell you how many people you need to approach in your sample.

In a previous blog, I wrote about how best to draw a sample. In the blog, I briefly described the difference between a select and a random sample. There is a substantial difference between the two.

In a random sample, everyone in the focus population has an equal chance of being in the sample. This sample is also called a probability sample or random selection. There are several methods for doing a random sample:

• Single random sampling: the lottery method, you randomly select a number of people. This can be done manually or by computer.
• Systematic random sampling: you choose a random number and then go through your list in steps, for example, 20-120-220 etc.
• The cluster or bunch sampling: the list is divided into several clusters. And then, a group is chosen at random.
• The quota sampling: In advance, it is known how many respondents are needed; when that number is reached, the data collection stops.

In a select sample, not everyone has a chance to be in the sample group. The results apply only to the group being studied. There are a number of selective sampling options:

• Snowball sampling: At first, one person is talked to; this person is asked if they know anyone who would also be interesting to talk to. And so on until the sample is large enough. When doing this, make sure you approach people with different perspectives; otherwise, your sample is flawed. Use this method when conducting interviews.
• The convenience sample: the researcher approaches people from his circle or the circle of colleagues until the sample is large enough. Of course, this sampling method is not fully representative because the respondents are chosen on insignificant factors (would know).
• Stratified sample: you divide the population into different groups. A representative number of respondents are chosen from each group.
• The two or multi-stage sampling: a sample is first drawn from several main categories. After this, a representative number of respondents are chosen from the selected main categories. For example, first a number of cities are determined, and from these cities, a neighborhood and then a street per neighborhood. This method is not a good reflection of the population.

From the conversations I have with various people who do research stems some confusion about the term research methods. There are theories on which you can conduct a research study, and you have multiple ways of collecting data.

In my blogs, I regularly talk about research methods, referring to the various ways of collecting data.

Once you have clarity about your research questions, you examine what information you can collect and how. There are many different methods to do this. You have qualitative research methods and quantitative research methods. Qualitative research methods are not about facts and figures but rather about how and why. Quantitative research methods are more about facts and figures that can be compared. Also, check out my blog about the difference between qualitative and quantitative research methods.

There are all sorts of research methods. My overview blog of different research methods lists different ways. Also, be creative with the ways you collect data. Look beyond the standard practices of research and make interesting combinations.

Once you have chosen a research method, thorough preparation is essential. Look at what you need per method and take the time to set up your measuring instrument properly. Discuss it with colleagues and test the measuring instrument before using it.