Using multiple ratings of a single concept can help you cross-check your data and assess the test validity of your measures.

You ask their direct employees to provide anonymous feedback on the managers regarding the same topics.

You ask managers to rate their own leadership skills on 5-point scales assessing the ability to delegate, decisiveness and dependability.

You operationalize this concept in two ways: The concept you want to measure is the leadership of managers. Example of operationalizationYou have decided to use surveys to collect quantitative data. When planning how you will collect data, you need to translate the conceptual definition of what you want to study into the operational definition of what you will actually measure. Operationalization means turning abstract conceptual ideas into measurable observations. However, often youвЂ™ll be interested in collecting data on more abstract concepts or variables that canвЂ™t be directly observed. Sometimes your variables can be measured directly: for example, you can collect data on the average age of employees simply by asking for dates of birth. To analyze data from populations that you canвЂ™t access first-hand.ДЇind existing datasets that have already been collected, from sources such as government agencies or research organizations. To understand current or historical events, conditions or practices.ДЄccess manuscripts, documents or records from libraries, depositories or the internet. Join and participate in a community and record your observations and reflections. To study the culture of a community or organization first-hand. Measure or survey a sample without trying to affect them. To understand something in its natural setting. Verbally ask participants open-ended questions in individual interviews or focus group discussions. To gain an in-depth understanding of perceptions or opinions on a topic. To understand the general characteristics or opinions of a group of people.Дistribute a list of questions to a sample online, in person or over-the-phone. Manipulate variables and measure their effects on others.

Surveys, observations, archival research and secondary data collection can be quantitative or qualitative methods.Д¬arefully consider what method you will use to gather data that helps you directly answer your research questions.

Interviews, focus groups, and ethnographies are qualitative methods.

Experimental research is primarily a quantitative method.

Step 2: Choose your data collection methodД«ased on the data you want to collect, decide which method is best suited for your research. You decide to use a mixed-methods approach to collect both quantitative and qualitative data.

Your second aim is to gather meaningful feedback from employees to explore new ideas for how managers can improve.

Your first aim is to assess whether there are significant differences in perceptions of managers across different departments and office locations.

Examples of quantitative and qualitative research aimsYou are researching employee perceptions of their direct managers in a large organization. If you have several aims, you can use a mixed methods approach that collects both types of data. If your aim is to explore ideas, understand experiences, or gain detailed insights into a specific context, collect qualitative data. If your aim is to test a hypothesis, measure something precisely, or gain large-scale statistical insights, collect quantitative data.

Qualitative data is expressed in words and analyzed through interpretations and categorizations.Quantitative data is expressed in numbers and graphs and is analyzed through statistical methods.Depending on your research questions, you might need to collect quantitative or qualitative data: Next, formulate one or more research questions that precisely define what you want to find out. You can start by writing a problem statement: what is the practical or scientific issue that you want to address and why does it matter?

Before you start the process of data collection, you need to identify exactly what you want to achieve.

What are data analysis methods