Answer:

Qualitative Data

1.) Concept Maps

2.)Case Studies

3.)Video and recordings

Quantitative data

1.)A bag of broccoli crowns weighs four pounds

2.)scores on achievement tests

3.)In an entire school, there are 523 students

Explanation:

Quantitative data are data about numeric variables (e.g. how many; how much; or how often). Qualitative data are measures of 'types' and may be represented by a name, symbol, or a number code. Qualitative data are data about categorical variables (e.g. what type).

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Answer:

Qualitative data collection methods

Qualitative data collection methods vary, and usually rely on unstructured or semi-structured techniques. Common methods include:

Focus groups

Individual interviews

Observation or immersion. For example, an ethnography

Diary studies

Literature reviews

Open-ended survey questions

Using qualitative research methods, the sample size is typically small, and respondents are selected to fulfill a given quota.

Quantitative research

Quantitative (“quant”) research is used to quantify the problem by way of generating numerical data that can be transformed into useable statistics. It is used to quantify attitudes, opinions, behaviors, and other defined variables, and generalize results from a larger sample population. Quantitative research uses measurable data to formulate facts and uncover patterns in research.

Quantitative data collection methods

Quantitative data collection methods are much more structured; they include:

Surveys. For example: online surveys, paper surveys, mobile surveys, and kiosk surveys

Interviews. For example: face-to-face interviews, telephone interviews, remote interviews

Longitudinal studies

Website interceptors

Online polls

Systematic observations

Experiments

Qualitative vs quantitative data

In terms of the actual data, here are some of the key differences:

Qualitative data is not countable. It’s chunks of text, photos, videos, and so on

Quantitative data can be counted as it’s numerical

Qualitative data is usually unstructured, which means it’s not ordered or grouped logically. You can turn qualitative data into structured quantitative data through analysis methods like

Most of the time qualitative data will be collected from a smaller sample size than quantitative data because, generally, you’re not looking for statistical significance with qualitative research

Qualitative data is quite rich, and can give you directional insights about people’s thoughts, feelings, emotions, and so on

Quantitative data can help to give you more confidence about a trend, and allow you to derive numerical facts

Imagine you’re looking down on a city from a helicopter at 5,000 feet. From here, you count all of the vehicles on a particular road, and conclude that 60 percent of vehicles are cars, 30 percent are trucks, and the rest are motorbikes. This would be a quantitative information. If you then landed on the ground and interviewed some motorbike riders about their thoughts on truck drivers, the notes or recording of those interviews would be qualitative data.

Turning qualitative data into quantitative data

You can turn qualitative data into quantitative data, and vice versa. They often blur, and you can represent the same data set in both ways.

Let’s consider a bunch of email conversations. In its raw form, this would be considered qualitative data. To answer the research question “what are the most popular greetings in emails?” you’d need to go through and sum all of the different occurrences of different greetings, then sort them by frequency. By doing this, you would have turned some unstructured qualitative data into a structured, countable insight.

How to analyze qualitative data and quantitative data

Once you have the data at your fingertips, you’ll need to learn how to analyze it in order to make meaning of it and answer your research questions.

Analyzing quantitative data

Because quantitative data is based on numbers, some form of mathematical analysis will be required. The methods range from simple maths like calculating means and medians, to more advanced statistical analysis like calculating the statistical significance of your results.

Tools like Excel, SPSS, or R can be used to calculate:

The mean scores of your data (also known as the average)

The frequency of a particular answer

The correlation or causation between two or more variables

The validity or statistical significance of your resultsQuantitative research approach

Let’s consider an example. If you were to measure user behavior on a website, you might learn that 25 percent of people clicked on this button, then this button, and so on. That’s good to know, and you can run split tests (otherwise known as “A/B” or “multivariate” testing) to try out different versions of your implementation to see if you can change people’s behaviors for the better.

However, this data doesn’t provide information on why people did what they did.

Qualitative research approach

Qualitative research generally focuses more on the human angle—what are people thinking and feeling? What’s their rationale for doing something? What’s their attitude or perception of something? You can get much richer/deeper information with qualitative data, because you can actually understand the intent behind action, and not just see the result of it.