Question

QUESTION 2 : Words: 200

What is the difference between Qualitative data and quantitative data?

Answer 1

Answer :

differences between quantitative & qualitative data;

• Definitions

Quantitative data is a group of quantifiable information that can be used for mathematical computations and statistical analysis which informs real-life decisions while qualitative data is a group of data that describes information.

Quantitative data is a combination of numeric values which depict relevant information. Qualitative data, on the other hand, uses descriptive approach towards expressing information.

• Another name

Quantitative data is also known as numerical data while qualitative data is also known as categorical data. This is because quantitative data are measured in the form of numbers or counts.for qualitative data, they are grouped into categories.

• Types

Quantitative data are of two types namely; discrete data and continuous data. Continuous data is further divided into interval data and ratio data.

Qualitative data, on the other hand, is also divided into two types, namely; nominal data and ordinal data. However, ordinal data is classified as quantitative in some cases.

• Examples

Some examples of quantitative data include Likert scale, interval sale etc. The Likert scale is a commonly used example of ordinal data and is of different types — 5 point to 7-point Likert scale.

Some qualitative data examples include name, gender, phone number etc. This data can be collected through open-ended questions, multiple-choice or closed open-ended questions.

• Characteristics

The characteristics of quantitative data include the following; it takes the numeric value with numeric properties, it has a standardised order scale, it is visualised using scatter plots, and dot plot, etc.

Qualitative data, on the other hand, may take numeric values but without numeric properties, does not have a standardised order scale And is visualised using a bar chart and pie chart.

• Analysis

Quantitative data analysis is grouped into two, namely; descriptive and inferential statistics. The methods include measures of central tendency, turf analysis, text analysis, conjoint analysis, trend analysis, etc.

Quantitative data analysis methods are however straightforward, where only mean and median analysis can be performed. In some cases, ordinal data analysis use univariate statistics, bivariate statistics, regression analysis etc. which are close substitutes to calculating some mean and standard deviation analysis.

• Tools

During the collection of qualitative data, researchers use tools like surveys, interviews, focus groups and observations, while Qualitative data is usually collected through surveys and interviews in a few cases. For example, when calculating the average height of students in a class, the students may be interviewed on what their height is instead of measuring the heights again.

• Collection Methods

Quantitative data is collected through closed-ended methods while qualitative data uses open-ended questions, multiple-choice questions, closed-ended and closed open-ended approach. This gives qualitative data a broader collection mode.

• Usage

Quantitative data is mostly used to carry out statistical calculations involving the use of arithmetic operations. Calculating the CGPA of a student, for example, will require finding the average of all grades.

Quantitative data, on the other hand, deals with descriptive information without adding or performing any operation with it. It is mainly used to collect personal information.

• Advantages

Quantitative data is compatible with most statistical analysis methods and as such is mostly used by researchers. Qualitative data, on the other hand, is only compatible with median and mode, making it have restricted applications.

Although, in some cases, alternative tests are carried out on ordinal data. For example, we use univariate statistics, bivariate statistics, regression analysis etc. as alternatives.

• Disadvantages:

Although very applicable in most statistical analysis, its standardised environment may limit the proper investigation. Quantitative research is strictly based on the researcher's point of view, thus limiting freedom of expression on the respondent's end.

This is not the case for qualitative research. Nominal data captures human emotions to an extent through open-ended questions. This may, however, cause the researcher to deal with irrelevant data.

Quantitative Data Examples

• Mean height in a class
• Measurement of physical objects
• The probability of an event occurring
• Random number generation
• Calculation of student's CGPA

Qualitative Data Examples

• Likert scale
• Data collected from a competitive analysis survey.
• Oral-job interview responses.
• Student biodata.
• Phone number
• Statistical compatibility

Quantitative data is compatible with most statistical methods, but qualitative data isn't. This may pose issues for researchers when performing data analysis.

This is part of the reason why researchers prefer using quantitative data for research.

• User-friendliness

Quantitative data collection methods are more user-friendly compared to that of qualitative data. Although open-ended questions may give the researchers much-needed information, it may get stressful for respondents.

Respondents like spending as little time as possible filling out surveys, and when it takes time, they may abandon it.