# Statistics – Qualitative Data Vs Quantitative Data

## Qualitative Data

Qualitative data is a set of information which can not be measured using numbers. It generally consist of words, subjective narratives. Result of an qualitative data analysis can come in form of highlighting key words, extracting information and concepts elaboration. For example, a study on parents perception about the current education system for their kids. The resulted information collected from them might be in narrative form and you need to deduce the analysis that they are satisfied, un-satisfied or need improvement in certain areas and so on.

### Strengh

·        Better understanding – Qualitative data gives a better understanding of the perspectives and needs of participants.

·        Provides Explaination – Qualitative data along with quantitative data can explain the result of the survey and can measure the correction of the quantitative data.

·        Better Identification of behavior patterns – Qualitative data can provide detailed information which can prove itself useful in identification of behaviorial patterns.

### Weakness

·        Lesser reachability – Being subjective in nature, small population is generally covered to represent the large population.

·        Time Consuming – Qualitative data is time consuming as large data is to be understood.

·        Possiblity of Bias – Being subjective analysis; evaluator bias is quite feasible.

## Quantitative Data

Quantitative data is a set of numbers collected from a group of people and involves statistical analysis.For example if you conduct a satisfaction survey from participants and ask them to rate their experience on a scale of 1 to 5. You can collect the ratings and being numerical in nature, you will use statistical techniques to draw conclusions about participants satisfaction.

### Strengh

·        Specific Quantitative data is clear and specific to the survey conducted.

·        High ReliabilityIf collected properly, quantitative data is normally accurate and hence highly reliable.

·        Easy communicationQuantitative data is easy to communicate and elaborate using charts, graphs etc.

·        Existing supportMany large datasets may be already present that can be analyzed to check the relevance of the survey.

### Weakness

·        Limited Options – Respondents are required to choose from limited options.

·        High Complexity – Qualitative data may need complex procedures to get correct sample.

·        Require Expertise – Analysis of qualitative data requires certain expertise in statistical analysis.