The quantitative research definition deals with numbers and digits while qualitative research deals with only words. There are significant differences between** qualitative and quantitative research **methods. **Qualitative research** describes the qualities of things in words. The quantitative research method is used to quantify the behaviors, opinions, and attitudes with the aim to accept or reject a hypothesis. Quantitative data are based on measurable quantities, values, and numbers. Thus the quantitative data are expressed in a numeric form such as duration, amount, price, size, height, length, and duration.

Such type of data that is based on numeric is considered more credible and objective. Data is gathered in numerical form that is further ranked and categorized with the help of measurable units and scales. Quantitative research method clearly specifies:

**1.** What is measured?

**2.** How is measured?

**Characteristics of quantitative research**

Following are the characteristics of quantitative research:

**1.** Data is collected by using structured research instruments like questionnaires, interviews, and surveys.

**2.** Sample sizes are chosen according to the size of the population so the samples truly represent the population.

**3.** The research study can be verified by others, which gives it high reliability.

**4.** It has clear research questions for which the research sought objective answers.

**5.** A comprehensive research methodology is defined before the data collection.

**6.** Data are in the numeric form that is arranged in tables, figures, and charts.

**7.** Its results may be generalized over a large population because of its objective nature.

**8.** Different tools are used like questionnaires and computer software to collect and analyze the data.

**Use of quantitative research **

Quantitative research is widely used in the fields of education, marketing, sociology, economics, demography, psychology, history, gender studies, gender studies, political science and health & human development.

**Methods of data collection**

**Qualitative data and quantitative data** are always contrasted to each other but here we are only concerned with quantitative data. **Kinds of qualitative research** methods are different from quantitative methods in may ways. Quantitative methods of data collection are based on quantifiable questions. Primarily quantitative data collection methods include interviews, questionnaires, and surveys. In this method the questions “how often?” and “how many?” are usually asked.

Quantitative data is collected in systematic so it can be analyzed with the help of computers to make tables and graphs from the given data. Questionnaires and interviews are based on a pre-defined set of questions. Questionnaires and interviews are administered by choosing the respondents randomly. When it comes to the discussion of results of research the quantitative data has an advantage over the qualitative data.

Quantitative data can be presented in the form of graphs and tables that gives it a comprehensive outlook. Quantitative data is easy to present, compare, generalize and summarize. The most common types of quantitative data collection include:

**1.** Interviews

**2.** Questionnaires

**3.** Probability sampling

**4.** Rating scales

**5.** Census

**Data Analysis**

Quantitative data analysis is closely related to the ideas of the scientific method, which includes the following:

**1.** Formulation of hypothesis

**2.** Development of methods for measurement

**3.** Development of instruments

**4.** Experimental control

**5.** Manipulation of variables

**6.** Collection of empirical data

**7.** Analysis of data

**8.** Results and findings

Quantitative data analysis widely uses statistical methods for data collection based on a hypothesis. A large sample of data is collected that is verified and validated before the analysis. Statistical methods are applied to quantitative data by using software packages.

The most commonly used software is SPSS (statistical package for social sciences). This software helps to correlate the variables and the frequency of responses. Furthermore, the simplest statistical formulas can be applied to the data by a single click. Most commonly used statistical methods are:

**1.** Measurement of frequencies

**2.** Measurement of central tendencies/averages

**3.** Standard deviations

**4.** Regressions

**5.** Correlation

**Limitations of quantitative research **

**1.** Experiments base on quantitative research cannot take place in natural settings.

**2.** Participants cannot explain their responses.

**3.** Good knowledge of statistical analysis is required to analyze and interpret the data. Poor knowledge may lead to wrong interpretations.

**4.** Large samples are required more accurate analysis

**5.** Small samples are less reliable to represent the whole quantitative data.

**Strengths of qualitative research**

**1.** Scientific objectivity is achieved in quantitative data analysis with the help of statistical approaches.

**2.** Software that is used for statistical analysis removes prolonged data analysis.

**3.** Quantitative data is in the numeric form so it is easy for others to recheck the results of numerical data.

**Points to remember while reporting the results of quantitative research**

Following points must be remembered when the results of a study using quantitative data analysis methods.

**1.** The researcher should explain which instruments are used to collect the data.

**2.** Explain the quantitative data collected and how they are statistically treated.

**3.** The researcher should report the unanticipated events which occurred during the data collection. The researcher should explain how his analysis differs from the planned analysis.

**4.** The researcher should provide a rationale for why those specific statistical procedures are selected to analyze the data. And he/she should specify the computer programs used for quantitative data analysis.

**5.** The researcher should describe the assumptions for all procedures to ensure that these assumptions are not violated to analyze the quantitative data.

**6.** When the researcher is using inferential statistics, he should provide the descriptive statistics, sample size, confidence interval, degree of freedom, the direction of variables and the level of significance.

**7.** The researcher should use tables, figures, and schedules to convey global effects.