Quantitative data is information that can be counted or measured and given a numerical value. Quantitative data can be used for mathematical calculations and statistical analysis. Program impact can be evaluated, and programming decisions can be made based on these mathematical derivations. Quantitative data can be used to determine:
Quantitative data is usually collected using surveys, experiments, phone interviews, polls, or questionnaires. Questionnaires and surveys are standard methods for collecting quantitative data.
Quantitative data should be properly analyzed to report program impact and make future programming decisions. Analyzing quantitative data can involve the following steps:
The data will need to be converted into quantifiable data by quantitative analysis. This involves organizing data properly to give it meaning. Data must be entered into a spreadsheet, organized, and coded.
This step involves associating measurement scales such as nominal, ordinal, interval, and ratio with the variables. This step is essential and helps arrange data in proper order within your spreadsheet.
It can be challenging to establish a pattern in the raw data; therefore, descriptive statistics help researchers find patterns within the data. Some commonly used descriptive statistics include:
These complex forms of analysis show the relationships between multiple variables to generalize results and make predictions. This can include:
For more information on quantitative research methods, contact firstname.lastname@example.org.
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