💯"Numbers reveal patterns; precision leads to discovery."💯
📢📢📢Characteristics of quantitative research enable researchers to identify patterns, test hypotheses, and make data-driven conclusions with measurable accuracy.
🔢 1. Contains measurable variables:
Quantitative research works with quantifiable data such as age, income, or temperature, allowing for comparisons and statistical analysis.
Example: In a study on academic performance, the measurable variable could be students' final grades.
🛠️ 2. Uses standardized research instruments:
Surveys, questionnaires, or sensors are applied using uniform procedures to ensure accuracy and minimize bias.
Example: A customer satisfaction study uses a questionnaire with closed-ended questions to measure responses consistently.
Sure, watch the following video to learn how to create a simple, accurate, and relevant questionnaire using the case study: Helen is trying to introduce a new product...
📊 3. Assumes a normal population distribution:
It assumes that data follows a normal curve, making statistical calculations and result extrapolation more effective.
Example: In a study on the average height of teenagers, most values cluster around the mean, with few extreme cases.
📉 4. Presents data in tables, graphs, or figures:
Information is visually organized to facilitate interpretation and comparisons between variables.
Example: In a market research study, survey results can be displayed in bar graphs comparing product preferences.
🔄 5. Uses repeatable methods:
The research is designed in a way that others can replicate it in different contexts and obtain similar results.
Example: An experiment on the effect of light on plant growth must follow specific steps that others can repeat.
🔮 6. Can predict outcomes:
Data analysis allows researchers to make projections about future trends or behaviors.
Example: A consumer habits study may predict an increase in product sales based on seasonal purchasing patterns.
📏 7. Uses measurement tools:
Scales, tests, or structured surveys convert responses into numerical data for analysis.
Example: An English proficiency test assigns a numeric score to evaluate participants' language skills.
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