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False. Data at the ordinal level can be either quantitative or qualitative. In ordinal data, the categories have a meaningful order or rank, but the difference between the categories is not necessarily equal.
Quantitative techniques allow for data-driven decision-making, providing objective and measurable results. They can help identify trends, patterns, and relationships in data that may not be obvious through qualitative analysis alone. Additionally, quantitative techniques can be used to make predictions and forecasts based on statistical models.
Movie ratings can be considered as ordinal data, as they are often ranked or categorized based on a predefined scale (such as stars or numerical values).
Surveys can gather both qualitative and quantitative data, depending on the type of questions asked. Quantitative data is more common in surveys and typically measures things like demographics, preferences, satisfaction levels, and opinions. Qualitative data may also be collected through open-ended questions to capture more detailed or subjective responses.
Experimental research methods are most likely to produce quantitative data that can identify cause and effect relationships in sociology. This involves manipulating variables and observing the effects on outcomes.
Research can be divided into two main categories: qualitative research, which focuses on understanding the "why" and "how" behind phenomena through qualitative data analysis; and quantitative research, which focuses on collecting and analyzing numerical data to answer research questions through statistical methods.