Quantitative research has its own set of strengths and limitations. Let's fill in the corresponding spaces with the appropriate details.
\begin{tabular}{|l|l|}
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\multicolumn{1}{|c|}{Strengths} & \multicolumn{1}{|c|}{Limitations} \\
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1. Allows for a broader study, involving a greater number of subjects, and enhancing the generalizability of the results. & 1. Typically requires a large sample size, which may not always be feasible or available. \\
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2. Facilitates objective measurements and statistical analysis, providing clarity and precision in the interpretation of data. & 2. Lacks in-depth insight into the context or the specifics of individual cases. \\
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3. Results can be, to some extent, replicated or extended by other researchers, enhancing the reliability of findings. & 3. May not be able to capture the nuance or complexity of phenomena as well as qualitative research methods. \\
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4. Data collected can be transformed into usable statistics, supporting the development of models and theories. & 4. Often relies heavily on instruments such as questionnaires, which may be subject to bias. \\
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5. Enables the verification or establishment of relationships between variables, aiding in predictive analysis and theory testing. & 5. Can be expensive and time-consuming due to the scale of data collection and analysis required. \\
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\end{tabular}
By understanding both the strengths and limitations of quantitative research, researchers can better design their studies and choose appropriate methods to explore their questions effectively.
