Agree or disagree thoughtfully with the following statements in full detail regarding quantitative research to complement to or improve the discussion (Fully cite all resources in-text from recent peer-reviewed scientific journals and provide a reference section at the end) : Quantitative research is a systematic method of collecting and analyzing numerical data to answer scientific questions. It helps in summarizing, finding patterns, making predictions, testing causal associations, and generalizing results. Quantitative approaches provide logical, data-driven insights, addressing decision challenges when data is limited. Modern statistical methods combine multiple data sets into a single likelihood framework, avoiding loss of information caused by separate steps (Bhandari, 2023). Statistical inference methods use metrics like information theory, likelihood ratios, and probability to provide quantitative and qualitative results. Modern methods enable the combination of multiple types of data for improved inference. Intuitive decision making offers advantages like speed and adaptability in complex situations, but can be influenced by biases and emotions. Balancing intuition with analysis ensures informed decisions and correlates with better organizational performance in unstable environments. However, blindly following intuition is discouraged in today's data-driven world (Johnson, 1999).Allowing emotions and bias can compromise the research and the results could be altered. Significance testing is a crucial tool in ecology, used to evaluate hypotheses and draw conclusions from data. Null models are widely used in ecological research to test predictions of theory, assessing whether observed patterns or relationships differ significantly from what would be expected by chance. Null models have become more complex in ecological research, applied to areas like trait-mediated coexistence, food webs, community assembly, and diversity relationships. However, null-hypothesis-testing provides arbitrary dichotomies and is often superfluous when the null hypothesis is clearly false on a priori grounds. Therefore, evaluating the 'strength of evidence' is central to science (Burnham & Anderson, 2001). Assumptions are essential in science for interpreting test results and fostering trust. Acknowledging these assumptions enhances transparency and allows others to evaluate the robustness of conclusions. Independent testing of assumptions encourages further investigation and prevents errors. However, significance tests are often misused and misunderstood, and are not very informative for most ecological data. More satisfactory methods of inference, such as model-based inference, likelihood ratios, or Bayesian inference, assess the degree of support provided by data for hypotheses. Modern statistical methods combine multiple data sets into a single likelihood framework, avoiding loss of information (Gerrodette, 2011).
Agree or disagree thoughtfully with the following statements in full detail regarding quantitative research to complement to or improve the discussion (Fully cite all resources in-text from recent peer-reviewed scientific journals and provide a reference section at the end) :
Quantitative research is a systematic method of collecting and analyzing numerical data to answer scientific questions. It helps in summarizing, finding patterns, making predictions, testing causal associations, and generalizing results. Quantitative approaches provide logical, data-driven insights, addressing decision challenges when data is limited. Modern statistical methods combine multiple data sets into a single likelihood framework, avoiding loss of information caused by separate steps (Bhandari, 2023). Statistical inference methods use metrics like information theory, likelihood ratios, and probability to provide quantitative and qualitative results. Modern methods enable the combination of multiple types of data for improved inference. Intuitive decision making offers advantages like speed and adaptability in complex situations, but can be influenced by biases and emotions. Balancing intuition with analysis ensures informed decisions and
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