Comment pouvez-vous utiliser la recherche quantitative dans les politiques publiques ?

Depends on tools can show data searched for depends on focus. While searching is an easy task when armoured with key questions for the questions at hand.

In essence, the integration of quantitative research in public policy involves leveraging surveys for comprehensive data collection, employing statistical analyses to discern patterns, and establishing metrics for continuous evaluation. This evidence-based approach strengthens the foundation of policymaking, fostering solutions that are not only well-informed but also responsive to the evolving needs of society.

Often quantitative research involves collecting data for statistical analysis, however it can also focus on model building and simulation. Better still, a virtuous relationship between experiments in the real world can be created to improve models and simulation in virtual worlds. Working in robotics I find that concurrent co-simulation can also allow for scenario testing that might otherwise be impossible. Imagine self driving cars, moose crossing a road from both sides … you get the point. Tackle the impossible in simulation using data from less risky real experiments for model veracity and higher fidelity.

De uma forma geral a pesquisa quantitativa visa a avaliação numérica, ou matemática de questionamentos e tendências em diversas áreas, podendo é claro, ser utilizada em Políticas Públicas. Em um momento inicial a pesquisa quantitativa é suficiente para auxiliar na elaboração e continuidade das Políticas Públicas, mas em seguimento de implementação e principalmente em etapas de avaliação de resultados a pesquisa deve estar preparada para utilizar uma ferramenta qualitativa associada.

Quantitative research is vital in shaping public policy through statistical analysis. It identifies trends and public preferences, aiding prioritization. It assesses policy effectiveness using clear metrics for evidence-based decisions and efficient resource allocation. This research supports targeted policies by identifying specific demographics or regions. It also assists in cost-benefit analysis, weighing economic implications. In conclusion, quantitative research enhances policy effectiveness, ensuring resources are directed for maximum impact and contributing to informed, targeted, and economically viable policies.

SQL skills are a must for data analysis. The US Census bureau has excellent large statistical data sets free to the public for anyone who wants to try out data analysis with real world data without messing with your production database.

Again, while quantitative analysis often focuses on statistics, regression, T tests for significance assessment, it can also involve model building. Methods range from physical models using differential equations, to machine learning, to more traditional methods like curve fitting. The ability to compare methods and even combine them is powerful. For example sensor fusion using a Kalman filter or physics informed machine learning.

En lo personal, toda investigación debe traer consigo las habilidades, de hecho estás son las que nos facilitarán o complicarán la recolección de la información

Quantitative research in public policy demands skills in research design, data collection, analysis, and visualization. Crafting precise research questions and ensuring ethical data collection are pivotal. Proficiency in tools like Excel and SPSS for descriptive and inferential statistics is essential. My firsthand experience emphasizes the importance of translating complex findings into accessible visuals. These skills collectively empower researchers to contribute robust evidence for informed policymaking.

Para utilizar una gran cantidad de datos como por ejemplo series de tiempo de múltiples variables, entre otros muchos tipos de datos se requiere tener un nivel avanzado en la utilización de software como Excel y software estadísticos y econométricos como SSPD, STATA, MATLAB, entre muchos otros, así como saber interpretar y plasmar adecuadamente los resultados obtenidos mediante la utilización de estas herramientas.

Quantitative research steps: 1. Define problem 2. Review literature 3. Formulate hypotheses 4. Design research 5. Select participants 6. Collect data 7. Analyze data 8. Interpret results 9. Draw implications 10. Report findings

Me parece que hay que definir o identificar el problema, pues este será nuestro punto de partida, pienso que en segundo lugar hay que establecer el plan del que, él cómo y él cuando, ahí seguido está la recopilación de datos y por último la condensación de los mismos.

1. Define the Problem and Review Literature: ◦ Clearly define the research problem. ◦ Review existing literature and evidence. 2. Develop a Research Plan: ◦ Specify objectives, hypotheses, and design. ◦ Choose data type, source, sampling, collection, and analysis methods. 3. Data Collection: ◦ Implement the chosen method. ◦ Ensure data quality. 4. Data Analysis: ◦ Use software for processing, organization, and exploration. 5. Report Findings: ◦ Summarize and interpret results. ◦ Discuss implications for policymaking.

Los hallazgos obtenidos utilizando software estadísticos y econométricos deben ser validados adecuadamente para que los hallazgos no correspondan a resultados espúreos sin validez.

The integration of quantitative research in public policy is instrumental for evidence-based decision-making. Utilizing surveys, statistical analyses, and modeling techniques, policymakers can identify and prioritize key issues, measure the impact of existing policies, allocate resources effectively, and forecast outcomes of proposed interventions. Whether evaluating healthcare, education, infrastructure, or economic policies, quantitative research provides a robust framework for assessing the success and areas of improvement. Collaboration with experts and institutions is crucial to ensuring the reliability and relevance of the data, fostering a more informed and targeted approach to addressing the diverse challenges faced in the country.

Imagine quantitative research is your policy BFF, the cool buddy who brings the fun facts to the party. Think of it this way: without it, you're basically throwing a surprise party without checking if anyone likes Pizzas. Numbers spill the tea on what's really happening, but here's the thing, don't forget the stories! Sometimes people get so caught up in the numbers game that they forget the real-life stories behind them. It's like knowing how many pizzas were ordered but not if anyone actually enjoyed the party. So, let's keep it real, mix the numbers with the stories, and you've got the perfect policy!

Quantitative research is critical for objective inquiry and the scientific method. Measures can be direct or indirect and in some cases such as surveys, may also quantify subjective data. The key is to avoid trying to make data support preconceptions. Sometimes a negative outcome or null hypothesis can even be useful - disproving or showing that a change has no impact - no sensitivity. Keep an open mind.

Benefits of quantitative research: - Objectivity and standardized approach - Numerical precision and statistical analysis - Generalizability to larger populations - Comparability for comprehensive insights - Statistical significance and confidence in results - Replicability and validation of findings - Efficiency in handling large datasets - Identifying quantifiable trends - Supporting data-driven decision-making - Time and cost savings, especially in large-scale studies.

Quantitative research in public policy holds multiple benefits. It provides reliable evidence to support or challenge decisions, assumptions, or claims. Measuring the magnitude, frequency, or distribution of policy issues, as well as evaluating the impact and cost-effectiveness of solutions, enhances informed decision-making. My perspective emphasizes its ability to uncover causal factors and compare policy alternatives. Quantitative research also captures stakeholders' views, needs, and preferences, contributing to a comprehensive understanding of complex policy landscapes.

Pienso que sus desafíos dependerán de tres factores fundamentales, cultura, seguridad y accesibilidad. Además de la sinceridad de quienes responda y también que es solo percepción del momento.

Quantitative research in public policy presents various challenges. It can be time-consuming, expensive, and complex, especially when dealing with large and diverse datasets. Accessing and utilizing specific data sources may pose difficulties, and issues like bias, error, or uncertainty can impact results. The scope, design, and assumptions of the research may limit its applicability. Furthermore, misinterpretation by policymakers can compromise the validity and generalizability of findings, emphasizing the need for careful consideration and transparent communication in quantitative research for effective policymaking.

Todos los hallazgos obtenidos de esta forma deben ser validados y revalidados con diferentes pruebas estadísticas y econométricas, igualmente, la metodología y los hallazgos deben ser validados por pares, es decir, por expertos en la metodología utilizada, el software y las herramientas estadísticas y econométricas y el tema de investigación del que se trata.

En la investigación cuantitativa, la recopilación inicial de datos es esencial, pero resulta igualmente imperativo considerar la variable del sujeto y sus contextos no solo durante la fase de recopilación, sino también a lo largo de las etapas de análisis y representación de resultados. Tanto el sujeto como el objeto de estudio, independientemente de la política pública que se pretenda implementar a priori, no deben limitarse exclusivamente a la recopilación per se. Es fundamental reconocer que el objeto de estudio engloba tanto a individuos como a comunidades, contextualizando estas relaciones en términos geográficos, económicos y culturales, y no condicionándolas a los intereses transitorios de los gobiernos de turno.

Quantitative method can be used in socio-legal research, criminal justice, corporate law and family law by obtaining data from the raw materials of an investigation or using variables in questionnaires like gender, public perception towards the justice system, victim blaming scale, etc. Ethical issues arise from questionable practices around confidentiality, privacy, anonymity, informed consent, withholding information as to purpose of research, or causing information-providers physical or psychological harm. Ethical collection of data avoids bias and upholds professional integrity by explaining the research to participants, gatekeepers and funding bodies. Numbers should reflect social reality without defending any body or theory blindly.

Foremost, quantitative research is just regular research done with quantitative methods, or better still, quantitative methods applied to research. Regardless of the theme, data have three different source types: primary data (the data you produced for your research and purposes), secondary data (the data others produced for their research and purposes) and tertiary data (the data that index, list, abstract, summarize, organize, compile and/or digest the other). It’s difficult to think of public policy without experimental design, sampling techniques, descriptive statistics, content analysis and interviews with multisetorial representatives, different social sectors and strata, diversity is key. Public policy always boils down to people.