### 统计代写|SPSS代写代考|Critical approaches

SPSS主要用于数据管理、高级分析、多变量分析、商业智能。

statistics-lab™ 为您的留学生涯保驾护航 在代写SPSS方面已经树立了自己的口碑, 保证靠谱, 高质且原创的统计Statistics代写服务。我们的专家在代写SPSS方面经验极为丰富，各种代写SPSS相关的作业也就用不着说。

• Statistical Inference 统计推断
• Statistical Computing 统计计算
• (Generalized) Linear Models 广义线性模型
• Statistical Machine Learning 统计机器学习
• Longitudinal Data Analysis 纵向数据分析
• Foundations of Data Science 数据科学基础

## 统计代写|SPSS代写代考|Critical approaches

Critical approaches are diverse and varied, so this term creates a broad umbrella. However, in general, these approaches hold that reality and truth are subjective (as does interpretivism) and that prevailing notions of reality and truth are constructed on the basis of power. Critical approaches tend to emphasize the importance of power, and that knowledge (and knowledge generation and validation systems) often serve to reinforce existing power relations. A range of approaches might fall into this umbrella, such as critical theory, feminist research, queer studies, critical race theory, and (dis)ability studies. Importantly, each of those perspectives also has substantial variability, with some work in those perspectives falling more into deconstructivism. Because in reality, there is wide variability in how people go about doing research, the lines between these rough categories are often blurred.

What can we know? We can know what realities have been constructed, and we can critically examine how they were constructed and what interests they serve. How do we generate and validate knowledge? Through tracing the ways that power and domination have shaped social realities. There is often an emphasis on locating and interrogating contradictions or ruptures in social realities that might provide insight into their role in power relations. There is also often an emphasis on advocacy, activism, and interrupting oppressive dynamics. What is the purpose of research? To create change in social realities and interrupt the dynamics of power and oppression.

## 统计代写|SPSS代写代考|Deconstructivism

Deconstructivism is another large umbrella term with a lot of diverse perspectives under it. These might be variously referred to as postmodernism, poststructuralism, deconstructivism, and many other perspectives. These perspectives generally hold that reality is unknowable, and that claims to such knowledge are self-destructive. Although truths might exist (or at least, truth claims exist), they are social constructions that consist of signs (not material realities) and are self-contradictory. Work in this perspective might question notions of reality and knowledge or might critique (or deconstruct) the ways that knowledges and truth claims have been assembled. There is some overlap with critical perspectives in that many deconstructivist perspectives also hold that the assemblages of signs and symbols that construe a social reality are shaped by power and domination.
What can we know? We cannot know in this perspective because there is a questioning of the existence of truth. We can, however, interrogate and deconstruct truth claims, their origins, and their investment with power. How do we generate and validate knowledge? In deconstructivist perspectives, researchers often critique or deconstruct existing knowledge claims rather than generating knowledge claims. This is because of the view that truth/knowledge claims are inherently contradictory and self-defeating. What is the purpose of research? To critique the world, knowledge, and knowability. One of the purposes of deconstructivist research is to challenge those notions, pushing others to rethink the systems of knowledge that they have accumulated.

## 统计代写|SPSS代写代考|Connecting epistemologies to perspectives and methods

In briefly reviewing major epistemological frames, we want to emphasize that epistemologies often do not fit neatly into these categories, nor are there only four kinds of epistemologies. These paradigms are quite expansive, and many researchers identify somewhere between these categories or with parts of more than one. In other words, the neatness with which we present these frames in this text is deceiving in that the reality of research and researchers is much messier, richer, and more diverse. One distinction that is common between qualitative and quantitative work is the openness with which researchers discuss their epistemological positions. Many qualitative researchers describe in some depth their epistemological and ideological positions in their published work. By contrast, the inclusion of that discussion is quite rare in published quantitative work. However, the ideological and epistemological stakes very much matter to the kinds of research a researcher does and the kinds of questions they ask.

One way that this happens is in the selection and mobilization of a theoretical perspective. As we described earlier in this chapter, good research questions are theoretically driven. Those theories have ideological and epistemological stakes. In other words, the selection of a theory or theoretical model for research is not a neutral or detached decision. Theories and their use emerge from particular epistemological stances and attempts to engage theories apart from their epistemological foundations are often frustrated. A key issue for this text, which focuses on quantitative analysis, is that most quantitative methods come from positivist and post-positivist epistemologies. One reason quantitative manuscripts often do not discuss epistemology is that there is a strong assumption of post-positivism in quantitative work. In fact, as we will discover in later chapters, the statistical models we have available are embedded with assumptions of positivism. That is not to say that all quantitative work must proceed from a post-positivist epistemology. However, being mindful of the foundations of quantitative methods in post-positivism, researchers who wish to engage these methods from other epistemological foundations will need to work with and in the tension that creates.

There is often some natural alignment between epistemology, theoretical perspective, and research method. Each method was created in response to a specific set of theoretical and epistemological beliefs. As a result, some methods more easily fit with certain theoretical perspectives which more easily fit with a particular epistemology. We have hinted at the fact that quantitative methods were designed for post-positivist work and thus fit more easily with that epistemology. There is also an array of theoretical perspectives that emerge from post-positivist work that are thus more easily integrated in quantitative work. But to reiterate it is possible to do interpretivist or critical work using quantitative methods. In future chapters, we will highlight some case studies that do so. Any such work requires careful reflection and thought, especially about the assumptions of quantitative work, and must be done carefully. Regardless of your position, we strongly urge students and researchers to consider their own epistemological beliefs and how they influence and shape the directions of their research.

## 广义线性模型代考

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## MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。