SCIENTIFIC INQUIRY WITH HYPOTHESIS TESTS

 INTRODUCTION

In this article when we consider the tests under the Scientific Inquiry: It is scientists study the natural world and propose explanations based on evidence derived by their work. Actually, hypothesis can turn the scientific test in to a logical reasoning process. Hypothesis are propositions that are made from the basis of reasoning. Confirmation & Acceptability are two words that can describe the outcome of the scientific inquiry. This outcome strength is depended on the evidential support of the hypothesis.

SCIENTIFIC INQUIRY

Scientific inquiry has two primary functions. Firstly, 
it provides a description of how scientific inquiry is 
conducted in practice. Secondly, it gives an 
explanation of why scientific inquiry is successful in 
arriving at genuine knowledge at the end of its 
process. Scientific inquiry extends beyond 
development of process skills such as observing, 
inferring, classifying, predicting, measuring, 
questioning, interpreting and analyzing data, which 
must occur in that order for proper scientific inquiry 
to happen. Scientific inquiry refers to the diverse 
ways in which scientists study the natural world and 
propose explanations based on the evidence derived 
from their work. Scientific inquiry includes the 
traditional science processes, but also refers to the 
combining of these processes with scientific 
knowledge, critical thinking and scientific reasoning 
to develop scientific knowledge.

The Parallels Between Philosophical Inquiry and Scientific Inquiry



The ‘community of inquiry’ as formulated by C. S. Peirce is grounded in the notion of communities of discipline‐based inquiry engaged in the construction of knowledge. The phrase ‘transforming the classroom into a community of inquiry’ is commonly understood as a pedagogical activity with a philosophical focus to guide classroom discussion. But it has a broader application. Integral to the method of the community of inquiry is the ability of the classroom teacher to actively engage in the theories and practices of discipline‐based communities of inquiry so as to become informed by the norms of the disciplines, not only to aspire to competence within the disciplines, but also to develop habits of self‐correction for reconstructing those same norms when faced with novel problems and solutions, including those in the classroom. This has implications for science education and the role of educational philosophy in developing students' ability to think scientifically. But it also has broader implications for thinking critically within all key learning areas. Here we concentrate on science education. We present the parallels between philosophical inquiry and scientific inquiry that need to be realised to promote and engage with scientific inquiry in the classroom. We also discuss the conflicts between philosophical inquiry and the way inquiry science in the classroom is portrayed in the education literature. Based on philosophical and historical perceptions of science as inquiry, a practical approach to implementation of scientific inquiry in the science classroom is presented.

Models Of Scientific Inquiry

Models of scientific inquiry have two functions: first, to provide a descriptive account of how scientific inquiry is carried out in practice, and second, to provide an explanatory account of why scientific inquiry succeeds as well as it appears to do in arriving at genuine knowledge.

The search for scientific knowledge ends far back into antiquity. At some point in the past, at least by the time of Aristotle, philosophers recognized that a fundamental distinction should be drawn between two kinds of scientific knowledge—roughly, knowledge that and knowledge why. It is one thing to know that each planet periodically reverses the direction of its motion with respect to the background of fixed stars; it is quite a different matter to know why. Knowledge of the former type is descriptive; knowledge of the latter type is explanatory. It is explanatory knowledge that provides scientific understanding of the world. (Salmon, 2006, pg. 3)

"Scientific inquiry refers to the diverse ways in which scientists study the natural world and propose explanations based on the evidence derived from their work."

HYPOTHESIS TESTS



Hypothesis testing is an act in statistics whereby an analyst tests an assumption regarding a population parameter. The methodology employed by the analyst depends on the nature of the data used and the reason for the analysis.Hypothesis testing is used to assess the plausibility of a hypothesis by using sample data. Such data may come from a larger population, or from a data-generating process. The word "population" will be used for both of these cases in the following descriptions.

How Hypothesis Testing Works




In hypothesis testing, an analyst tests a statistical sample, with the goal of providing evidence on the plausibility of the null hypothesis.Statistical analysts test a hypothesis by measuring and examining a random sample of the population being analyzed. All analysts use a random population sample to test two different hypotheses: the null hypothesis and the alternative hypothesis.The null hypothesis is usually a hypothesis of equality between population parameters; e.g., a null hypothesis may state that the population mean return is equal to zero. The alternative hypothesis is effectively the opposite of a null hypothesis (e.g., the population mean return is not equal to zero). Thus, they are mutually expensive,and only one can be true. However, one of the two hypotheses will always be true.

Steps of Hypothesis Testing


All hypotheses are tested using a four-step process:

  1. 1.The first step is for the analyst to state the two hypotheses so that only one can be right.
  2. 2.The next step is to formulate an analysis plan, which outlines how the data will be evaluated.
  3. 3.The third step is to carry out the plan and physically analyze the sample data.
  4. 4.The fourth and final step is to analyze the results and either reject the null hypothesis, or state that the null hypothesis is plausible, given the data.












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