Index number: 10717536 phil: 402



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Characteristics of a Good Inductive Reason 10717536

INDEX NUMBER: 10717536

PHIL: 402

QUESTION 1

What are the characteristics of good inductive reasoning?

Characteristics of a Good Inductive Reason


The primary activity of the scientific process starts with observations. It is the idea that scientific knowledge is derived from the method of induction. This is because induction regards observation as the primary activity of scientific observation and scientists use it to form hypotheses and theories. When making a decision, a person usually filters observations through their past experiences in a subconscious manner. For instance, it makes sense to assume you won't need an umbrella if the sky is sunny outside. This assumption is reasonable because it has been supported by numerous sunny days in the past. Since this line of thinking is based on specific experiences, observations, or facts, it serves as an example of inductive reasoning.[ CITATION Ind19 \l 1033 ] Unlike a deduction, inductive reasoning relies on the premises to provide some justification or proof that the conclusion will likely be true (not certain). The truth of the conclusion is not established or ensured by the premises. Then, to confirm the degree to which the conclusion is likely to be accurate given the strength of the evidence provided, the meanings of the content or information provided are important. Examples include inductive generalizations, statistical induction, causal inferences, analogical induction, predictive induction, and induction by confirmation[CITATION Ded22 \l 1033 ]. While one can use data and evidence to back up one’s claim or judgment there is still a chance that new facts or evidence will be u covered and prove your theory wrong.
This article or paper outlines the fundamental characteristics that make good deductive reasoning.
The accuracy of an inductively drawn conclusion depends on how thorough the observations were. As an illustration, say you have a bag of coins and you take out three pennies each. Then, based on inductive reasoning, you might suggest that all of the coins in the bag are pennies and that each coin removed from the bag was a penny. The conclusion drawn from inductive reasoning does not necessarily have to be accurate. This brings up the first property of good inductive reasoning, which is that it is predicated on assumptions (not certain)
Inductive reasoning relies on evidence and observation to reach a possible truth or conclusion. For instance, smoking raises the risk of developing cancer. Mr. X smokes. What is the likelihood that Mr. X will get cancer? Inferential statistics are used, as this illustration shows. As a result, the certainty of the conclusion is not assured by the premises. An inductive argument's evidence merely supports the hypothesis without proving it to be true. Although it cannot be assumed that Mr. X will develop cancer, smoking frequently can lead one to believe that Mr. X is more likely to do so. The validity of a scientific theory has also never been conclusively established. However, there is enough evidence to support it that it is accepted "beyond a reasonable doubt." The conclusions are changed if necessary to explain new evidence as it becomes available.
Another characteristic feature of good inductive reasoning is the use of background knowledge. In inductive reasoning with background knowledge, we, with regard to different examples and background knowledge focus on testable hypothesis generations. In fact, testable hypothesis generation is the most central assumption of inductive approaches. Accordingly, a hypothesis is a supposition or explanation made on bases on limited evidence as a starting point for further investigations (Badie, 2016)
Additionally, the degree of confirmation increases with the amount of evidence supporting the conclusion. Confirmation, though, does not equal proof. The term "confirmation" refers to the process whereby observational data and evidence speak for or support scientific theories or common hypotheses. As odd as it sounds, there is no such thing as proof in science, law, or many other fields; instead, conclusions are drawn from data and observations. Scientists can gather data that suggests a hypothesis is true, but they cannot prove it. Lawyers can offer evidence that appears indisputable, but they cannot prove that something occurred (or did not). The pursuit of truth is the core of reasoning. However, the truth isn't always as clear-cut as we'd like to think. The existence of absolute truth has been a topic of philosophical discussion for as long as we can remember. In general, if the evidence seems to support something, we can assume it to be true. The more evidence we have, the stronger our conclusion can be. Size matters when it comes to sampling. For instance, a murder occurs in a home where five other adults were present. Since there is no proof of anyone else entering the house, one of them is the main suspect. The initial likelihood that the main suspect killed the victim is 20%. If the four other witnesses claim that they saw the suspect commit the murder, additional evidence will be used to reevaluate the probability. Because the suspect's prints were found on the murder weapon and there were traces of the victim's blood on the suspect's clothing, jurors might conclude that the likelihood of the suspect's guilt is nearly certain enough to result in a conviction. A strong inductive reason must offer more data that can more strongly support a hypothesis. The style of inductive reasoning in our everyday life helps one to build one’s understanding of the world. Scientists gather data, through observations and experiments, make testable hypotheses based on that data and then test these theories further. Deductive reasoning confirms or disproves the internal logic of a theory, whereas inductive reasoning provides evidence in favor of a theory. Deductive reasoning sought to prove something, whereas inductive reasoning sought to discover a new piece of information. The pioneering work of Charles Darwin serves as a fitting illustration. He noted some differences between Darwin Finches on various islands of the Galapagos Archipelago. After some thought and deliberation, he proposed that all finches descended from a single common ancestor who then evolved and adapted via natural selection to take advantage of unoccupied ecological niches. He noted that the variation between the sub-species varied with distance and that these populations were geographically separated from one another. His Origin of Species was based on the fact that this caused evolutionary divergence and the emergence of new species. He used inductive reasoning to start with a specific piece of information and expand it into a broad hypothesis. But he also developed testable hypotheses and organized the internal logic of his experiments using deductive reasoning. [CITATION Mar \l 1033 ]. In essence, sound inductive reasoning combines the interpretive abilities of the observer with the analysis of observed events to provide new information on a subject or the information detailed in the conclusion. In as much as it generates a testable hypothesis, it should create room for criticism.
In conclusion, there must be more evidence supporting the conclusion for there to be a higher degree of confirmation, this will then be devoid of bias and create little room for criticism. 

References


CITATION Ind19 \l 1033 : , (Team, 2019),
CITATION Ded22 \l 1033 : , (Deductive vs Inductive Reasoning: Make Smarter Arguments, Better Decisions, and Stronger Conclusions, 2022),
CITATION Mar \l 1033 : , (Shuttleworth, & Wilson, n.d.),

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