Inductive
Scientists use deductive reasoning and inductive reasoning when looking at problems. Deductive reasoning involves making specific conclusions based on general principles or theories. Inductive reasoning involves making generalizations or theories based on specific observations or evidence. Both types of reasoning are important in forming hypotheses, making predictions, and drawing conclusions in scientific research.
It is faulty logical reasoning. For example,1^1 = 1*1 2^2 = 2*2 conclusion: n^n = n*n WRONG!
answer: likely
what do we call a measure that is relatively unaffected by extreme observations
Data is the raw material used for collating information to represent the qualitative or quantitative attributes of a variable or variables. Valid data can be gathered using carefully controlled observations or measurements. Qualitative observations are observations which can not be recorded numerically, they are qualities rather than quantities. Examples of qualitative observations are colour, type of material or taste. These observations may form the basis of information representing the attributes of a variable and as such they are data. Some may argue that qualitative observations are not always data as they may be observations of opinion rather than fact, I disagree with this argument. The true definition of a theory is a well-substantiated explanation or a well organized system of accepted knowledge that applies in a variety of circumstances to explain a specific set of phenomena. A theory may also be defined as an unproven conjecture. The use of the the word theory to mean a statement of opinion which cannot be substantiated is technically a colloquialism and should be disregarded. Data are often viewed as the lowest level of abstraction from which information and knowledge are derived. As a theory is a system of accepted knowledge and knowledge is derived from data this suggests that a theory can not be data. Quantitative observations are observations which can be recorded numerically, they are quantities rather than qualities, such as shoe size, time, length or number of people. As with quantitative data, these observations may form the basis of information representing the attributes of a variable and as such they are data. Measurement of any quantity such as length, speed or pressure is the name given the process of estimating or determining the magnitude of a quantity or variable. Measurements by definition are representations of the attributes of a variable and as such they are data. Therefore a, c and d are data and b is not. Theories are not an example of data.
hypothesis
specific ideas to argue for a general idea.
Inductive reasoning is a type of reasoning where conclusions are made based on patterns and observations. It involves moving from specific observations to broader generalizations. It is probabilistic and does not guarantee certainty in the conclusions drawn.
Inductive reasoning involves making generalizations based on specific instances or observations. It is a bottom-up approach that uses specific examples to draw likely conclusions. This method is often used in scientific research and can lead to probable rather than absolute conclusions.
Inductive reasoning involves drawing general conclusions from specific observations or instances. Deductive reasoning involves deriving specific conclusions from general principles or premises. Both are methods of logical reasoning used to make inferences or predictions.
Inductive reasoning involves drawing general conclusions from specific observations or examples, while deductive reasoning involves starting with general premises and using them to reach specific conclusions. Inductive reasoning is more probabilistic and involves making educated guesses, while deductive reasoning is more logical and deterministic. Both types of reasoning are used to draw conclusions and make decisions in various fields such as science, mathematics, and philosophy.
Inductive reasoning is empirical in nature, meaning it is based on observations and past experiences. It involves drawing general conclusions from specific examples or instances. However, the conclusions reached through inductive reasoning are not guaranteed to be true, as they rely on the evidence available at the time.
general; specific
Inductive method is a research technique where specific observations are used to draw general conclusions or theories. It involves gathering and analyzing data to identify patterns or relationships that can lead to the development of theories or hypotheses. The goal is to derive broad generalizations from specific observations.
Induction is a logical process where reasoning moves from specific observations to general principles. It involves drawing conclusions based on patterns or trends observed in specific instances.
Inductive thinking involves making generalizations based on specific observations or examples. It involves moving from specific instances to broad generalizations without guaranteeing the truth of the conclusion.
Induction is a method of reasoning that involves making generalizations based on specific observations or evidence. It is used to infer patterns or conclusions from specific instances or cases. In science, induction is utilized to formulate hypotheses or theories based on experimental data and observations.