Logical fallacies -- those logical gaps that invalidate arguments -- aren't always easy to spot. While some come in the form of loud, glaring inconsistencies, others can easily fly under the radar, sneaking into everyday meetings and conversations undetected. Having an understanding of these basic logical fallacies can help you more confidently ...
In place of logical evidence, this fallacy substitutes examples from someone's personal experience. Arguments that rely heavily on anecdotal evidence tend to overlook the fact that one (possibly isolated) example can't stand alone as definitive proof of a greater premise.
Instead of acknowledging that most (if not all) issues can be thought of on a spectrum of possibilities and stances, the false dilemma fallacy asserts that there are only two mutually exclusive outcomes.
Slothful induction is the exact inverse of the hasty generalization fallacy above. This fallacy occurs when sufficient logical evidence strongly indicates a particular conclusion is true, but someone fails to acknowledge it, instead attributing the outcome to coincidence or something unrelated entirely.
The tu quoque fallacy (Latin for "you also") is an invalid attempt to discredit an opponent by answering criticism with criticism -- but never actually presenting a counterargument to the original disputed claim.
Often used to protect assertions that rely on universal generalizations (like "all Marketers love pie") this fallacy inaccurately deflects counterexamples to a claim by changing the positioning or conditions of the original claim to exclude the counterexample.
This fallacy occurs when your opponent over-simplifies or misrepresents your argument (i.e., setting up a "straw man") to make it easier to attack or refute. Instead of fully addressing your actual argument, speakers relying on this fallacy present a superficially similar -- but ultimately not equal -- version of your real stance, helping them create the illusion of easily defeating you.
The objective of this lab experiment is to determine the coefficients of velocity and discharge of two small orifices in the lab and compare them with values in textbooks and other reliable sources.
Orifices have many applications in engineering practice besides the metering of fluid flow in pipes and reservoirs. Flow entering a culvert or storm drain inlet may act as orifice flow; the bottom outlet of a dam is another example.
Statistics provide a way to summarize and interpret behavioral observations. Descriptive statistics, such as measures of central tendency, measures of variability, and graphical representations of data, summarize observations. Central tendency can be measured with the mean, median, or mode. The mean, the most common measure, has the advantage of considering the specific value of every score in the distribution. The median is often appropriate when the distribution of scores is skewed or contains a few extreme scores. The mode can be used when the data are measured on a nominal scale of measurement. Variability is most often measured using standard deviation, which provides an indication of how far, on average, scores are from the mean.
One is a statistical hypothesis that the experimenter expects to reject. It is referred to as the null hypothesis
Recall the distinction between deductive and inductive reasoning. With deductive reasoning, the truth of the conclusion is implicit in the assumptions. Either we draw a valid conclusion from the premises, or we do not. There is no in-between ground. This is not the case with inductive or scientific proof. Conclusions do not follow logically from a set of premises. Rather, they represent extensions of or generalizations based on empirical observations. Hence, in contrast to logical proof, scientific or inductive conclusions are not considered valid or invalid in any ultimate sense. Rather than being either right or wrong, we regard scientific propositions as having a given probability of being valid. If observation after observation confirms a proposition, we assign a high probability (approaching 1.00) to the validity of the proposition. If we have deep and abiding reservations about its validity, we may assign a probability that approaches 0. Note, however, we never establish scientific truth, nor do we disprove its validity, with absolute certainty.