Some people think that science and common sense are alike because science is a systematic and controlled extension of common sense, which is, in turn, a series of concepts and conceptual schemes satisfactory for practical uses. But science and common sense differ in two significant ways. First, their uses of conceptual schemes and theoretical structures are strikingly different. [1] (1. Since 2. While. Now that) the man in the street uses “theories” and concepts, he ordinarily does so in a loose fashion. He often accepts fanciful explanations of natural and human phenomena. An illness, for instance, may be thought to be a punishment for sin. The scientist, on the other hand, systematically builds her theoretical structures, tests them for [2] (1. internal 2. external 3. social) consistency, and subjects aspects of them [3] (1. for 2. to 3. through) empirical testing. Furthermore, she knows that the concepts she is using are manmade terms that may or may not exhibit a close relation to reality.
Secondly, the scientist systematically and empirically tests her hypotheses. The man in the street certainly tests his “hypotheses,” too, but he tests them in what might be [4] (1. defined 2. assumed 3. called) a selective fashion. He often “selects” evidence simply because it is consistent with his hypothesis. Take the stereotype: Fast food is bad for you. If some people believe this, they can easily “verify” their belief by noting that many kinds of fast food are unhealthy. [5] (1. Exceptions 2. Rules 3. Objectives) to the stereotype, such as healthy or low-fat fast foods, are not taken into account. The true social scientist, knowing this “selection tendency” to be a common psychological phenomenon, carefully guards her research against her own preconceptions and predilections, and avoids selecting only the kinds of data that support her hypotheses. Most importantly, she is not content with an armchair exploration of a relation; she feels it [6] ( 1. uncomfortable 2. obligatory 3. stressful) to test her hypothesis against empirical reality.She thus emphasizes the importance of systematic, controlled, and empirical testing of her hypotheses.
There is little doubt that hypotheses are important and indispensable tools for scientific research. Indeed you can call hypotheses the[７] ( 1. working 2. Newly-devised 3. Easy-toaccess) instruments of theory. Hypotheses can be deduced from theory. If, for instance, we are working on a theory of aggression, we are presumably looking for causes and effects of aggressive behavior. We might have observed cases of aggressive behavior occurring after frustrating circumstances. The theory, then, might include the following proposition: Frustration produces aggression. From this proposition, we may deduce more specific hypotheses, such as the following: Preventing children from reaching goals they find desirable (thus causing frustration) will result in their fighting with each other (i.e., aggression); If children are deprived of parental love (causing frustration), they will react, in part, with aggressive behavior.
The use of the hypothesis in scientific investigation is similar to playing a game of chance. The rules of the game are [8] ( 1. held forth 2.Set up 3. taken over, and bets are made, in advance. One cannot change the rules after an outcome,[9] ( 1. seldom 2. Never 3. Nor) can one change ones bet after making it. That would not be fair. One cannot throw the dice first and then bet. Similarly, if one gathers data first, then [10] (1. selects 2. throws 3. spares) only a few data and comes to a conclusion on the basis of those few data, one has violated the rules of the scientific game. The game would not be fair because the investigator could easily [11] (1. capitalize on 2. take over 3. give in), say, two significant relations out of five tested. What happens to the other three? They might be forgotten. But in a fair game every throw of the dice is counted, in the [12] (1. game 2. hypothesis 3. sense) that one either wins or does not win on the basis of the outcome of each throw. The main point is that the purpose of hypotheses is to direct inquiry. As Darwin pointed out long ago, all observations have to be for or against some view, if they are to be of any use.
Hypotheses are derived from theory. A good theory produces good hypotheses. And yet, it is also hypotheses that make theories better and sounder. There are two aspects to handling hypotheses: hypothesis making and hypothesis testing. [13] (1. Distinguishing 2. Discounting 3. Defending) these aspects are the key to seeing how hypotheses can contribute to theory. For example, Freud had a theory of anxiety that included the concept of “repression.” [14] (1. By 2. On 3. To) repression, Freud meant the forcing of unacceptable ideas into the unconscious. Testing Freud’s theory is thus a difficult matter, because the concepts of “repression” and the “unconscious” need to be defined in a measurable, empirical way. This is [15] (1. part 2. Soil. Most) of making a hypothesis and testing it empirically. If the concepts used in a hypothesis are operationally defined, that is, empirically testable, then a scientist can test the theory itself, and the theory can be improved upon. [16] (1. Relative to 2. Depending Oil 3. Owing to) the hypothesis-testing activity tests not only the hypothesis in question but also the validity of the theory under consideration.
Hypotheses are important in scientific investigation in that they can be tested and shown to be probably true or probably false. Isolated facts are not tested; only relations are tested. The fact that hypotheses are relational propositions is the main [17] (1. way 2. reason 3. argument) they are used in scientific inquiry. They are, in essence, predictions of the form, “If A, then B” which we set up to test the relation between A and B. We [18] (1. let 2. make 3. see) the facts have a chance to establish the probable truth or falsity of the hypothesis. A hypothesis is a prediction. It says that if x occurs, y will also occur. That is, y is predicted from x. If, then, x is made to occur, and it is observed that y also occurs, then the hypothesis is confirmed. This is more powerful evidence than simply observing, [19] (1. with reservations 2. within the limit 3. without prediction), the covering of x and y. The scientist makes a bet that x leads to y.If, in an experiment, x does lead to y, then she wins the bet.
She cannot just enter the game at any point and pick a perhaps accidental common occurrence of x and y. Games are not played this way. She must play according to the rules, and the rules in science are made to minimize error.
Hypotheses are an essential part of the rules of the game. The scientist disciplines the whole business by writing systematic and testable hypotheses. If an explanation cannot be formulated in the form of a testable hypothesis, then it can be considered to be a [20] (1. metaphysical 2. plausible 3. critical) explanation and thus not amenable to scientific investigation. As such, it is dismissed by the scientist as being of no interest.
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