Science and Experiment

 The theme of the reading material is all about the introduction to experimental physics. We need to learn about creating experiments, measuring observed variables, and assessing results. The core of science is said to be conceptions generated in the brain and compared with controlled experiments or observations. The first to be discussed in the book is experimental science. Experimental Science is a scientific test where someone performs a series of actions and carefully observes their effects to learn about something. The characteristic element of experimental science is that we have a measure of control over the conditions that produce observations. Physics is an excellent example of science in which we may control experimental factors like temperature, pressure, and others. An example of science in which we can do astronomical measurements, but the source of the observations is brutal to monitor. Before delving into the specifics of this experimental physics technique, it is worth considering its advantages and disadvantages. The researcher will need to devote a significant amount of time thoroughly studying experimental physics. Therefore, they have to believe in its value. One of the method's strengths is that they allow for precise control of extraneous and independent variables. Over the several preceding centuries, experimental science, with its related topics of engineering and technology, has progressed faster than any other field of significance to individuals. The improved grasp of how the cosmos runs and the range of applications in daily life has been immense. In every undertaking involving human beings, disputes will happen. Scientists solve theirs by subjecting them to the beautiful testing process through experiments. A person may desire to compare this with techniques utilized in pursuits such as religion, politics, and law, to name just three. Since imperfect human beings deploy technology, it is virtually inevitable that cheating will happen sometimes. The checks and balances proposed in the experimental approach often bring this to light sooner rather than later. The same applies when actual errors occur. Although the researcher's personality is often crucial in the success of a piece of labor, it does not intrude as much as in certain other occupations; objectivity is vital in science. Sometimes this includes adopting a unique form of scientific practice termed the "double-blind" approach. Consider what happens when a new drug's effect is tested on patients to illustrate the "double-blind" technique. Some patients who experience the placebo effect improve when given a harmless treatment simply because they expect to feel better.

Conversely, the doctor testing the new treatment may have a stake in its efficacy and guarded against the tendency to perceive the findings favorably. The double-blind strategy utilizes persons who construct a communication barrier between doctor and patient such that neither knows if the specific person has gotten the drug or placebo. Only when the answer once each patient has been examined is the doctor notified who got which treatment. Many of the abilities learned in experimental physics are applicable outside the laboratory. The study of experimental physics is no "ivory tower" system without application to the "real world." The fault resulting from human error may impact the empirical research findings throughout the long term. Other drawbacks of experimental research include the inability to control extraneous variables, the difficulty of measuring human responses, and the possibility of bias from participants. It takes substantial time to become proficient in the approach, not least because the only satisfactory means of learning is by doing, particularly in an experimental topic like science. Non-scientists do not generally comprehend the process. If a scientist cannot explain a study to a general audience, misinterpretations may occur. There is an extra challenge when scientists disagree on interest to the public, such as the degree of global warming projected in the future. The strategy is not ideal for many pursuits. Whereas it may aid in analyzing a painting or piece of music, it will add nothing to our enjoyment of the same. There is no mention of ethics; the process is as relevant to creating nuclear weapons as discovering medicines. It is up to the individual scientist, or those who set job restrictions, to instill a moral component into the system. To understand experimental physics, a thing to understand is to think about the four general skills required for its successful implementation: experimental design, data collection, data analysis, and experiment reporting. Any excellent work the scientist has done in other areas will be affected if they fail in one of these available talents. They are best studied together because the abilities are supposed to be combined. Experimental Design refers to the entire set of methods required to move a topic from a vague idea to a scientific journal report on an experiment. The initial step, determining what problem to research, is one of the most challenging for a newcomer. Students rarely have much input in this because of a lack of time and experience and must progress through a sequence of experiments to teach them basic procedures. The final stage, producing a report, is also critical because what good is good work if no one knows about it?

Data collection is the act of collecting and assessing the information on variables of interest in a systematic way that enables researchers to answer research questions, test hypotheses, and evaluate results. Because they are cheaply manufactured or entail simple counting, measurements sometimes show no variation when repeated. In scientific experiments, this is rarely the case, and the variability of repeated observations is an essential component of the data. We must agree on how to deal with this variability to advance science. Crude measurements are methods that attempt to rely on non-fully-specified elements of the world to ensure that an underdeveloped or underpowered solution manages to address the problem. Simple counting is another form of measurement wherein variability does not need to be anticipated is when we count a set number of things. Again, errors might well happen, but capable individuals will rapidly detect and remedy them. The significance of the measurement, and hence the care with which when conducted, will still differ. Because anyone can make a mistake when taking or recording a measurement, it is a good idea to take another one, even if it is to double-check the first. Second, we will not receive the same response each time we take a series of measurements of an experimental variable under what considers to be the same conditions. Although this variability will be less in a well-controlled experiment than in one with many variations in the settings, it is an important measurement property. The more measurements one takes, the more data one has. Do not, however, make the mistake of gathering data without regard for its quality; having a modest and well-defined variability is pointless if it is drowned by a systematic error, rendering all of their readings useless. We redo a measurement a few times, attempting to get the same result but failing. The reason is that we have not always been able to perfect the measurement conditions. When comparing the results to those of someone who has taken more care, they will see more variability in measurements when careless.

Data analysis in physics involves arranging and interpreting experimental data to validate a hypothesis or theory. It is a fundamental aspect of the scientific process, and it necessitates that students display high proficiency in critical scientific skills. We require a straightforward, agreed-upon approach for summarizing such data. In diagrams, there are two types of data visualization. A bar chart, for example, is a graph with measured values on the x-axis and the number of occurrences on the y-axis. It shows all the deals, but it does not deliver the collected time or order. When there are many measurements, the graph's shape might provide helpful information about the qualities of the data. Knowing the histogram's shape may compensate for this loss of data. Because it retains the measurement sequence, the second figure type is called a time series. The obtained values are represented on the y-axis, while the occurrence time lies on the x-axis. Because the times at which the measurements are uncertain, we exhibit them chronologically.

We need to enhance the visual method with a numerical overview of a significant quantity of data. There are two main applications of such a summary: First, generate a number that fairly depicts the "best" value to summarize the data combined with other numbers to illustrate the spread in values about this best value. Second, discern between good and poor data to treat them properly. We use the arithmetic mean, which we shall see is the best approximation we can make of the actual value we are seeking, given there are no systematic mistakes of substantial scale. The latter are covered later. The standard deviation defines the spread of our values, whereas the standard error indicates the variation of the norm from the actual values. We may design several metrics to fulfill the second, but there is no need to make another definition when the standard deviation would suffice. All other variables being equal, a data collection with a minor standard deviation (small spread) will be of superior quality. So if we combine two sets of data to reach an overall mean, for example, we will give higher weight to the one with a lesser standard deviation. That flippant statement "all other things being equal" includes a lot of experimental physics as it introduces the crucially important problem of systematic mistakes. Thus the ideal data set has a modest standard deviation and a small systematic error. The latter cannot be measured unless by comparing your data with someone else's, and if they differ, either one or both might be in mistake.

Experimenting with inanimate objects is not a problem, but living systems are more limited in what we can do to them. Stanley Milgram, an American psychologist, conducted a human behavior experiment published in his book Obedience to Authority. One might argue for hours about the legal and philosophical implications of obedience from many perspectives, but a scientific method would be to observe specific situations, or even better, conduct an experiment to see how individuals behave in practice. The investigation reported here was first carried out at Yale University and then replicated with over a thousand individuals at numerous other universities. Science must be accessible to all. After seeing the trainee strapped in, he is escorted to the next room and sits behind a powerful shock generator. The teacher got instructed to put the person in the other room for the exam. The teacher and experimenter frequently clash when the student feigns discomfort at low voltages. Should the teacher cease the experiment in response to this obvious discomfort, or should he continue to bow to the requests of the experimenter, who enjoins him to continue despite his hesitations? What is remarkable is how far people will go to follow the experimenter's directions; a sizable proportion of them persist until the last shock on the generator. The experiment's main finding is that adults are incredibly willing to go to nearly any length on the instruction of an authoritative figure.