Agreement with the True Value Is Called

CAUTION – Avoid excessive units created by calculators and spreadsheets. In the example above, we measured 50 plots and found that there were 4.5 + 0.5 plants/plot. When I finished the calculations in my spreadsheet, there were actually 4,423 plants per plot. But I made the informed decision to round up to the next half (0.5 plant). The number 4,423 implies that I could see fractions of a plant on 1/1000 (or 0.001). Sorry, I just can`t imagine 1/1000 of a plant and I don`t think it would be very helpful to make decisions based on the 1000th of a plant. Especially since I only measured 50 plots. Just because you can calculate numbers with many units beyond the decimal number doesn`t mean you should. Here are some guidelines: Precision refers to the proximity of a measurement or estimate to true. Accuracy refers to the correspondence of measurement and actual value and says nothing about the quality of the instrument. The instrument may be of high quality and yet not match the actual value. In the example above, it was assumed that the purpose of the clock is to measure the location of the sun as it seems to move in the sky. However, in our time zone system, the sun is only directly above us at twelve o`clock if you are in the middle of the time zone.

If you are on the eastern edge of the time zone, the sun is just above you around 11:30.m., while at the western edge, the sun is just above you around 12:30.m. Thus, at both edges, the twelve-hour reading does not correspond to the phenomenon that the sun is at the local zenith, and we could complain that the clock is not accurate. Here, the accuracy of the clock reading is influenced by our time zone system rather than a watch flaw. Technical errors can be divided into two categories: random errors and systematic errors. Random errors, as the name suggests, occur periodically, without discernible reason. A systematic error occurs if there is a problem with the device. For example, a ladder could be poorly calibrated and read 0.5 g with nothing on it. All measurements would therefore be overestimated by 0.5 g. If you do not take this into account in your measurement, your measurement will contain an error.

However, few things are certain when measuring vegetation. We often use averages to express what is called the “central tendency.” In the above example of the target and arrows, we are relatively accurate when the average of our shots (i.e. the central tendency) is close to the bull`s eye. An estimate of uncertainty (or data dissemination) is an expression of our accuracy. Suppose you measure the length of your desk with a ruler or tape measure, and the result was one meter and twenty centimeters (L = 1.20 m). Now, the true length is not known here, partly because you don`t have complete knowledge of how the meter was made and because you can`t see under the microscope to confirm that the edge of the table exactly matches the marks on the device. Therefore, in this case, you cannot discuss an error. Nevertheless, it does not seem with absolute certainty that L = 1.20 m. Grouping samples above their own mean is called standard deviation.

If we represent an error (e.B. 5cm) with a measurement (e.B. 180 cm), it does not mean an error, but due to experimental limitations, there is an uncertainty of 5cm in the specified value. Note that it is always possible to construct a very specific sentence. In the worst case, we could say that the desk is no shorter than zero meters and no longer than four meters (because it would not fit into the room). This measure may be almost useless, but it is completely safe! By specifying a confidence interval for a measurement, the scientist makes statements that any reasonable scientist must accept. The ability is to keep confidence intervals (uncertainty) as small as possible. Precision refers to the correspondence between a measure and the true or correct value. When a clock beats twelve, when the sun is just above them, it is said that the clock is accurate.

The measurement of the clock (twelve) and the phenomena it is supposed to measure (The Sun at its Zenith) coincide. Accuracy can only be meaningfully discussed if the actual value is known or recognizable. (Note: The actual value of a measure can never be known.) Accuracy refers to the repeatability of the measurement. It doesn`t require us to know the right or true value. If a watch displays exactly 10:17 a.m. every day for several years when the sun is at its zenith, that watch is very accurate. Since there are more than thirty million seconds in a year, this device is more accurate than one part in a million! It is indeed a very beautiful watch! You should note here that we don`t have to take into account the complications of the edges of time zones to decide that this is a good watch. The true meaning of noon is not important because we only care that the watch gives a reproducible result. The term precision (or variance) refers to the degree of agreement for a number of measures. As with accuracy, you need to know the true or correct value to discuss your error.

But think about what science is. The central goal is to discover new things. If they are new, then we do not know in advance what the true value is. Therefore, it is not possible to discuss our error. You can raise the possibility that the experiment has a faulty component or an incorrect assumption, so that a mistake is made. Of course, the scientist is concerned about this. As a rule, there have been many discussions with other scientists and a review of methods to avoid exactly this possibility. However, if an error occurs, we simply won`t know. The true value has not yet been established and there is no other guide. The good scientist assumes that the experiment is not imperfect. This is the only choice available.

Subsequent research, attempts by other scientists to repeat the result will hopefully reveal problems, but the first time there is no such guide. Accuracy indicates how close a measurement is to the correct value for that measurement. The accuracy of a measurement system refers to the proximity of the correspondence between repeated measurements (which are repeated under the same conditions). Measurements can be both accurate and precise, accurate but not accurate, accurate but not accurate, or neither. .

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