the mean, and the precision signified show well the various measurements performed by same instrument on the same quality characteristic agree with each other. The difference between the mean of set of readings on the same quality characteristic and the true value is called as error. Less the error more accurate is the instrument. SENSITIVITY Sensitivity may be defined as the rate of displacement of the indicating device of an instrument, with respect mn to the measured quantity. In other words, sensitivity of an instrument is the ratio of the scale spacing to the scale division value. For example, if on a dial indicator, the scale spacing is 1.0 mm and the scale division value is 0.01 mm, then the sensitivity at any value of y=dx/dy, where dx and dy are increments of x and y, taken over the full instrument scale, the sensitivity is the slope of the curve at any value of y. The sensitivity may be constant or variable along the scale. In the first case we get linear transmission and in the second non-linear transmission.. Sensitivity refers to the ability of measuring device to detect mall differences in a quantity being measured. High sensitivity instruments may lead to drifts due to thermal or other effects, and indications may be less repeatable or less precise than that of the instrument of lower sensitivity. …show more content…
The distinction between the precision and accuracy will become clear by the following example. Several measurements are made one component by different types of instruments (A, B and C respectively) and the results are plotted. In any set of measurements, the individual measurements are scattered about the mean, and the precision signified show well the various measurements performed by same instrument on the same quality characteristic green with each other. The difference between the mean of set of readings on the same quality characteristic and the true value is called as
In order to find out what are some of the key drivers’ of the analysis I will further run different sensitivity analysis. I think some of the key drivers of our assumptions could be sales growth, production costs as a percentage of sales, inventories as a percentage of cost of goods sold etc.
...e been beneficial to the experiment. An error may have occurred due to the fact that measurements were taken by different individuals, so the calculations could have been inconsistent.
Household´s decision could be influence by wages for hired labor, wages for off-farm work, declines in crop yields (e.g. due to short rainy season or plant diseases) or yield increases (e.g. due to water availability, improve planting material). Therefore a sensitivity analysis is performed in order to see the household responses. For the sensitivity analysis to wages and yields, five levels of the factor were considered 0.5, 0.7, 1, 1.3 and 1.5. During the simulation run tested factor is kept constant at the initially chosen
If we look at the sensitivity analysis, we find as WACC increases, the percentage of US$360M investment in Deltex also increases. When WACC is 5.8%, the percentage of US$360M investment in Deltex is equal to 30% equity of Deltex.
I made a chart to record how my thermometer measured freezing and boiling water, and proceeded to find the average. I took the average of each, and used them to find the average inaccuracy of the thermometer. I found that the average inaccuracy of the thermometer for freezing water was of by 0.7°C or -0.7°C. The average inaccuracy of the thermometer for boiling water I recorded as off by 1°C or -1°C.
Reliable-Measuring what is actually intended to measure; not easy to manipulate; as objective and quantifiable as
Over the observed fifty seconds, there was a consistency among the temperatures. Without a calculated percent error, we are able to assume the average temperature was twenty-six degrees Celsius. There are factors that could have caused error to arise in our data collection. One factor could be that the temperature of the room was not consistent throughout the room. Another factor may have been the performance of the thermometer. The grasp in which the thermometer was held for procedure B may also be a factor.
In this experiment, there were several objectives. First, this lab was designed to determine the difference, if any, between the densities of Coke and Diet Coke. It was designed to evaluate the accuracy and precision of several lab equipment measurements. This lab was also designed to be an introduction to the LabQuest Data and the Logger Pro data analysis database. Random, systematic, and gross errors are errors made during experiments that can have significant effects to the results. Random errors do not really have a specific cause, but still causes a few of the measurements to either be a little high or a little low. Systematic errors occur when there are limitations or mistakes on lab equipment or lab procedures. These kinds of errors cause measurements to be either be always high or always low. The last kind of error is gross errors. Gross errors occur when machines or equipment fail completely. However, gross errors usually occur due to a personal mistake. For this experiment, the number of significant figures is very important and depends on the equipment being used. When using the volumetric pipette and burette, the measurements are rounded to the hundredth place while in a graduated cylinder, it is rounded to the tenth place.
Sensitivity analysis is a technique used to determine how different values of an independent variable will influence a particular dependent variable under a given set of assumptions. The presentation describes elements that affect health care staffing at Patton-Fuller, such as raises in wages and changes in the nurse-to-patient ratio.
Then, we multiply the result by 100 to get a percentage number. An example calculation from the 5.00mL pipet is: ((5.00mL - 4.9178mL)/5.00mL)*100 = 1.6438%. The percent error allows us to see which type of glassware is the most accurate at measuring substances. From our results, we concluded that the variable auto pipettor was the most accurate, since it had the lowest percent error, at 0.0500%. The volumetric pipet, volumetric flask, and burette, all had similar percent errors at 1.0430%, 0.6394%, and 0.6619%, respectively. These results indicate that these glassware types are still very accurate. Next, the graduated cylinder had a percent error of 1.6400%, which is still relatively low, indicating that the graduated cylinder is also very accurate. The beaker and erlenmeyer flask both had higher percent errors, at 7.5218%, and 9.4146%, respectively. The beaker and the erlenmeyer flask were not accurate at measuring substances. This is perhaps because they are larger, and are meant to hold larger volumes of water, or they are meant to contain and pour substances. After finding out
If we wish to measure a thing "A" then the test has to be able to measure "A" even when very little of "A" is present; this is sensitivity. Specificity means when we measure "A" with our test, we know that the test does not measure "B", "C," or "D."
... point was subjective; however it would have been a systematic error because I consistently judged the end point of my experiment. To eliminate this inaccuracy I should have used a colorimeter to judge the end point of my experiment.
Possible sources of error in this experiment include the inaccuracy of measurements, as correct measurements are vital for the experiment.
__C__ 8. Which of the following scales would be used when the information is qualitative rather than quantitative?
General uncertainty – the quality of the readings of most instruments decreases over time due to any number of environmental and internal factors, as frequent calibration is necessary. When several consecutive incorrect readings are taken for a liquid of known specific density, it is clear that the hydrometer is out of