EXPERIMENT 3 Measurement Instruments (Mass, Volume, and Density) T Advance Study
ID: 1878790 • Letter: E
Question
EXPERIMENT 3 Measurement Instruments (Mass, Volume, and Density) T Advance Study Assignment Read the experiment and answer the following questions. is the least count of a measurement instrument, and how is it related to the number of significant figures of a measurement reading? 2. Does a laboratory balance measure weight or mass? Explain. What is the function of the vernier scale on the vernier caliper? Does it extend accuracy or precision? Explain. 3. istinguish between positive and negative zero errors and how corrections are made for such errors. For what kind of error does a zero correction correct?Explanation / Answer
1. The least count of a measurement instrument is "the smallest change in a value that can be measured with the measuring instrument". It is related to the precision of an instrument. The least count of an instrument is inversely proportional to the precision of an instrument.
2. A laboratory balance which measure mass because weight is the measurement of a gravitational pull and mass is the amount of matter in an object. We know that, scales are used to measure weight.
Weight is measured by using a spring balance or compression balance and the unit is "newton". Therefore, the unit for mass will be "kilogram" Or "gram".
3. The function of "Vernier scale" on the Vernier caliper is to measure the dimensions of rectangular objects and diameters of the circle. This instrument is consisting of two jaws such as lower jaw and upper jaw.
Lower jaw is used for measuring of diameter for cylindrical-shaped objects.
Upper jaw is used for measuring a distance between two surfaces of hallow cylindrical objects.
Basically, this tool is applied to extend a precision by increasing the number of divisions that can be read off.
4. A positive zero error is an error which indicate that there is a difference between a control group and experimental group when in fact, there is not.
Therefore, we falsely reject a null hypothesis when it is true.
A negative zero error is an error which state that there is no difference when in fact, there is.
Therefore, we accepting the nul hypothesis, when it is false.
One way to correct for these are to increase the sample size.
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