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Introductory Lab: Domino Size & Density

Background

● Background Overview

○ Measurements

Physical measurements are more than a simple numerical value. They are specified by:

  1. A physical dimension which is a product of powers of base physical dimensions such as length, time, and mass. Other dimensions include, for example, electric charge.

  2. A choice of units. Usually we use SI units: meter (m), second (s), and kilogram (kg).

  3. A numerical value that depends on the choice of units.

  4. A range of the numerical value depending on the accuracy of measurements.

Calculations performed using physical quantities follow certain rules:

  1. Scalar physical quantities can be added or subtracted only if they have the same units.

  2. Scalars can be multiplied (or divided). The same action must be performed on the values and on the units.

Volume VV and mass mm are two measures of the size of an object. If an object is made of a uniform material, then doubling the amount of material will double both its mass and its volume. Density ρ\rho is ratio of mass to volume.

ρ=mV\rho=\frac{m}{V}

Density is a material property, independent of the amount of material or shape of the object. The volume of a rectangular parallelepiped shape, i.e., a box, is the product length times width times height, i.e.:

V=lwhV=l \cdot w \cdot h

○ Estimating Error

The accuracy of a measurement depends on the limits of the instrument, and on skill in using the instrument. One estimate of the accuracy of a measurement is to independently repeat the measurement multiple times and observe the range and standard deviation of the results. Another approach is to determine the instrument tolerance or precision.

Measurement errors change calculated or derived results in different ways, depending on how the quantities enter equations. For example, if the measured mass is larger than the actual mass, then the calculated density will also be larger that the actual density. Suppose, on-the-other-hand, that the measured volume is larger than the actual volume. Because the volume appears in the denominator of (1), the calculated density will be reduced.

Experimental Procedure

● Preview

Left) Dominoes provided. Right) Relevant length, width, height dimensions of the dominoes.

Figure 1:Left) Dominoes provided. Right) Relevant length, width, height dimensions of the dominoes.

Create data tables (See examples in ● Common Data and ● Trial Data):

Convert your measurements into SI units (e.g. kilogram kg, meter m, second s, etc.)

Calculate volume VV using (2), and density ρ\rho using (1).

You will now analyze your domino measurements in a few ways, through measurement uncertainties and through average and standard deviation (i.e. the spread of the data from the average).

Vmin=(lδl)(wδw)(hδh)V_{\min} = (l-\delta_l)\cdot(w-\delta_w)\cdot(h-\delta_h)
ρ=mminVmax=mδmVmax\rho = \frac{m_{\min}}{V_{\max}} = \frac{m-\delta_m}{V_{\max}}

At this point, you should have a complete trial with a range of densities based on your measurement uncertainties.

Does this range appear far from your estimated densities from the prior knowledge that these dominoes’ densities are close to that of water? If so, this is a good time to double check any of your measurements that may seem like an outlier or any of your calculations that may have been entered into Excel incorrectly.

Up to this point, each individual trial has its own range of densities based on the measurement uncertainties. If we were only analyzing individual trials, this can be satifactory for error analysis. However, each person measured each color domino. We can therefore also analyze the repeated measurements by looking at the average densities and the spread or variation of the data from that average value (i.e. standard deviation, often denoted as the Greek letter sigma, σ\sigma).

We will analyze the data in two ways, first by sorting your data by domino color (across all group members) and by person (across all domino colors). To do so, create two Data Analysis tables including (● Analysis Table 1 (by color)):

Based on your data, do you expect some or all of the dominos to float, sink, or stay neutrally buoyant in room-temperature water? Before you leave, there should be a bucket of water near the front of the lab, test it out!

Post-Lab Submission --- Interpretation of Results

● Finalized Spreadsheets

● Post-lab Writeup

The Whiteboard

Example data tables are shown below to assist you in building your spreadsheet for this first lab. Additionally the original whiteboard summary is at the end of this section.

● Common Data

Variable (units)Value
Mass uncertainty (SI units)
Caliper uncertainty (SI units)

● Trial Data

Trial numberGroup Member InitialsColorLength (measurement units, mm)Width (measurement units, mm)Height (measurement units, mm)Mass (measurement units, g)Length (SI units)Width (SI units)Height (SI units)Mass (SI units)Volume (SI units)Min Volume (SI units)Max Volume (SI units)Density (SI units)Min Density (SI units)Max Density (SI units)
1ABpink
2ABgreen
3ABorange
4ABblue
5CDpink
6CDgreen
7CDorange
8CDblue
9EFpink
10EFgreen
11EForange
12EFblue

● Analysis Table 1 (by color)

Length (units)Width (units)Height (units)Mass (units)Volume (units)Density (units)Did it float?
Avg pink
Avg green
Avg orange
Avg blue
Stdev pink
Stdev green
Stdev orange
Stdev blue

● Analysis Table 2 (by person)

Length (units)Width (units)Height (units)Mass (units)Volume (units)Density (units)
AB avg
AB stdev
CD avg
CD stdev
EF avg
EF stdev

● Original Whiteboard Info

Original whiteboard summary

Figure 2:Original whiteboard summary