Data Analysis Lab Report
The purpose of this experiment was to discover the suitable ways of organizing experimental data in the form of tables and graphs by proficiently using Microsoft Excel. After being provided with a set of experimental data, a graph is then created. The graph contains useful information such as the slope, which could give the density value. The calculation of significant figures was one of the key objectives in this lab as well. Significant figures are essential to interpreting data because they allow for increased precision and accuracy. Also, using Excel, the density calculations could be performed quickly and accurately. In this experiment, the density of water was found by collecting the masses known, which was volumes of water. To determine what the unknown density is, the mass should be divided by the volume.
The densities of water were obtained, by regulating the masses of samples of known volumes. In table 1 it includes the densities of 25.00 mL samples of water
In order to solve for density, first the mass must be known (which is in grams) and then find the volume (mL or cm3). Once the mass and volume are found, you divide the mass by the volume. The average for mass (g) is 24.89 and …show more content…
the average for density (g/mL) is 0.996. The standard deviation for mass (g) is 0.07 and the standard deviation for density (g/mL) is 0.003
The equation of the best-fit line in Activity B was very important when it comes to determining the slope. With the use of Microsoft Excel, being able to determine the best-fit equation wasn’t very difficult. Y=mx+b is the formula used for the best-fit equation. In this equation, the variable m is the slope. Since the density is found by dividing mass and volume, the slope of the graph is equivalent to the value listed for density Significant figures are important because with this concept, one can show how accurate and/or precise the data is. In order to reduce some uncertainty in data, one must maintain the proper amount of significant figures that need to be considered.
Standard deviation (SD) explains the differences among different dimensions.
SD is the unit to which different types of copies that change from the sample mean. SD informs us how the data is distributed when in regards to the mean. The less the standard deviation, the less uncertainty there is. This allows one to build more certainty relating to their experiment. A disadvantage, when it comes to including many points, is when fitting a curve, the points are not located near the averages. This can result in a lot of confusion with the linear equation. On the other hand, an advantage when it comes to including several points, when attempting to fit a portion of a non-linear curve to a line, is being able to develop a linear equation that demonstrates the data on the
curve.
The densities of water were obtained, by regulating the masses of samples of known volumes. In table 1 it includes the densities of 25.00 mL samples of water
In order to solve for density, first the mass must be known (which is in grams) and then find the volume (mL or cm3). Once the mass and volume are found, you divide the mass by the volume. The average for mass (g) is 24.89 and …show more content…
the average for density (g/mL) is 0.996. The standard deviation for mass (g) is 0.07 and the standard deviation for density (g/mL) is 0.003
The equation of the best-fit line in Activity B was very important when it comes to determining the slope. With the use of Microsoft Excel, being able to determine the best-fit equation wasn’t very difficult. Y=mx+b is the formula used for the best-fit equation. In this equation, the variable m is the slope. Since the density is found by dividing mass and volume, the slope of the graph is equivalent to the value listed for density Significant figures are important because with this concept, one can show how accurate and/or precise the data is. In order to reduce some uncertainty in data, one must maintain the proper amount of significant figures that need to be considered.
Standard deviation (SD) explains the differences among different dimensions.
SD is the unit to which different types of copies that change from the sample mean. SD informs us how the data is distributed when in regards to the mean. The less the standard deviation, the less uncertainty there is. This allows one to build more certainty relating to their experiment. A disadvantage, when it comes to including many points, is when fitting a curve, the points are not located near the averages. This can result in a lot of confusion with the linear equation. On the other hand, an advantage when it comes to including several points, when attempting to fit a portion of a non-linear curve to a line, is being able to develop a linear equation that demonstrates the data on the
curve.