Reflective Discussion Blog

     A linear model is a graph in which all the data points are plotted in a scatter plot and a line of best fit is included. This line has a slope (m) and a y-intercept (b) that illustrate the general trend of the data points. If the independent variable is doubled, the dependent variable will be twice the independent variable plus the y-intercept.      A proportional model is similar to a linear model because it also is a scatter plot that includes a line of best fit. What distinguishes a proportional model from a linear model is the fact that the line of best fit starts from the point (0,0). This means there is no y-intercept which in turn means that there is a direct proportional relationship between the data points and the line of best fit. There is a proportionality constant (A) that when multiplied by any of the independent variables will give you a value for the dependent variable. Here if the independent variable is doubled, the dependent variable ...

    The purpose of this investigation was to successfully create a free-weight scale that could accurately measure the weight of various objects in which its unit is quarters. In order to collect data, we had to calibrate the force being measured by the IOLab brick with the Ziploc bag connected and no quarters inside. This would give the tare, which we would then record its absolute value of the force being measured by the brick into IOLab and repeat this process after adding quarters one by one up to 5 quarters. Collecting the data with others was helpful because they would help me when I had issues with my IOLab brick or if I made a mistake with my graphs. The weight of 8 quarters would be about .46 Newtons. I made this prediction based on tracing the line of best fit of my graph until it reached the value at 8 on the x-axis. Here is my graph:

     Designing Friday's experiment was very interesting and informative. Thinking everything through and making sure that each of us where on the same page was crucial to the design of our experiment. We had to be particular about our investigation in order to accurately replicate it, as well as have other scientists do the same. We distinguished independent and dependent variables in order to clearly indicate what we are measuring and any relevant variables that can't be changed. Establishing the control variables is very important because it is another indicator to compare one's results of their experiment with. Without it, the results can be quite contradictory or ineffective.      The investigation we designed is science because we are measuring a natural phenomenon that can also be easily replicated. It is like a science because what we are ultimately studying is the effect gravity has on the velocity of a small object over a short distance. The result...

     Science is the study of nature and the universe around us, which can be further broken down into numerous branches. Such examples include Astrobiology, Chemistry, Physics, and others.      Umbrellaology is not a science. It doesn't explain the universe, nor are there any groundbreaking discoveries waiting to be made in this field. This idea is more closely related to Psychology as it seeks to explain correlation, likelihood, and statistical data among people and what type of umbrella(s) they own.     The difference between Umbrellaology and Zoology for example is that Zoology explains the organisms on our planet in its entirety. In Zoology, there are plenty of unknown phenomena as well as species that haven't been discovered yet. Also, organisms have been around for billions of years, have had significant impact on our world, and will most likely continue to do so for billions of years to come. That isn't the case with Umbrellaology. Umbrella...

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