Intelligence vs. Brain Size

Intelligence vs. Brain size Project 2 selective information Collection College Algebra 161 November 15, 2012 Intelligence vs. Brain size The Data Collection brook was designed to t all(prenominal) students how to collect, and organize, describe and document data using jump lists and graphs. I chose this particular subject to research to further my understanding of the flummoxment of human species. Can intelligence and mindset size be forthwith related, and as intelligence increases, what happens to the size of our brains? I conducted my research through the mesh by searching for previous, creditable research by someone prepare the in the field of Anthropology. The website that I found to have to most efficacious information needed to conduct an extensive research with adequate telescope history in the subject was Creation Studies. org. The website contained an article written by the institutes chief technical advisor, Steven Rowitt, Th. M. , Ph. D. After reviewing the infor mation contained in the article, I was able to formulate a hypothesis.My hypothesis is that as human race evolve, and intelligence increases, so does the size of the brain. The tools used in this tolerate were the website from which I obtained the information and Microsoft excel which I used to document and chart the data. exploitation that data I was able to formulate a graph, and a numerical model that could visitation and support my hypothesis. The graph shows you the trend of growth in brain size, per ____(one thousand years.However you decide to chart it)- The mathematical model explicate from the graphed data, will allow future visitationing to see if the trend stillness continues, or if the size of a human brain reaches a upper limit or minimum. The goal was to chart previous data collected by experts to support my hypothesis as well as predict and test the size of human brains in the future if the trend continued and develop a cable televisionar equating to represent t he findings. I began by amass 12 points of data of the average size of human brains at a specific time (years) in history.I recorded the average size of the brain in the year that correlated it. After collecting the data, I plot the data in Excel and used a best business fit to give me a running(a) par/ elongated fixing model to represent my data. See table below We entered the data is as follows The in mutually beneficial variable was the number of preventive stacks which represented the x axis. The dependent variable was how far the en fell, which represented the y axis. We chose a orbit of 0 to 25 because the number of rubber bands we used ranged from 0 bands to 15 bands.By choosing a domain or an x-axis of this amount, it gives you a graph that allows you to see the line past 15 rubber bands. We went with a range for of 0 to 90 inches because according to our data, the maximum number of inches that the egg dropped was 67 inches so in order to get a better picture of the data we widen the y-axis to 90 inches. The elongated regression model that fitted our data was D(r) = 3. 948r + 5. 758, with the y-intercept being (0, 5. 758) and m= 3. 948 inches.Interpretation for the data in the context of the study based on our linear regression model, is at zero rubber bands, the egg would go 5. 758 inches, and with each added rubber band the egg would fall an additional 3. 948 inches. To test this linear regression equation we were given a aloofness of 67 inches. To mathematically solve for 67 inches to predict the number of rubber bands needed, we solved for (r) as follows D(r) = 3. 948r + 5. 758 67(r) = 3. 948r + 5. 758 r = 15. 5 What we concluded from our mathematical prevision was that it would take 15. rubber bands to have a successful fall of 67 inches. Because it was not hard-nosed to use 15. 5 rubber bands, we went with 15 instead. This was a realistic prediction because the length that the egg fell was 66 inches, without imposing any cost to t he egg and leaving us 1 inch from the original test value of 67 inches. Had we used 16 rubber bands instead, based on our linear regression model which states that for every(prenominal) rubber band added the egg would fall an additional 3. 948 inches it would have left our fall around 69. 48 inches and as a expiry leaving us more than 2 inches from the original test value of 67 inches. Reasons for error in the thrust could be based on several components. The elasticity of the rubber bands varies from band to band which would cause a difference in the length of the fall and a change not resulting in a slope of 3. 948 inches. During the introductory part of the project, for an unknown reason, but not as a result of the test, the egg cracked, res ulting in a possible change in the diffusion of the weight of the egg and affecting the resulting length of the fall.And further more if our linear regression equation was tested in the future, the results may not be the same if another egg was used due to the mass of every egg varying. In summary, after testing several jumps involving a polar number of rubber bands each time and recording the corresponding length of how far the egg fell we had enough data to plot a scatter graph and formulate a linear regression equation that we could test any hypothesis without having to repeat the project itself.Discoveries made during the project was the close comparison in the tested data and the mathematical equation theorize by using excel or a scientific calculator. For an example when we tested 1 rubber band, the egg fell 10. 5 inches. Using the equation to solve for the answer D(r) = 3. 948(r) + 5. 758 D(r) = 3. 948(1) + 5. 758 D(r) = 9. 706 inches The experiment itself and the equation formulated from it, although not precise, it is an accurate representation of real outcomes of the amount of stretch in the rubber bands as shown in the comparison model above.