Project Summary
Rocketry, aeronautics, and computer sciences have become very important fields of science since the Apollo projects in the 1970’s. In order to measure the different outcomes of each field, simulation programs were created. This allowed scientists to accurately predict the results of experiments without actually conducting them, saving them time, money, and in the case of rockets, maybe even lives.

After researching many of the required subjects, such as physics, calculus, and programming, as well as using our previous knowledge and problem solving skills, we decided to create a user-friendly JavaScript Program capable of accurately predicting the boost time, mass of the rocket, burn time, velocity at burnout, and the total altitude reached by a model rocket. This program will also account for air resistance, wind factors, and air humidity.

For this experiment, we tested the program for three different rocket lengths. After entering the required model rocket information into our program, as well as weather statistics, we retrieved the data from the program and recorded the values into a database. We then launched a model rocket 10 times per length for a total of 30 launches, calculated the altitude, boost time, and velocity, and recorded the data next to the corresponding program outputs.

In order to analyze our data, we entered our data into a t-test equation and found the calculated value for our experment's parameters. Each set of 10 launches was analyzed with its corresponding program outputs, leading to a total of 3 t-tests. After comparing the calculated value for 10 launches with the critical value, we found that the calculated value was higher; therefore, we rejected the null hypothesis. This showed that the distributions of the means of the program set and the actual value set had high variability. We repeated this process with the other two sets of data and received the same result. Because of this, we found that there was no significant difference between the program values and the actual values, signifying that our program was accurate.

The variable that the scientists changed throughout the experiment (independent variable) was the length of the rocket. The variable that was measured to compare and analyze data (dependent variable) was the altitude, boost time, and boost velocity of the physical rocket and the altitude, boost time, and boost velocity that the program predicted for the rocket. There were several control variables for this experiment to help keep the experiment fair and the conclusions unbiased. These were the Estes converter tubes, the rocket, the altimeter, and the JavaScript program.

#### Accuracy of a JavaScript Program in predicting Model Rocket Trajectory

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