Relationship between Car price and Car investments

To explain how the study was set, in our group of four, we were randomly assigned to one of four parking areas, two of which were parking lots and the other two parking garages. As individuals, we compiled 4 datasets of 20 samples for each parking lot. The 20 samples have a split of 10 with and without transponders, ensuring a balanced datasets between parking areas. Data was collected at 1-4pm on two days a week for two weeks. Experimental designGiven the assigned parking area, we randomly selected 20 cars from the parking lot. We recorded the make and model of the car and whether or not they had a transponder, then took a picture of the back to later record the year. If the either set with or without transponder was not completed, we randomly selected more cars until the requirements of 10 cars with and without transponders were fulfilled. In order to reduce the chances of pseudoreplication in our design we framed the experiment by these key points. We measured in an implemented time range (1-4pm), randomized selection of vehicles in parking lots and implemented a balanced design in the form of same number of frequencies across datasets Data Input and Statistical AnalysisUsing the year, make and model we determined the price of the car through a constant source (KBB, 2019). Two 2-tailed t-tests were done that measured for the prices of garage parking vs lots, and the other test for with and without transponders in all parking areas.