Central Limit Theory Lab Report

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The goal of this lab was to test the central limit theory. The central limit theory is a process in which sample means can be collected and put together in such a way that the average of the averages can be taken. This allows, once enough samples are taken, for the average of the population to match the average of the sample close enough for any differences to not have any effect for the purposes of our lab. The larger the sample and the more samples taken, the more accurate the average of averages of the sample becomes to the population sample. In order to collect data, we used the years from pennies and the frequencies of those years to construct our tables. The goal of this lab was to educate us on how to use the central limit theory. …show more content…

We then gave the cup back and drew 5 pennies, 5 times, with shaking the cup in between trials. On our draw-36, we drew 36 pennies and returned the contents of the cup back to the population bag, which was shaken and received a new sample set 5 times. When adding the data into the spreadsheet we added with our own data collected, older data, which raised our number of trials. We then collected the min’s, max’s and mean’s for each category in the sample categories we also included the min of means, the max of means, the range of means, mean of means, standard deviation of means and the central limit thermos and the width that would be used for the graphs. While the population included the minimum, maximum, range, width, average, and the population standard deviation. For each category we included the class, class max, and the frequency except in the 36 category the class was not needed do to the class max being the same as it would have …show more content…

By following these formulas we calculated and concluded that this theory is true, especially with larger samples. However, during our experiment, errors occurred within the class data input. This was due to the fact that students wanted to get out of this lab quicker and incorrectly typed in the years that were written on the pennies. Plus, Jasmine wanted to make things “interesting” by adding incorrect data to make our lives “fun.” For example, some data could have been 2008 pennies, but were written down as 20008, which caused huge outliers. To address these issues, we looked at the max and mins which enabled us to see if there were outliers. From there we sorted the data, if there were outliers, to max and mins, and deleted THE ENTIRE ROWS of the incomplete data. This was necessary because if one data within that sample was incorrect, the whole sample was inaccurate and should not be

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