Playing the lottery is a common game people engage in everyday. Within this game. It brings us statistics we can analyze and interpret. For this project the goal was to obtain results from 50 different drawings from Loafs “Pick 4” lottery results. By creating two histograms, the results were shared from finding the mean of the 50 sample means and also demonstrating the Orlando 200 dolts that were selected. To begin, finding the mean is defined as finding a measure of center that allows us to e the average number of the data set.
First, the mean of the 50 different drawings from the “Pick” lottery was found, resulting in 50 different sample means. Continuing on, the mean of the 50 sample means was taken to calculate to 4775. After this, standard deviation was found, the measure of variation of all values from the mean. From the data calculations, the standard deviation ended up to be 1. 505. The calculations obtained seem appropriate for a histogram graph because It allows n observer to see the means in a way that is clear and easy to analyze.
From looking at the two graphs it is apparent that the 200-digit histogram does not resemble a typical “bell shape” but the sample mean histogram does. Continuing on with my data it is apparent that the central limit theorem can be used. Since we have the (mean), o (standard deviation), and the sample size we can use the central theorem because the data is normally distributed. This is true because our sample size Is rater than 30, making x normal, thereby also making x bar normal.