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SAMPLING

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From the above analysis, the several conclusion can be reached and also several observation. It is clear that after sampling we were able to get the entire time. After this, we were able to get the quintile range, median. This includes the upper and the lower quintile range that is Q1 and Q3. With this arrangement, we can be able to arrange the entire field and how the game is organized where most of the players are concentrated at the center of the field. This is turn to be one of the importance of sampling.
The data was able to give us a precise arrangement of how the field will look like. Sampling is used to make a code that will be employed in a computer or a phone as a football game. Without sampling, it can de hand to get those games operate. The sampling helps us to get the most relevant summary of the entire data. The minimum and the maximum value that turn to be 175 and 300 respectively, the lower quintile and the upper quintile that was 196.25 and 238.75 respectively. We were also able to get the median that was 217.50.
When a box-whisker of the samples was plotted, it turns to be a perfect shape of the football field is. The box and whisker plot deals with maximum and minimum values, shows the lower and the upper quartiles and is also based on the median. The sampling is one of the most important aspects of probability and statistic. It makes information and data to have to mean. It helps to come up with meaningful information.
We use excel to calculate a sample mean that was 220.6 pounds and the sample standard deviation was 33.84 pounds. The sample saves us the struggle of getting the entire population mean. It saves our time, and it is the best way to estimate the population mean and standard deviation of the data. The actual population means and the standard deviation were calculated as 214.6 pounds and 42.2 respectively. This indicates that the sample of statistic fairly represent the whole population hence can be used to make conclusions on behalf of the entire population.
The sample mean and the standard deviation were used to come up with the Empirical Rule graph. The Empirical Rule graph helps to get the skewness of the data alkalized. The rule is also applied in the distribution for normality test. The size of the deviations is computed in the form of standard deviation and compared to the expected frequency. In our case, we had a normal skewed graph. This means that the data follow the empirical rule and that the data can be used for further analysis.
In conclusion, it is found that data sampling is imperative in coming up with a varied determination and data analysis. We realized that in most cases a sample of data usually represents the entire population. It is important to put in mind that when taking samples we must be very careful to take only the correct data from the entire population. This helps not to transfer errors from the primary data to analysis. The sample if well corrected in most cases it represent the population. It is important to put in mind that once a sample one end up getting the wrong analyzed data that read to the bad conclusion.

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