Free answer
SAMPLING
NAME:
INSTITUTION:
DATE:
It is evidence that was basing our argument on the analysis above; it is clear that several conclusions and observation can be met. The analysis gives us the importance of sampling and how it can be applied in real life. Through sampling, one can tend to understand the behavior and characteristic of an individual population without necessarily interviewing the entire population.
I found my own personal sample of 30 players by starting at the player named in the email that accompanied this assignment. Start counting with the next person on the list, and take every third person on the list until I get 30 people. The data can be found in the spreadsheet “Sample Data”.
Using Excel, we found the following five-number summary for the data “Weight”. The calculations were made in Excel.
|
Min |
Q1 |
Median |
Q3 |
Max |
|
175 |
196.25 |
217.50 |
238.75 |
300 |
We draw a box whisker plot of the sample data as follows:
Using Excel, we calculated that the sample mean was 220.6 pounds, and the sample standard deviation was 33.84 pounds. We used the sample mean of 220.6 pounds and sample standard deviation of 33.84 pounds to get an Empirical Rule graph as follows:
The maximum and the minimum values which were 175 and 300 respectively. Through the evaluation of data, we were able to obtain the median value as 217.50. The values were used to come up with a perfect and modern football field that can fit a game. This proofs that sampling can be used to code a game that can be utilized in a current phone or a computer hence making it one of the most significant aspect of programming.
The data was used to plot box-whisker, and it turned to be a perfect shape of the football field. The box-whisker was plotted using minimum and maximum values. The plot also demonstrated the upper and the lower quartile. The sampling is one of the most vital aspects of probability and statistic, hence gives the mean of the data. Sampling also helps in coming up with meaningful information.
As the population has a mean of 214.6 pounds with a population standard deviation of 42.2 pounds, the sample data has a mean of 220.60 pounds with a standard deviation of 33.84 pounds, which is very close to the population parameters. Thus, we would say that the sample statistics fairly represent the population parameters.
The above box whisker plot shows the data is skewed to right, so looks differently than the Empirical Rule graph. So, the data does not follow the Empirical Rule.
The sample standard deviation and the sample mean were used to construct empirical rule graph. The figure aids in getting the skewness of the data being analyzed. In the test distribution of normality, the empirical graph can also be used. The size of the deviations is calculated in the form of standard deviation and equated to the expected frequency. The normal skewed figure was applied in this case of analysis hence the data follow the empirical rule and can be used in the additional study.
Finally, it can be concluded that sampling has turned to be one of the most important aspects of the data analysis. It is clear that from the above analysis, sampling can be used to represent the entire population. When taking samples, one should be very careful so as to make the only correct data to avoid wrong analysis that leads to erroneous in conclusion.
