Example Of Statistics: Application And Common Mistakes Creative Writing

Question 1.

The monthly average prices of regular gas is listed in the table below:
Question 2.
The mean value of a set is defined as the summation of all values divided by the number of values in the set. In the sample above, the mean value must be calculated as follows:
=mean= Sum of all the valuesnumber of values= $40.35812=$3.363

Question 3.

The median value of a set refers to the middle value when the data is arranged from lowest to highest. In the average monthly prices of regular gas, since there are twelve values, the average of the 6th, which is at $3.406, and 7th, which is at $3.487, values will be the median. Therefore:
median=$3.406+$3.4872=$3.447

Question 4.

The standard deviation of a set refers to the “closeness” of the values. In our example, the calculation for the standard deviation is as follows:
Standard deviation= σ= 1Ni=1n[Xi-(mean)]2
σ= 1121.316=0.331158

Question 5.

Figure 1. The graph shows the values of the average price of regular gas per month.

Question 6.

Figure 2. An example of a bar graph depicting the number of days that experienced snow during the months of December, January, February and March. (Source: Basic-mathematics.com)
In the figure shown above, the x-axis represents the number of days while the y-axis indicates the month. This graph, however simplistic, is very informative. In this graph, it is obvious that the number of days that experienced snow within a month can be concluded easily. For example, the month of December experienced 2 days with snow while the month of February experienced 14 days with snow. Therefore, this graph is successful in informing the viewers with its intended message.

Question 7.

Statistical data can sometimes be misleading. The interpretation of the results can be confusing and creates a great impact when publicized to a number of people. Especially in the medical field, statistics is often used to interpret the risks regarding illnesses and drugs.
The misleading part of statistics happens when the interpretation of the data is wrong. For example, the United Kingdom Committee on Safety of Medicines warned the public in 1995 that the use of third-generation oral contraceptive pills can increase the risk of developing a potentially fatal thrombosis in either the legs or lungs by twice, therefore, 100%. Of course, as the public sees that the chance of having a potentially fatal thrombosis in the legs or lungs becomes 100% after taking this third-generation oral contraceptive pills, it caused anxiety, and eventually, women stopped the consumption of the drug (Dye, 2008).
Unfortunately, the disseminated warning was erroneous in the sense that the data was badly interpreted. The actual studies had a sample of 14,000 women, 7,000 of which took the second-generation oral contraceptive pills while the remaining women took the third-generation oral contraceptive pills. There was only one case of thrombosis in the set who took the second-generation oral contraceptive pills, while the other set had two. Indeed, the increase was 100%, but still, they did not state that, previously, the risk was just one in 7,000 (Dye, 2008).
Therefore, it must be right to inform with full details. The scare should have been prevented if the committee issued the necessary information which includes the actual number of cases in both sets.

References:

“Bar graphs”. Basic-mathematics.com. Retrieved from <http://www.basic-mathematics.com/bar-graphs.html>
Dye, Lee. (15 October, 2008). Drug Claims Often Misleading. abcNEWS. Retrieved from <http://abcnews.go.com/Technology/story?id=6034371&page=1&singlePage=true>
U.S. EIA. (17 February 2015). U.S. Regular All Formulations Retail Gasoline Prices (Dollars per Gallon) [Data file]. Retrieved from <http://www.eia.gov/dnav/pet/hist/LeafHandler.ashx?n=PET&s=EMM_EPMR_PTE_NUS_DPG&f=M>