Discussion: Descriptive Data Analysis
Discussion: Descriptive Data Analysis
Discussion: Descriptive Data Analysis
Descriptive Data Analysis
The following analysis is about the blood pressure effects of a contraceptive pill among women between the ages 35 and 44. Both continuous and discrete variables are present. This paper aims at utilizing a standard approach to presenting and understanding data through normal estimations.
Part One
Regarding the blood pressure values indicated in table 2A, it is a continuous variable. Blood pressure is considered a continuous variable since the values are obtained from measuring and not counting which applies to discrete variables. The application of value intervals is also a justification for blood pressure being a continuous variable, meaning that blood pressure can take any of the values in the applied intervals. Additionally, the data set for blood pressure also applies an infinity structure where it does not specify the minimum or maximum measurements (Chen, 2010).
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In the event that the number of women under both categories of users and non-users were identified, the number of women would be a discrete value. Primarily, the rationale for this position is that number of women would be obtained through counting as opposed to measuring which is used for the continuous variables (Chen, 2010). Furthermore, the number of women used for the blood pressure research is finite, providing a complete specified range of numbers. Moreover, the counting of women will only recognize distinct values such as 1, 2 or 3, meaning that there is no fraction of a woman. Subsequently, the women count would have the characteristic of isolated points and non-overlapping.
Part Two
Figure 1: Histogram of the Blood Pressure of Non-Users. (Source: http://www.zweigmedia.com/RealWorld/stats/histogram.html)
Figure 2: Histogram of the Blood Pressure of Users. (Source: http://www.zweigmedia.com/RealWorld/stats/histogram.html)
The use of the contraceptive pill can have a significant effect on the blood pressure of its users either through low or high blood pressure. However, according to the tabulated data on the use of the contraceptive pill, it has no significant effect on low blood pressure on its users. On the other hand, the pill is indicated to cause significant high blood pressure to its users. Compared to the non-users, the pill has a significant effect in causing increased high blood pressure. Normal measurements for blood pressure are medically recommended to be between 90 and 120 for systolic blood pressure. Therefore the inference about the effects of the pill on blood pressure is based on the higher percentages of women under users as depicted through the negative skewness
Part Three
Normal approximation of data is a technique used in the demonstration of data in estimated distributions. The normal approximation technique is effective in converting the intervals into units that are standard for ease of data explanations. In viewing the data on the systolic blood pressure of women aged between 35 and 44, normal approximations enabled the histogram to provide a normal curve that is symmetrical with value both below and above the data average. As a result, the set of data on the blood pressures can utilize a common standard deviation in providing data quality. In estimating the percentage of the women under a given range of blood pressure, it would follow that both the standard deviation and the average are computed for purposes obtaining standard units (Chen, 2010). This realization is in consideration that normal distributions develop data inferences about the mean (Chen, 2010).
Conclusion
In general, the application of normal distribution and approximation enable a harmonious integration of discrete and continuous variables. The above analysis is an illustration of processing data to obtain meaningful information. In this case, the conclusion is that the contraceptive pill causes significant blood pressure increases.
References
Chen, Y. (2010). Introduction to probability theory. The lecture notes on information theory. Duisburg-Essen University.
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