Friday, February 21, 2020

Using and interpreting statistics Essay Example | Topics and Well Written Essays - 2000 words

Using and interpreting statistics - Essay Example Statistics and biostatistics enabled medical practitioners to take apart authenticity from randomness and fiction as it steered organized reasoning, evaluation and decision-making, a vital component in the scientific sphere of medicine. Coupled to this are the advances in informatics' which made possible the treatment of huge quantity of data by highly developed and multifaceted analytical methods, refined samplings, or superior medical data linkage.Informational data from a study associated with childhood diabetes, informational data from a heart and lung surgery, and informational data from transfusion orthopaedic surgery were collected, tabulated and statistically treated with 95% confidence interval, risk ratio, probability, chi square, mean, standard deviation, standard error, regression.No category have a value of 4 or 13.33 percent gene A present while Yes category have a value of 14 or 46.67 percent. This means that there are minimal numbers of diabetics with gene A. The Sens itivity study of gene A is equal to 0.22222, which means that respondents with gene A and true gene A rate is quite low. Specificity is equal to 0.38095. This is almost one third of the probability of without gene A in health and true negative rate. The findings reveal that there is a 30% or 0.30 probability of gene A. This is also called the risk of gene A or the estimated probability.The probability of the exposed cases is equal to 0.4667 while the probability of the exposed in control is equal to 0.1333. The overall or total exposed has a value of 0.3000. With 95% confidence, the interval 1.410185 to 27.15574 contains the unknown mean . a) Based on the given informational data, the study design used is randomized controlled trial design. This is because it involved the random allocation of different interventions (or treatments) to subjects . b) The risk of childhood diabetes for individuals with gene A compared to those without gene A can be calculated using proportion statistics treatment of the data on Table 2. c) Yes, the data suggest evidence to support Ho: gene "A" is associated with childhood diabetes because 14 or 46.67 percent though indicating minimal numbers of diabetics with gene A, the Sensitivity study of gene A is equal to 0.22222. Thus, despite the low number of respondents with gene A its Specificity is equal to 0.38095. This is almost one third of the probability of without gene A in health and true negative rate. The findings reveal that there is a 30% or 0.30 probability of gene A in childhood. This is also called the risk of gene A or the estimated probability. d) This study aimed to find out if gene "A" is associated with childhood diabetes. The findings revealed diabetics under the No category have a value of 4 which is 13.33 percent gene A present while the Yes category have a value of 14 which is 46.67 percent. This means that there

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