Average Weight among the Cancer Patients

Average Weight among the Cancer Patients


Choose a topic of study that is tracked (or that you would like to see tracked) from your place of work. Discuss the variable and parameter (mean or proportion) you chose, and explain why you would use these to create an interval that captures the true value of the parameter of patients with 95% confidence. Consider the following:
How would changing the confidence interval to 90% or 99% affect the study? Which of these values (90%, 95%, or 99%) would best suit the confidence level according to the type of study chosen? How might the study findings be presented to those in charge in an attempt to affect change at the workplace?






Evaluation of the Average Weight Among Cervical Cancer Patients

Among the anthropometrics measurements, weight issues are concern amongst the cancer patients, especially those receiving chemotherapy. As such, using a random sample of weights of 10 cervical cancer patients in a public hospital, the average weight and sample standard deviation were computed as 40.9 kg and 2.42, respectively. The variable of interest in this assessment is the weight of the cervical cancer patient, which is assumes a continuous level of measurement. In this case, the researcher took a random sample of the weights of 10 patients from the hospital records and calculated the average weight and the sample standard deviation. To evaluate the true average weight of cervical cancer patients, we need to compute a 95% confidence interval that gives the range of values where the true average weight lies. A 95% confidence interval is computed as:


The results suggested that we are 95% confident that the true average weight among cervical cancer patients lies between 39.4 and 42.4 kilograms. We choose to use a 95% confidence level since it is the most commonly used in public health; with a 95% confidence interval, we have a 5% chance of making an error in estimating the true parameter.

However, changing the confidence level to 90% or 99% will change the confidence interval. With a 90% confidence interval, we have a 10% chance of making an error to estimate the population parameter. With a 99% confidence interval, we have a 1% chance of making an error in estimating the population parameter. A 90% confidence interval has 1.645, 95% has 1.96, and 99% has 2.58 critical value obtained from z-distribution tables. In this regard, a 99% confidence interval would be wider than a 95% confidence interval, and a 90% confidence interval would be narrower than a 95% confidence interval. Therefore, when testing the claim about the true average weight of cervical cancer patients based on the previous studies, it would be better to use a 95% confidence interval with a large sample. Nonetheless, it would give a more precise interval than a 90% or 99% confidence interval.