Recently, a nurse commented that when a patient calls the medical advice line claiming to have...
Recently, a nurse commented that when a patient calls the medical advice line claiming to have the flu, the chance that he or she truly has the flu (and not just a nasty cold) is only about 4%. Of the next 25 patients calling in claiming to have the flu, let ? be the number of patients in the sample that actually have the flu.
Explain why ? can be treated as a binomial random variable.
• Specify (in words) which event would be defined as a “success”?
Homework Answers
In this scenario, the number of patients in the sample who actually have the flu, denoted as "?," can be treated as a binomial random variable. This is because each patient in the sample can be classified as either a success (having the flu) or a failure (not having the flu).
In a binomial random variable, there are two possible outcomes, success and failure, and each trial is independent of the others. In this case, each patient calling in claiming to have the flu can be considered as a separate trial.
The event defined as a "success" in this context would be a patient who actually has the flu. So, if a patient in the sample is diagnosed with the flu, it would be considered a success. Conversely, if a patient in the sample does not have the flu, it would be considered a failure.
The probability of success (having the flu) is given as approximately 4% or 0.04, and the probability of failure (not having the flu) would be the complement of this probability, which is 1 - 0.04 = 0.96.
By counting the number of patients in the sample who actually have the flu (?), we can observe the number of successes (patients with the flu) out of the 25 trials (25 patients calling in claiming to have the flu). Therefore, we can treat "?" as a binomial random variable with parameters n = 25 (number of trials) and p = 0.04 (probability of success).
This allows us to apply the properties and formulas associated with binomial distributions to analyze the probabilities and characteristics of the variable "?," such as calculating the mean, variance, and probabilities associated with specific outcomes.
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Recently, a nurse commented that when a patient calls the
medical advice line claiming to have...
Recently, a nurse commented that when a patient calls the medical advice line claiming to have...
Recently, a nurse commented that when a patient calls the medical advice line claiming to have the flu, the chance that he or she truly has the flu (and not just a nasty cold) is only about 4%. Of the next 25 patients calling in claiming to have the flu, we are interested in how many actually have the flu. On average, for every 25 patients calling in, how many do you expect to have the flu? (Enter your answer...
Recently, a nurse commented that when a patient calls the medical advice line claiming to have...
Recently, a nurse commented that when a patient calls the medical advice line claiming to have the flu, the chance that he or she truly has the flu (and not just a nasty cold) is only about 4%. Of the next 25 patients calling in claiming to have the flu, we are interested in how many actually have the flu. On average, for every 25 patients calling in, how many do you expect to have the flu? (Enter your answer...
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Recenty, a nurse commented that when ® patient cals the medicai advice le daining to have the nu, the dance that he or she tny屢the flu (and notjust a nasty cold)-ory about 4%, orthe next 25 patients calling in claiming to have the fu, we are interested in how many actually have the u Find the probabiliny that at least ive of the 25 patients actuaily have the lu (Round your answer to four dedmal places.)
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The data below are the ages and systolic blood pressures (measured in millimeters of mercury) of 9 randomly selected adults. Age 38 41 45 48 51 53 57 61 65 Pressure 116 120 123 131 142 145 148 150 152 a) Find equation of the regression line for this data b) Assuming these variables have a significant correlation, what is the best predicted value for blood pressure of an individual who...
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