Approximately 8.26% of patients in the Seasonal Effect data set contracted an SSI. If this happens...
- Approximately 8.26% of patients in the Seasonal Effect data set
contracted an SSI. If this happens completely randomly, in a random
selection of 10, calculate the following probabilities, from a
binomial distribution with parameters n=10 and p=0.0826. Show all
work.
- Identify the complement of {X≥1} and use the rule of complements to calculate the probability that at least 1 patient contracts an SSI, P(X≥1) (10%)
- probability that more than 1 but less than 5 patients contract an SSI, P(1<X<5) (10%) (Hint: use the cumulative probability function in excel).
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Approximately 8.26% of patients in the Seasonal Effect data set
contracted an SSI. If this happens...
Approximately 8.26% of patients in the Seasonal Effect data set contracted an SSI. If this happens...
Approximately 8.26% of patients in the Seasonal Effect data set contracted an SSI. If this happens completely randomly, calculate the probability that three randomly selected patients all contract an SSI in each of the following two ways: Using counting rules and probability trees (10%) Using the binomial distribution (hint: n=3, p=0.0826) (10%) Approximately 8.26% of patients in the Seasonal Effect data set contracted an SSI. If this happens completely randomly, in a random selection of 10, calculate the following probabilities,...
In the Seasonal Effect data set, an average of 20 patients develop an SSI each month....
In the Seasonal Effect data set, an average of 20 patients develop an SSI each month. For a randomly selected month in the year, calculate the following probabilities using the Poisson distribution. Show all work. Exactly 20 patients develop an SSI in the month, P(X=20) (10%) Use the cumulative distribution to calculate the probability that less than 10 patients develop an SSI in the month, P(X≤10) (10%) Side Note: there are 2919 total patients. Not sure if this information is...
The average BMI of the 241 patients who contracted an SSI in the Seasonal Effect data...
The average BMI of the 241 patients who contracted an SSI in the Seasonal Effect data set is approximately 27.9 with a sample standard deviation of approximately 6.53. Use this information to answer questions 4-6. 4. Use the Central Limit Theorem to calculate the standard error of the sample mean of the sample of 241 patients. Show your work. (5%) Please explain the steps as well so I understand.
A doctor knows from experience that 10% of the patients to whom she gives a certain...
A doctor knows from experience that 10% of the patients to whom she gives a certain drug will have undesirable side effects. Among the 13 patients to whom she gives the drug, find the following probabilities. (Give your answers correct to three decimal places.) (a) Find the probability P(At most two will have undesirable side effects). (b) Find the probability P(At least two will have undesirable side effects).[Hint: apply complement rule, P(at least 2) = 1 - p(less than 2)...
11. A medication has side effects. Given that nausea is a side effect, the probability is...
11. A medication has side effects. Given that nausea is a side effect, the probability is 0.42 for getting bad headaches. The probability for getting nausea is 0.32. The probability is for getting nausea and bad headaches. 12. The distribution function for X is F(x). Find the value of the density function at X = 6. Li F(x) = 0 0.27 0.51 0.78 1 x <5 5 <x< 6 6<x<7 7<x<8 x 8 f(6) 13. At a company, 75% of...
1. Approximately 30% of obese patients develop diabetes (p=0.3). If a physician sees 10 patients (n=10)...
1. Approximately 30% of obese patients develop diabetes (p=0.3). If a physician sees 10 patients (n=10) who are obese, what is the probability that half of them will develop diabetes (Pr X=5)? [Hint: use the binomial equation] A. 0.10 B. None are correct C. 249.8 D. 3.34 * 10-6 E. 0.01 2. Obesity is a growing problem in the U.S. and educators are looking to determine the probability of children in their schools becoming obese...
apter 1. Consider the following data on distances traveled by 100 people to visit the local...
apter 1. Consider the following data on distances traveled by 100 people to visit the local park. 1-8 30 25 20 15 10 9-16 17-24 25-32 33-40 Expand and construct the table adding columns for relative frequency and cumulative relative frequency. Then plot Histogram, Frequency Polygon and Ogive Curve. 2. Math test anxiety can be found throughout the general population. A study of 200 seniors at a local high school was conducted. The following table was produced from the data....
The data of a major referral hospital showed that most patients with ischemic heart disease (IHD)...
The data of a major referral hospital showed that most patients with ischemic heart disease (IHD) were black American. Based on this, it was concluded that black Americans are at higher risk of IHD compared to other community groups. How would you describe the conclusion? A. Correct, because risk factors for IHD are more common in black African American. B. Incorrect, because no test of statistical significance has been made C. Incorrect, because prevalence is used instead of incidence D....
The data of a major referral hospital showed that most patients with ischemic heart disease (IHD)...
The data of a major referral hospital showed that most patients with ischemic heart disease (IHD) were black American. Based on this, it was concluded that black Americans are at higher risk of IHD compared to other community groups. How would you describe the conclusion? A. Correct, because risk factors for IHD are more common in black African American. B. Incorrect, because no test of statistical significance has been made C. Incorrect, because prevalence is used instead of incidence D....
Please help ! Concepts to be familiar with: 1. Difference between populations (parameters) and samples (statistics):...
Please help !
Concepts to be familiar with: 1. Difference between populations (parameters) and samples (statistics): definitions and notation differences 2. Descriptive v. inferential statistics. What are they? What are their limitations? 3. Independent Variables (IVs) and Dependent Variables (DVs): definitions and how to recognize which is which in a study description 4. Discrete vs. continuous variables, apparent vs. real limits 5. Scales of measurement (N,O,I,R). Know what they are and examples of each. 6. Frequency tables: a. X, f,...
11. A medication has side effects. Given that nausea is a side effect, the probability is 0.42 for getting bad headaches. The probability for getting nausea is 0.32. The probability is for getting nausea and bad headaches. 12. The distribution function for X is F(x). Find the value of the density function at X = 6. Li F(x) = 0 0.27 0.51 0.78 1 x <5 5 <x< 6 6<x<7 7<x<8 x 8 f(6) 13. At a company, 75% of...
apter 1. Consider the following data on distances traveled by 100 people to visit the local park. 1-8 30 25 20 15 10 9-16 17-24 25-32 33-40 Expand and construct the table adding columns for relative frequency and cumulative relative frequency. Then plot Histogram, Frequency Polygon and Ogive Curve. 2. Math test anxiety can be found throughout the general population. A study of 200 seniors at a local high school was conducted. The following table was produced from the data....
Please help !
Concepts to be familiar with: 1. Difference between populations (parameters) and samples (statistics): definitions and notation differences 2. Descriptive v. inferential statistics. What are they? What are their limitations? 3. Independent Variables (IVs) and Dependent Variables (DVs): definitions and how to recognize which is which in a study description 4. Discrete vs. continuous variables, apparent vs. real limits 5. Scales of measurement (N,O,I,R). Know what they are and examples of each. 6. Frequency tables: a. X, f,...
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