1. Researchers take a random sample of 100 patients who have experienced a myocardial infarction (MI, heart attack). They wish to estimate the average age at which an event occurs. A 95% confidence interval of the average age at the time of the event based on the sample of 100 was 59.8 to 68.5. What is the interpretation of this interval?

a. This interval gives a plausible range of values for the true average age of MI in the population of all patients from which the sample was taken.

b. Most (95%) of the patients in the sample had a heart attack between 59.8 and 68.5 years of age.

c. 95% of all heart attacks occurs between the ages of 59.8 to 68.5 in the population from which the sample was takem

d. This interval gives a plausible range of values for the average age of MI in this sample of 100 patients.

2. Generally speaking what is true about the 95% CI for a population level quantity (mean, proportion incidence rate)?

a. The 95% CI will always include the true value of the population level quantity.

b. The 95% CI provides a range of plausible values for the unobserved population level quantity by recognizing the uncertainty in the sample based estimate of this quantity.

c. 95% CIs can only be computed from the results of large samples.

d. 95% CIs from larger samples are more likely to include the true value of the population level quantity as compared to 95% CIs from smaller samples.

3. Suppose I take a sample of 500 employed Baltimore City residents and ask them their commute time to work today (how long it took them to get to work today in minutes). The standard deviation of these 500 values is 24.2 minutes and the standard error of the sample mean is 1.1 minutes. What do each of these values (standard deviation and standard error) quantify?

a. Both quantify the variability of the individual commute times in the sample of 500.

b. Standard deviation quantifies the variability of individual commute times in the sample of 500; standard error quantifies the variation in sample mean commute times across multiple random samples of 500 employed Baltimore City residents.

c. Standard error quantifies the variability of individual commute times in the sample of 500; standard deviation quantifies the variation in sample mean commute times across multiple random samples of 500 employed Baltimore City residents.

d. Both quantify the variation in sample mean commute times across multiple random samples of 500 employed Baltimore City residents.

Question

1. Researchers take a random sample of 100 patients who have experienced a myocardial infarction (MI, heart attack). They wish to estimate the average age at which an event occurs. A 95% confidence interval of the average age at the time of the event based on the sample of 100 was 59.8 to 68.5. What is the interpretation of this interval?

a. This interval gives a plausible range of values for the true average age of MI in the population of all patients from which the sample was taken.

b. Most (95%) of the patients in the sample had a heart attack between 59.8 and 68.5 years of age.

c. 95% of all heart attacks occurs between the ages of 59.8 to 68.5 in the population from which the sample was takem

d. This interval gives a plausible range of values for the average age of MI in this sample of 100 patients.

2. Generally speaking what is true about the 95% CI for a population level quantity (mean, proportion incidence rate)?

a. The 95% CI will always include the true value of the population level quantity.

b. The 95% CI provides a range of plausible values for the unobserved population level quantity by recognizing the uncertainty in the sample based estimate of this quantity.

c. 95% CIs can only be computed from the results of large samples.

d. 95% CIs from larger samples are more likely to include the true value of the population level quantity as compared to 95% CIs from smaller samples.

3. Suppose I take a sample of 500 employed Baltimore City residents and ask them their commute time to work today (how long it took them to get to work today in minutes). The standard deviation of these 500 values is 24.2 minutes and the standard error of the sample mean is 1.1 minutes. What do each of these values (standard deviation and standard error) quantify?

a. Both quantify the variability of the individual commute times in the sample of 500.

b. Standard deviation quantifies the variability of individual commute times in the sample of 500; standard error quantifies the variation in sample mean commute times across multiple random samples of 500 employed Baltimore City residents.

c. Standard error quantifies the variability of individual commute times in the sample of 500; standard deviation quantifies the variation in sample mean commute times across multiple random samples of 500 employed Baltimore City residents.

d. Both quantify the variation in sample mean commute times across multiple random samples of 500 employed Baltimore City residents.

Accepted Answer

NOTE- AS PER POLICY I HAVE CALCULATED FIRST MAIN QUESTION ONLY
Here Given 95% confidence interval of…