Consider a random sample of size \(n = 50\). The sample mean and standard deviation are:
Use this sample to test \(H_0\colon \ \mu = 4 \ \text{ vs } \ H_1\colon \ \mu > 4\).
Report:
Consider a random sample of size \(n = 100\). The sample mean and standard deviation are:
Use this sample to test \(H_0\colon \ \mu = 0 \ \text{ vs } \ H_1\colon \ \mu \neq 0\).
Report:
Consider two independent random samples.
Sample 1, from Population \(X\):
Sample 2, from Population \(Y\):
Use these samples to test \(H_0\colon \ \mu_x = \mu_y \ \text{ vs } \ H_1\colon \ \mu_x \neq \mu_y\).
Report:
Consider two independent random samples.
Sample 1, from Population \(X\):
Sample 2, from Population \(Y\):
Use these samples to test \(H_0\colon \ \mu_x = \mu_y \ \text{ vs } \ H_1\colon \ \mu_x \neq \mu_y\).
Report:
Consider a random sample of size \(n = 50\) from a dichotomous population. The sample proportion of the “success” class is
Use this sample to test \(H_0\colon \ p = 0.50 \ \text{ vs } \ H_1\colon \ p \neq 0.50\).
Report:
Consider a random sample of size \(n = 100\) from a dichotomous population. The sample proportion of the “success” class is
Use this sample to test \(H_0\colon \ p = 0.70 \ \text{ vs } \ H_1\colon \ p > 0.70\).
Report:
Consider two independent random samples from dichotomous populations.
Sample 1, from Population \(X\):
Sample 2, from Population \(Y\):
Use these samples to test \(H_0\colon \ p_x = p_y \ \text{ vs } \ H_1\colon \ p_x \neq p_y\).
Report:
Consider two independent random samples from dichotomous populations.
Sample 1, from Population \(X\):
Sample 2, from Population \(Y\):
Use these samples to test \(H_0\colon \ p_x = p_y \ \text{ vs } \ H_1\colon \ p_x \neq p_y\).
Report:
Consider a random sample of size \(n = 12\) from a population that is assumed to be normal. The sample mean and standard deviation are:
Use this sample to test \(H_0\colon \ \mu = 4 \ \text{ vs } \ H_1\colon \ \mu > 4\).
Report:
Consider a random sample of size \(n = 8\) from a population that is assumed to be normal. The sample mean and standard deviation are:
Use this sample to test \(H_0\colon \ \mu = 0 \ \text{ vs } \ H_1\colon \ \mu < 0\).
Report:
Consider a random sample of size \(n = 12\) from a population that is assumed to be normal. The sample mean and standard deviation are:
Use this sample to test \(H_0\colon \ \sigma = 2 \ \text{ vs } \ H_1\colon \ \sigma > 2\).
Report:
Consider a random sample of size \(n = 22\) from a population that is assumed to be normal. The sample mean and standard deviation are:
Use this sample to test \(H_0\colon \ \sigma = 5 \ \text{ vs } \ H_1\colon \ \sigma > 5\).
Report:
Consider two independent random samples. Assume both populations are normal and that their variances are equal.
Sample 1, from Population \(X\):
Sample 2, from Population \(Y\):
Use these samples to test \(H_0\colon \ \mu_x = \mu_y \ \text{ vs } \ H_1\colon \ \mu_x \neq \mu_y\).
Report:
Consider two independent random samples. Assume both populations are normal and that their variances are equal.
Sample 1, from Population \(X\):
Sample 2, from Population \(Y\):
Use these samples to test \(H_0\colon \ \mu_x = \mu_y \ \text{ vs } \ H_1\colon \ \mu_x \neq \mu_y\).
Report: