Examlex

Solved

The Heights (In Cm) for a Random Sample of 60

question 65

Multiple Choice

The heights (in cm) for a random sample of 60 males were measured. The sample mean is 166.55, the standard deviation is 12.57, the sample kurtosis is 0.12, and the sample skewness is −0.23. The following table shows the heights subdivided into non-overlapping intervals. The heights (in cm)  for a random sample of 60 males were measured. The sample mean is 166.55, the standard deviation is 12.57, the sample kurtosis is 0.12, and the sample skewness is −0.23. The following table shows the heights subdivided into non-overlapping intervals.   For the goodness-of-fit test for normality, the null and alternative hypothesis are ________. A)  H<sub>0</sub>: Heights follow a normal distribution with mean 166.55 and standard deviation 12.46, H<sub>A</sub>: Heights do not follow a normal distribution with mean 166.55 and standard deviation 12.46 B)  H<sub>0</sub>: Heights do not follow a normal distribution with mean 166.55 and standard deviation 12.46, H<sub>A</sub>: Heights follow a normal distribution with mean 166.55 and standard deviation 12.46 C)  H<sub>0</sub>: Heights follow a normal distribution with mean 166.55 and standard deviation 12.57, H<sub>A</sub>: Heights do not follow a normal distribution with mean 166.55 and standard deviation 12.57 D)  H<sub>0</sub>: Heights do not follow a normal distribution with mean 166.55 and standard deviation 12.57, H<sub>A</sub>: Heights follow a normal distribution with mean 166.55 and standard deviation 12.57 For the goodness-of-fit test for normality, the null and alternative hypothesis are ________.


Definitions:

Customer Relationship Management

A technology for managing all your company's relationships and interactions with customers and potential customers.

Neural Networking

Refers to artificial neural networks, which are computing systems vaguely inspired by the biological neural networks of human brains.

Machine Learning

A subset of artificial intelligence that involves computers learning and improving from data without being explicitly programmed.

Deep Learning

A subset of machine learning where artificial neural networks learn from large amounts of data.

Related Questions