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A doctor used to believe that babies were equally likely to be born on any day of the week. However, with the rise in scheduled deliveries, the doctor now claims that babies are twice as likely to be born on a weekday (Monday through Friday) than on a weekend (Saturday and Sunday). To test this theory, she selects a random sample of 120 babies born this year and determines on which day of the week they were born. She would like to carry out a test of significance to test her claim. Are the conditions for inference met?

A. No, the random condition is not met.
B. No, the 10% condition is not met.
C. No, the large counts condition is not met.
D. Yes, all of the conditions for inference are met.

Answer :

Yes, all of the conditions for inference are met with each other.

What is the probability?

Probability is a measure of how likely it is for a particular event or outcome to occur. It is expressed as a decimal number between 0 and 1, or as a percentage between 0% and 100%.

Yes, all of the conditions for inference are met.

In order to carry out a test of significance, the following conditions must be met:

Independence: Each baby in the sample must be chosen independently of the others.

Random sampling: The babies in the sample must be chosen randomly from the population of all babies born this year.

Large counts: The sample must be large enough to accurately represent the population. In general, a sample size of at least 30 is considered sufficient for inference.

Hence, it seems that all of the conditions for inference are met. The babies in the sample were chosen independently of each other, the sample was chosen randomly from the population of all babies born this year, and the sample size (120 babies) is larger than 30. Therefore, the conditions for inference are met and the doctor can proceed with her test of significance.

To learn more about probability, visit:

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