Select which of the following are examples of parameters from these examples.
Question options:
The probability that a ticket with be a winner is .2 (or a 20% chance)
The proportion of winning tickets in the sample of 100
99% of samples will have between 37% and 43% of voters favoring the candidate
The 40% of voters favor candidate C
The standard deviation for the 500 trials is .0224
53% of correct guesses detecting caffeine
The probability of detecting caffeine is .5
To determine which of the options are examples of parameters, we need to understand what a parameter is.
A parameter is a numerical characteristic of a population. It describes a population based on the entire dataset. Parameters are usually unknown and are estimated using sample statistics.
Now, let's analyze each option and determine if it is an example of a parameter:
1. The probability that a ticket will be a winner is 0.2 (or a 20% chance): This is not a parameter. It is a probability value associated with an individual ticket but does not describe the entire population.
2. The proportion of winning tickets in the sample of 100: This is an example of a parameter. It represents the proportion of winning tickets in a specific sample, which can be used to estimate the proportion of winning tickets in the entire population.
3. 99% of samples will have between 37% and 43% of voters favoring the candidate: This is not a parameter. It represents a range of values for a sample statistic, which is used to make inferences about the population parameter.
4. The 40% of voters favor candidate C: This is not a parameter. It represents a specific proportion of voters in a population but does not describe the entire population.
5. The standard deviation for the 500 trials is 0.0224: This is not a parameter. It is a measure of variability in a specific sample but does not describe the entire population.
6. 53% of correct guesses detecting caffeine: This is not a parameter. It represents a proportion in a specific sample but does not describe the entire population.
7. The probability of detecting caffeine is 0.5: This is not a parameter. It represents a probability value associated with a specific situation but does not describe the entire population.
Based on the analysis, option 2, "The proportion of winning tickets in the sample of 100," is the only example of a parameter.