Respuesta :
Answer:
D. We do not expect that exactly 23% of the sample participates in the textbook recycling program. We do expect that the sample proportion will be close to the population proportion, but it will vary by the sample error from sample to sample
B. The sample with size 400 will be closer to 23% because a larger sample size has a smaller standard error.
Step-by-step explanation:
The mean of sample can be estimated from the population. However, what we only get is the estimated mean of the sample which isn't the exact figure as that of the population. This slight variation in the mean value of the sample is due to sampling error.
According to the Central limit theorem, increasing the sample size yield a sample mean which continously converges to that of the population mean as the sampling error for such distribution drops lower and lower.
The true statements are:
- D. We do not expect that exactly 23% of the sample participates in the textbook recycling program. We do expect that the sample proportion will be close to the population proportion, but it will vary by the sample error from sample to sample Â
- B. The sample with size 400 will be closer to 23% because a larger sample size has a smaller standard error.
The given parameters are:
[tex]\mathbf{P(Recycling) = 23\%}[/tex]
This means that there is a 23% chance that a student in a college participates in textbook recycling
However, it does not mean that the probability is exactly 23% in a sample of 40 students.
This is so because, there may be error in the sampling of the population.
Hence, the true statement is (d)
According to central limit theorem, as the sample size increases, the sample error reduces.
This mean that the probability will be closer to 23% when the sample size increases to 400
Hence, the true statement is (b)
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