Final answer:
The question deals with calculating the confidence interval for the population proportion of households with internet access in a large city using a simple random sample of 500 households, where 444 have internet access and the normal distribution approximation via the Central Limit Theorem is valid.
Step-by-step explanation:
The subject of the question asked by the student regarding a market survey organization's study on internet access refers to the concept of a confidence interval in the context of sample proportions. The Central Limit Theorem (CLT) is a fundamental statistical principle that allows us to use the normal distribution to approximate the sampling distribution of sample proportions when the sample size is sufficient, which is the case in this scenario with 500 households.
For a simple random sample of 500 households where 444 households had internet access, assuming a normal distribution approximation via the CLT, the student is likely interested in calculating the confidence interval for the population proportion of households with internet access. This is commonly done in statistics to estimate the proportion of a population with a certain characteristic based on sample data.
To calculate the confidence interval, we use the formula for the confidence interval of a population proportion, which is p±z*(sqrt(pq/n)), where p is the sample proportion, q is 1-p, z is the z-score corresponding to the desired confidence level, and n is the sample size. Applying this formula to the given data (where p = 444/500), we can compute the confidence interval that will estimate the true proportion of households in a large city with internet access.