Why is the central limit theorem important to statistical analysis?
What will be an ideal response?
Although the normal distribution occurs frequently and describes many populations, it is not the only probability distribution in existence. The value of the central limit theorem is found in its conclusion that regardless of the shape of the population distribution (i.e. samples can come from any type of distribution), the sampling distribution of the mean will form a normal distribution. The central limit theorem provides the basis for considerable work in applied statistical analysis. Many random variables can be modeled as sums or means of independent random variables, and the normal distribution provides a good approximation of the true distribution. It can be applied to both discrete and continuous random variables.
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An entity that buys goods and sells them to customers at a markup is a:
A) merchandiser. B) service provider. C) manufacturer. D) producer.
The following transactions for the month of March have been journalized and posted to the proper accounts
Mar. 1 The business received $7,000 cash and issued common stock to stockholders. Mar. 2 Paid the first month's rent of $500. Mar 3 Purchased equipment by paying $2,000 cash and executing a note payable for $6,000. Mar. 4 Purchased office supplies for $700 cash. Mar. 5 Billed a client for $12,000 of design services completed. Mar. 6 Received $9,000 on account for the services previously recorded. What is the balance in Accounts Receivable? A) $9,000 B) $3,000 C) $6,000 D) $12,000