According to a survey in a country, 21% of adults do not own a credit card. Suppose a simple random sample of 200 adults is obtained. Complete parts (a) through (d) below. Click here to view the standard normal distribution table (page 1). Click here to view the standard normal distribution table (page 2). = 0.21 (Round to two decimal places as needed.) Determine the standard deviation of the sampling distribution of p. GA = 0.029 (Round to three decimal piaces as needed.) (b) What is the probability that in a random sample of 200 adults, more than 25% do not own a credit card? The probability is 0.0838 (Round to four decimal places as needed.) Interpret this probability. If 100 different random samples of 200 adults were obtained, one would expect 8 to result in more than 25% not owning a credit card. (Round to the nearest integer as needed.) (c) What is the probability that in a random sample of 200 adults, between 20% and 25% do not own a credit card? The probability is 0.5493 (Round to four decimal places as needed.) Interpret this probability. If 100 different random (Round to the nearest integer as needed.) of 200 adults were obtained, would expect 55 to result in between 20% and 25% not owning a credit card. (d) Would it be unusual for a random sample of 200 adults to result in 40 or fewer who do not own (Round to four decimal places as needed.) credit card? Why? Select the correct choice below and fill in the answer box to complete your choice. O A. The result is not unusual because the probability that p is less than or equal to the sample proportion is which is less than 5%. O B. The result is unusual because the probability that p is less than or equal to the sample proportion is which is greater than 5%. O C. The result is unusual because the probability that p is less than or equal to the sample proportion is which is less than 5%. O D. The result is not unusual because the probability that p is less than or equal to the sample proportion is which is greater than 5%.
Inverse Normal Distribution
The method used for finding the corresponding z-critical value in a normal distribution using the known probability is said to be an inverse normal distribution. The inverse normal distribution is a continuous probability distribution with a family of two parameters.
Mean, Median, Mode
It is a descriptive summary of a data set. It can be defined by using some of the measures. The central tendencies do not provide information regarding individual data from the dataset. However, they give a summary of the data set. The central tendency or measure of central tendency is a central or typical value for a probability distribution.
Z-Scores
A z-score is a unit of measurement used in statistics to describe the position of a raw score in terms of its distance from the mean, measured with reference to standard deviation from the mean. Z-scores are useful in statistics because they allow comparison between two scores that belong to different normal distributions.
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