In a random sample of 7 cell phones, the mean full retail price was $512.60 and the standard deviation was $186.00. Further research suggests that the population mean is $431.12. Does the t-value for the original sample fall between −t0.99 and t0.99? Assume that the population of full retail prices for cell phones is normally distributed. The t-value of t=? Does or does it not fall between −t0.99 and t0.99 because t0.99 =?

In a random sample of 7 cell phones, the mean full retail price was $512.60 and the standard deviation was $186.00. Further research suggests that the population mean is $431.12. Does the t-value for the original sample fall between −t0.99 and t0.99? Assume that the population of full retail prices for cell phones is normally distributed. The t-value of t=? Does or does it not fall between −t0.99 and t0.99 because t0.99 =?

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Description: In a random sample of 7 cell phones, the mean full retail price was$512.60 and the standard deviation was$186.00. Further research suggests that the population mean is$431.12. Does the t-value for the original sample fall between −t0.99 and t0.9

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Question

In a random sample of 7 cell phones, the mean full retail price was

$512.60 and the standard deviation was

$186.00. Further research suggests that the population mean is

$431.12. Does the t-value for the original sample fall between −t0.99 and t0.99?

Assume that the population of full retail prices for cell phones is normally distributed.

The t-value of

t=? Does or does it not fall between −t0.99 and t0.99 because t0.99 =?

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

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