A personality test has a subsection designed to assess the "honesty" of the test-tak subsection among the general population. You decide that you'll use the mean of a What is the minimum sample size needed in order for you to be \( 95 \% \) confident tha population standard deviation of scores on this subsection. Carry your intermediate computations to at least three decimal places. Write your minimum whole number that satisfies the requirements). (If necessary, consult a list of formulas.)

Which of the following statements are TRUE about the Normal Distribution? Check all that apply. The graph of the Normal Distribution is bell-shaped, with tapering tails that never actually touch the horizontal axis. \( 50 \% \) of the data values lie at or above the mean. about \( 95 \% \) of all data values lie within 1 standard deviation of the mean. The mean, median and mode are all equal and occur at the center of the distribution. Data values are spread evenly around the mean. Data values farther from the mean are less common than data values closer to the mean.

The weights for newborn babies is approximately normally distributed with a mean of 6 pounds and standard deviation of 1.5 pounds. Consider a group of 1100 newborn babies: 1. How many would you expect to weigh between 3 and 8 pounds? 2. How many would you expect to weigh less than 7 pounds? 3. How many would you expect to weigh more than 6 pounds? 4. How many would you expect to weigh between 6 and 9 pounds?

A variable is normally distributed with mean 18 and standard deviation 9 . Use your graphing calculator to find each of the following areas. Write your answers in decimal form. Round to the nearest thousandth as needed. a) Find the area to the left of 17.

A set of exam scores is normally distributed with a mean \( =74 \) and standard deviation \( =8 \). \( 95 \% \) of the data values lie between 58 \( \% \) of the exam scores are between 66 and 74 . \( \% \) of the exam scores are between 74 and 90 . \% of the exam scores are greater than or equal to 66 .

In a normal distribution, a data value located 1.4 standard deviations below the mean has Standard Score: \( \mathrm{z}=-1.4 \) In a normal distribution, a data value located 2.3 standard deviations above the mean has Standard Score: \( \mathrm{z}=2.3 \) In a normal distribution, the mean has Standard Score: \( \mathrm{z}=\square \)