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POST 1:

According to our reading in chapter 6, z (means) equals 0 and the standard deviation (variance) equals 1.Using the standard normal distribution in appendix B:Table 1, the probability when z ≤ -1.75 is 0.0401 and the probability when z ≤ 1.75 is 0.9599 meaning there is at least a probability that -1.75 is 4% equal to or less than the means and 1.75 is equal to or less than the means by 96%.6.2 describes the properties of probability distribution as areas normal to the curve less than, greater than or equal to the mean of zero.Using a graph with a curve to show the standard deviations, the normal curve is balanced around the mean and the total area below the curve is equal to or less than 1.Our reading show is the three types of probabilities we need to compute include the probability that the standard normal random variable z will be less than or equal to a given value, the probability that z will be between 2 given values and the probability that z will be greater than or equal to a given value.

POST 2:

The probability is a score of 0.0401 when z < -1.75; and the probability is 0.9599 when z < 1.75, under the standard normal curve to the left of Z. On this bell shaped graph, the sum of both of these probabilities from the z table complement each other in that they are equal to 1, therefore 1.75 and -1.75 balance each other. With the Z score table, both have a median (or mean) of 0 and a standard deviation of 1. The chart I used is from http://www.stat.purdue.edu/~mccabe/ips4tab/bmtables.pdf because our book does not provide a Z Score chart.

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