Suppose the number of orange M&Ms in a bag are normally distributed with a mean μ= 13 and a standard deviation of σ= 1.67. Show all work. 1. What if we want to receive the top 20% of all orange M&M’s, how many orange M&M’s will we get? 2. The Mars Company does want to make sure there is some quality control, because they would hate tohave a bag have no orange M&Ms but they also don’t want the whole bag to contain orange M&Ms. Sothey are looking for a statement that they can make to the public that goes as follows: ”We guaranteethat the majority of plain M&M bags contain between (lower estimate) and (upper estimate) orangeM&Ms.” Our job is to fill in the lower estimate number and the upper estimate number. The percentagethat Mars decided to reject was any bag below 5% orange and any bag above 5% orange. Use this datato fill in the lower and upper estimates and complete there statement.
Suppose the number of orange M&Ms in a bag are normally distributed with a mean μ= 13 and a standard deviation of σ= 1.67. Show all work. 1. What if we want to receive the top 20% of all orange M&M’s, how many orange M&M’s will we get? 2. The Mars Company does want to make sure there is some quality control, because they would hate tohave a bag have no orange M&Ms but they also don’t want the whole bag to contain orange M&Ms. Sothey are looking for a statement that they can make to the public that goes as follows: ”We guaranteethat the majority of plain M&M bags contain between (lower estimate) and (upper estimate) orangeM&Ms.” Our job is to fill in the lower estimate number and the upper estimate number. The percentagethat Mars decided to reject was any bag below 5% orange and any bag above 5% orange. Use this datato fill in the lower and upper estimates and complete there statement.
Suppose the number of orange M&Ms in a bag are normally distributed with a mean μ= 13 and a standard deviation of σ= 1.67. Show all work. 1. What if we want to receive the top 20% of all orange M&M’s, how many orange M&M’s will we get? 2. The Mars Company does want to make sure there is some quality control, because they would hate tohave a bag have no orange M&Ms but they also don’t want the whole bag to contain orange M&Ms. Sothey are looking for a statement that they can make to the public that goes as follows: ”We guaranteethat the majority of plain M&M bags contain between (lower estimate) and (upper estimate) orangeM&Ms.” Our job is to fill in the lower estimate number and the upper estimate number. The percentagethat Mars decided to reject was any bag below 5% orange and any bag above 5% orange. Use this datato fill in the lower and upper estimates and complete there statement.
Suppose the number of orange M&Ms in a bag are normally distributed with a mean μ= 13 and a standard deviation of σ= 1.67. Show all work.
1. What if we want to receive the top 20% of all orange M&M’s, how many orange M&M’s will we get?
2. The Mars Company does want to make sure there is some quality control, because they would hate tohave a bag have no orange M&Ms but they also don’t want the whole bag to contain orange M&Ms. Sothey are looking for a statement that they can make to the public that goes as follows: ”We guaranteethat the majority of plain M&M bags contain between (lower estimate) and (upper estimate) orangeM&Ms.” Our job is to fill in the lower estimate number and the upper estimate number. The percentagethat Mars decided to reject was any bag below 5% orange and any bag above 5% orange. Use this datato fill in the lower and upper estimates and complete there statement.
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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