Normal Distribution Problem

In summary: Can you please help me understand what z-score has to do with juice box fill?In summary, the author is asking if the variability of the machine that fills the juice boxes is reduced to 0.025 oz, can the lower required average/mean amount of juice to 4.05 oz be confirmed.
  • #1
RedPhoenix
26
0
Been having an issue with these specific homework problems. Can you give me some insight on where to start.

#4.78 F

The actual amount of juice that a machine fills the juice boxes with is 4-ounces, which may be a random variable with normal distribution of [tex]\sigma[/tex] = 0.04 ounce

a) If only 2% of the boxes contained less than 4 ounces what is the mean/average fill on the juice boxes

b) If the variability of the machine that fills the boxes are reduced to 0.025 oz, confirm that the lower required average/mean amount of juice to 4.05 oz and keeping the 98% of jars above 4 oz
I have no idea where to start... Please help thanks
 
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  • #2
I am new to statistics, so ignore this if it doesn't make sense. What they say doesn't really make sense to me anyway. But do you have a standard normal table (or application)? It sounds like they are giving you enough to solve a standard z-score equation -- 2% of the population should fall below the z-score of x = 4 oz. with [itex]\sigma[/itex] = .04:

[tex]\frac{4 - \mu}{.04} = z[/tex]

Look up what z-score has 2% of the area to its left.
 
  • #3
I don't have a table handy, but how can I find [tex]\mu[/tex]?

I know its E(x).. or atleast I think so. I also know that the problem is written poorly and the book is not much better.
 
  • #4
You can find tables and calculators online by googling, e.g., "standard normal table". Do you know what I am talking about, though?

You can find [itex]\mu[/itex] by finding the z that you need and plugging it into the above equation. Imagine the standard normal distribution. Do you know what this (bell) curve looks like? Put it in the Cartesian coordinate system so that the curve sits on the x-axis and the mean lies on the y-axis. You need to travel along the x-axis to the point where you can draw a line parallel to the y-axis and it will divide the curve into two figures such that the area of the figure on the left is 2% of the area of the original distribution curve. You express the distance that you have to travel in terms of standard deviations. Does this make sense?

To find exactly how far you have to travel, you can go http://davidmlane.com/hyperstat/z_table.html" , scrolll down to the second graph, type ".02" into the "Shaded Area:" box, and click the "Below" radio button. This will shade the graph and give you the number of (standardized) standard deviations from the mean that you have to travel, i.e., your value for z.

I am pretty sure this is the right approach because the answer that I got makes sense with part (b) of your question.
 
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1. What is a normal distribution problem?

A normal distribution problem refers to a type of statistical problem where the data follows a normal, bell-shaped curve. This means that the majority of the data is centered around the mean, with a smaller percentage of data falling on either side of the mean. Normal distribution problems are commonly used in statistics to analyze and interpret data.

2. How is a normal distribution calculated?

A normal distribution is calculated by using the mean and standard deviation of a dataset. The mean, or average, represents the center of the distribution, while the standard deviation measures the spread of the data from the mean. These values are used to create the bell-shaped curve that represents the normal distribution.

3. What are the characteristics of a normal distribution?

A normal distribution is characterized by its symmetrical, bell-shaped curve. It is also known as a Gaussian distribution. The mean, median, and mode of a normal distribution are all equal, and the total area under the curve is equal to 1. Additionally, approximately 68% of the data falls within one standard deviation of the mean, 95% within two standard deviations, and 99.7% within three standard deviations.

4. What is the purpose of using a normal distribution in statistics?

The purpose of using a normal distribution in statistics is to analyze and interpret data. Many real-world phenomena can be approximated by a normal distribution, making it a useful tool for understanding and predicting outcomes. Normal distributions are also used in statistical tests and models to make assumptions about the data and make accurate predictions.

5. How is a normal distribution problem solved?

A normal distribution problem can be solved by using various statistical methods, such as the z-score, to calculate probabilities and make predictions. These methods involve using the mean and standard deviation to determine the likelihood of a certain outcome or to compare different datasets. Additionally, statistical software and calculators can be used to quickly and accurately solve normal distribution problems.

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