What is the value of the missing area in a standard deviation problem?

In summary, the problem involves finding probabilities for different regions under a normal curve, specifically for the given x-value of -1.5. It is unclear whether the white region should be considered or not, and if so, what assumptions should be made. Additional information or assumptions about the boundaries of the white region may be needed to accurately solve the problem.
  • #1
bap902
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Homework Statement


http://img338.imageshack.us/img338/5064/picture1nk.png

2. The attempt at a solution
I know the area for -1.5 is .0668. I also know that the area of the positive half of the curve is .5000. I don't know how to figure out what the other blue piece is or how much the white space is worth.
 
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  • #2
Since all they give you in the problem is x = -1.5, my guess is that you're supposed to find P(x < -1.5) and P(x > -1.5), and just assume that the white region is essentially not there.

On the other hand, I can see little tickmarks in the drawing, so maybe you're supposed to assume that they are at -1.5 and -1.25. Under this assumption you would be finding P(x < -1.5) and P(x > -1.25). Whichever way you decide to go, be sure to include your assumptions.

Regarding your other question, and assuming we want to find P(x > -1.25), the area under the curve between x = -1.25 and x = 0 is the same as the area between x = 0 and x = +1.25. Can you find that area/probability? Whatever that is, add it to the .50 you already have and your will have P(x > -1.25).
 
  • #3
You are apparently given that the left boundary of the white (unshaded) region is -1.5. If you do not know the x-value for the right boundary, there is no way to answer this.

(I might be inclined to make a guess of x= -1, but that should be given in the problem.)
 

FAQ: What is the value of the missing area in a standard deviation problem?

What is standard deviation?

Standard deviation is a measure of how spread out a set of data is from its mean or average. It tells us how much the data varies from the average.

Why is standard deviation important?

Standard deviation is important because it allows us to understand the variability and distribution of a data set. It can help us make comparisons between different data sets and identify outliers.

How is standard deviation calculated?

The standard deviation is calculated by finding the square root of the variance. The variance is found by taking the average of the squared differences between each data point and the mean.

What does a high standard deviation mean?

A high standard deviation means that the data points are spread out over a wider range from the mean. This indicates that there is a lot of variability in the data set.

What does a low standard deviation mean?

A low standard deviation means that the data points are clustered close to the mean. This suggests that there is not much variability in the data set.

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