-aux.13.Normal Distribution area

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Discussion Overview

The discussion revolves around the properties of a normal distribution related to a random variable $$X$$, specifically focusing on calculating probabilities and parameters such as the mean $$\mu$$ and standard deviation $$\sigma$$. The participants explore the implications of given probabilities and the relationships between them, as well as methods for determining these parameters.

Discussion Character

  • Mathematical reasoning
  • Technical explanation
  • Homework-related
  • Debate/contested

Main Points Raised

  • Some participants note that the area of the shaded region $$A$$, where $$x \geq 12$$, is given as $$0.1$$ based on the probability $$P(X \geq 12) = 0.1$$.
  • There is a discussion about finding the mean $$\mu$$, with some suggesting it lies between $$8$$ and $$12$$, proposing $$\mu = 10$$ based on symmetry arguments.
  • Participants discuss how to derive the standard deviation $$\sigma$$, with one suggesting that $$\sigma$$ can be calculated using the z-score corresponding to the area of $$0.1$$.
  • There are varying methods proposed for calculating $$P(X \leq 11)$$, with some participants indicating the need to standardize the variable and use z-scores to find the probability.
  • One participant mentions the need to consider the area to the left of the mean when calculating probabilities, suggesting a potential adjustment to the final probability for $$P(X \leq 11)$$.

Areas of Agreement / Disagreement

Participants generally agree on the relationships between the probabilities and the parameters of the normal distribution, but there are differing methods and interpretations regarding the calculations, particularly for $$P(X \leq 11)$$. The discussion remains unresolved with multiple approaches being considered.

Contextual Notes

Some participants express uncertainty about the exact z-values to use and the implications of symmetry in the normal distribution. There are also mentions of needing to reference standard normal distribution tables, which may introduce variability in results based on the tables used.

Who May Find This Useful

This discussion may be useful for students or individuals studying statistics, particularly those interested in understanding normal distributions and probability calculations related to them.

karush
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View attachment 1020

still having trouble figuring this out!

The graph shows a normal curve for the random variable $$X$$, with mean $$ \mu$$ and standard deviation $$\sigma$$

It is known that $$P \left(X \geq12 \right) = 0.1$$.

(a) The shaded region $$A$$ is the region under the curve where $$x \geq 12$$. Write down the area of the shaded region $$A$$.

It is also known that $$P(X \leq 8) = 0.1$$.

(b) Find the value of $$\mu$$, explaining your method in full.

in that $$\mu$$ is in between 8 and 12 which would be $$\mu=10$$(c) Show that $$\sigma = 1.56$$ to an accuracy of three significant figures.

(d) Find $$ P(X \leq 11)$$.
 
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karush said:
View attachment 1020

still having trouble figuring this out!

The graph shows a normal curve for the random variable $$X$$, with mean $$ \mu$$ and standard deviation $$\sigma$$

It is known that $$P \left(X \geq12 \right) = 0.1$$.

(a) The shaded region $$A$$ is the region under the curve where $$x \geq 12$$. Write down the area of the shaded region $$A$$.
Seriously? You were just told that this area is 0.1!

It is also known that $$P(X \leq 8) = 0.1$$.

(b) Find the value of $$\mu$$, explaining your method in full.

in that $$\mu$$ is in between 8 and 12 which would be $$\mu=10$$.
Okay, Since the graph of the normal distribution is symmetric about mu, and you are told that the probabilities that x is less than 8 and larger than 12 are equal, mu is exactly half way between them

(c) Show that $$\sigma = 1.56$$ to an accuracy of three significant figures.
If a normal distribution has mean 10 and standard deviation [math]\sigma[/math], then [math]\frac{x- \mu}{\sigma}[/math] has standard normal distribution. Look up the "z" that has probability .1 in a table of the standard distribution (a good one online is at Standard Normal Distribution Table) then solve [math]\frac{12- 0}{\sigma}= z[/math]

(d) Find $$ P(X \leq 11)$$.
Knowing both [math]\sigma[/math] and [math]\mu= 10[/math] you can find the "standard" variable [math]z= \frac{11- 10}{\sigma}[/math] using the table of the normal distribution.
 
karush said:
View attachment 1020

still having trouble figuring this out!

The graph shows a normal curve for the random variable $$X$$, with mean $$ \mu$$ and standard deviation $$\sigma$$

It is known that $$P \left(X \geq12 \right) = 0.1$$.

(a) The shaded region $$A$$ is the region under the curve where $$x \geq 12$$. Write down the area of the shaded region $$A$$.

It is also known that $$P(X \leq 8) = 0.1$$.

(b) Find the value of $$\mu$$, explaining your method in full.

in that $$\mu$$ is in between 8 and 12 which would be $$\mu=10$$(c) Show that $$\sigma = 1.56$$ to an accuracy of three significant figures.

(d) Find $$ P(X \leq 11)$$.

(a) You are given that:

$$P \left(X \geq12 \right) = 0.1$$

What relationship is there between this and the shaded region?

(b) Using the given:

$$P(X \leq 8) = 0.1$$

We may state:

$$8<\mu<12$$

and by symmetry:

$$\mu-8=12-\mu$$

Note: we are simply stating mathematically that the mean is midway between $X=8$ and $X=12$.

(c) We know that:

$$z=\frac{\mu-x}{\sigma}$$

or:

$$\sigma=\frac{\mu-x}{z}$$

Once we know $\mu$, and we use $x=12$, what $z$-value should we use? What area is to the left of $x$ but to the right of $\mu$?

(d) Once we have $\sigma$, we may standardize $X=11$ (convert it to a $z$-score) and then use our table to determine $$ P(X \leq 11)$$.

So, what do you find? :D

I see, before I post, that another has posted, but I figure we are saying the same thing in slightly different ways, and I am not giving anything further away. :D
 
MarkFL said:
(a) You are given that:

Once we know $\mu$, and we use $x=12$, what $z$-value should we use? What area is to the left of $x$ but to the right of $\mu$?

well from the table I found $0.5-0.1=0.4$ so $0.4$ on table is $\approx 0.3997$ or a $z$ value of $1.28$

so $\frac{|10-12|}{1.28}=1.56 = \sigma$
I assume the numerator has to be a abs value

MarkFL said:
(d) Once we have $\sigma$, we may standardize $X=11$ (convert it to a $z$-score) and then use our table to determine $P(X \leq 11)$.

So, what do you find? :D

so $\frac{10-11}{1.56} = z =.64$ from table is $.2389 = P(X \leq 11)$

however don't we include what is left of $\mu$ which would add $.5$ which would give us $\approx .7389$

View attachment 1025
 
Correct, and correct. :D
 

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