James' question about Normal Distribution

In summary, normal distribution, also known as Gaussian distribution, is a statistical concept used to describe the pattern of data on a graph. It is a bell-shaped curve with the majority of data points near the mean. Normal distribution is calculated using a mathematical formula and is commonly used in statistical analyses to understand and analyze large sets of data. Not all data can be described by normal distribution, and it is important to assess the data before assuming it follows a normal distribution. The central limit theorem states that as sample size increases, the distribution of sample means will approach a normal distribution, making it a useful tool in statistical analyses.
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(a) We are told $\displaystyle \begin{align*} \textrm{Pr}\,\left( X < 3 \right) = \textrm{Pr}\,\left( Z < a \right) \end{align*}$, so if $\displaystyle \begin{align*} x = 3 \end{align*}$ and $\displaystyle \begin{align*} z = a \end{align*}$ then we have

$\displaystyle \begin{align*} z &= \frac{x - \mu}{\sigma} \\ a &= \frac{3 - 5}{2} \\ a &= \frac{-2}{\phantom{-}2} \\ a &= -1 \end{align*}$(b) We are told $\displaystyle \begin{align*} \textrm{Pr}\,\left( X > 8 \right) = \textrm{Pr}\,\left( Z > b \right) \end{align*}$, so if $\displaystyle \begin{align*} x = 8 \end{align*}$ then we have

$\displaystyle \begin{align*} z &= \frac{x - \mu}{\sigma} \\ b &= \frac{8 - 5}{2} \\ b &= \frac{3}{2} \\ b &= 1.5 \end{align*}$(c) We are told $\displaystyle \begin{align*} \textrm{Pr}\,\left( X > 6 \right) = \textrm{Pr}\,\left( Z < c \right) \end{align*}$, so by symmetry, $\displaystyle \begin{align*} \textrm{Pr}\,\left( X > 6 \right) = \textrm{Pr}\,\left( Z > -c \right) \end{align*}$, and thus if $\displaystyle \begin{align*} x = 6 \end{align*}$ then

$\displaystyle \begin{align*} z &= \frac{x - \mu}{\sigma} \\ -c &= \frac{6 - 5}{2} \\ -c &= \frac{1}{2} \\ c &= -\frac{1}{2} \end{align*}$
 
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Prove It said:
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(a) We are told $\displaystyle \begin{align*} \textrm{Pr}\,\left( X < 3 \right) = \textrm{Pr}\,\left( Z < a \right) \end{align*}$, so if $\displaystyle \begin{align*} x = 3 \end{align*}$ and $\displaystyle \begin{align*} z = a \end{align*}$ then we have

$\displaystyle \begin{align*} z &= \frac{x - \mu}{\sigma} \\ a &= \frac{3 - 5}{2} \\ a &= \frac{-2}{\phantom{-}2} \\ a &= -1 \end{align*}$(b) We are told $\displaystyle \begin{align*} \textrm{Pr}\,\left( X > 8 \right) = \textrm{Pr}\,\left( Z > b \right) \end{align*}$, so if $\displaystyle \begin{align*} x = 8 \end{align*}$ then we have

$\displaystyle \begin{align*} z &= \frac{x - \mu}{\sigma} \\ b &= \frac{8 - 5}{2} \\ b &= \frac{3}{2} \\ b &= 1.5 \end{align*}$(c) We are told $\displaystyle \begin{align*} \textrm{Pr}\,\left( X > 6 \right) = \textrm{Pr}\,\left( Z < c \right) \end{align*}$, so by symmetry, $\displaystyle \begin{align*} \textrm{Pr}\,\left( X > 6 \right) = \textrm{Pr}\,\left( Z > -c \right) \end{align*}$, and thus if $\displaystyle \begin{align*} x = 6 \end{align*}$ then

$\displaystyle \begin{align*} z &= \frac{x - \mu}{\sigma} \\ -c &= \frac{6 - 5}{2} \\ -c &= \frac{1}{2} \\ c &= -\frac{1}{2} \end{align*}$
Your answers look fine but I wouldn't have done things as you did.
You're given that ##\mu = 5## and ##\sigma = 2##, so ##Z = \frac{X - \mu}\sigma##. Substituting for the given parameters, we have ##Z = \frac{X - 5}2 \Rightarrow X = 2Z + 5##.

For part a, ##Pr(X < 3) = Pr(2Z + 5 < 3) = Pr(2z < -2) = Pr(Z < -1)##, so ##a = -1##, same answer that you gave, but probably cleaner in its derivation. The other two parts are done similarly.
 
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1. What is normal distribution?

Normal distribution, also known as Gaussian distribution, is a statistical concept that describes the pattern of data when plotted on a graph. It is a symmetric bell-shaped curve, with the majority of data points falling near the mean (average) and decreasing as they move away from the mean.

2. How is normal distribution calculated?

Normal distribution is calculated using a mathematical formula known as the probability density function, which takes into account the mean and standard deviation of the data. This formula allows us to determine the likelihood of a data point falling within a certain range of values.

3. What is the purpose of normal distribution?

The purpose of normal distribution is to help us understand and analyze large sets of data. It is commonly used in statistical analyses and modeling to make predictions and draw conclusions about a population.

4. Can all data be described by normal distribution?

No, not all data can be described by normal distribution. While many natural phenomena and human characteristics follow a normal distribution, there are also many types of data that do not. It is important to assess the distribution of your data before assuming it follows a normal distribution.

5. How does normal distribution relate to the central limit theorem?

The central limit theorem states that as the sample size of a population increases, the distribution of sample means will approach a normal distribution, regardless of the shape of the original population. This is why normal distribution is commonly used in statistical analyses, as it allows us to make inferences about a population based on a smaller sample size.

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