Normal Distribution Porbability

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SUMMARY

The discussion focuses on calculating the probability of a normalized variable in a normal distribution, specifically ##\bar{X} \sim N(\mu, 9/25)##. The user seeks to find ##P(\bar{X} > \mu + 1.05)## and learns to normalize the distribution using the formula ##Z = \frac{\bar{X} - \mu}{0.6}##, leading to the equivalent probability ##P(Z > 1.75)##. The key takeaway is that the events ##\{\bar{X} > \mu + 1.05\}## and ##\{Z > 1.75\}## represent the same probability, clarifying the normalization process.

PREREQUISITES
  • Understanding of normal distribution and its properties
  • Familiarity with the concepts of mean (##\mu##), variance (##Var[X]##), and standard deviation (##SD[X]##)
  • Knowledge of Z-scores and their application in probability calculations
  • Ability to manipulate and interpret mathematical expressions involving probabilities
NEXT STEPS
  • Study the derivation and application of Z-scores in normal distribution
  • Learn about confidence intervals and their relation to normal distributions
  • Explore the Central Limit Theorem and its implications for sample means
  • Investigate statistical software tools for calculating probabilities in normal distributions
USEFUL FOR

Statisticians, data analysts, students studying probability theory, and anyone involved in statistical modeling or analysis of normal distributions.

Calu
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I have ##\bar{X}## ~ ##N(\mu , 9/25)##

I have ##E[X] = \mu##
##Var[X] = 9/25##
##SD[X] = 3/5 = 0.6##

An interval for ##\bar{X}## has been recorded: ##\bar{X} \pm 1.05##.

I asked to find ##P(\bar{X} > \mu + 1.05)##

I can "normalize" the distribution through:

##Z = \frac{\bar{X} - \mu}{0.6}## ~ ##N(0,1)##

I'm confused by this next step:

##P(\bar{X} > \mu + 1.05) = P(Z > \frac{1.05}{0.6} = 1.75)##

I'm not sure how you go from the first probability to the other. Could any help please?
 
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Calu said:
I have ##\bar{X}## ~ ##N(\mu , 9/25)##

I have ##E[X] = \mu##
##Var[X] = 9/25##
##SD[X] = 3/5 = 0.6##

An interval for ##\bar{X}## has been recorded: ##\bar{X} \pm 1.05##.

I asked to find ##P(\bar{X} > \mu + 1.05)##

I can "normalize" the distribution through:

##Z = \frac{\bar{X} - \mu}{0.6}## ~ ##N(0,1)##

I'm confused by this next step:

##P(\bar{X} > \mu + 1.05) = P(Z > \frac{1.05}{0.6} = 1.75)##

I'm not sure how you go from the first probability to the other. Could any help please?

The events ##\{\bar{X} > \mu + 1.05\}## and ##\{Z > 1.05/0.6\}## are the same:
\{ \bar{X} &gt; \mu + 1.05\} = \{\bar{X} - \mu &gt; 1.05 \}<br /> = \{ (\bar{X} - \mu)/0.6 &gt; 1.05/0.6 \}
 
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Ray Vickson said:
The events ##\{\bar{X} > \mu + 1.05\}## and ##\{Z > 1.05/0.6\}## are the same:
\{ \bar{X} &gt; \mu + 1.05\} = \{\bar{X} - \mu &gt; 0.15\}<br /> = \{ (\bar{X} - \mu)/0.6 &gt; 1.05/0.6 \}

Oh I see, I was being a bit silly there, thanks!
 

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