Normal Distribution and High Jumping Heights: Probability and Standard Deviation

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In summary, the high jumper in this problem has a 20% chance of clearing a height of at least 1.78m and a 70% chance of clearing a height of at least 1.65m. By using the standard normal distribution table, the mean and standard deviation of the heights can be found to be 1.71m and 0.065m respectively. The probability that the high jumper can jump at least 1.74m can then be calculated as 0.8209.
  • #1
thomas49th
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Homework Statement


From expirence a higher jumper knows he can claer a height of at least 1.78m once in 5 attempts. He also knows that he can clear a height of at least 1.65m on 7 out of 10 attempts

Assuming that the heights the high jumper can reach follow a Normal Distribution,

a) Draw a sketch to illustrate the information above

b) find, to 3 decimal places, the mean and the standard deviation of the heights the higher-jumper can reach

c) Calculate the probability that he can jump atleast 1.74m



Homework Equations



You'll need the distribution table

The Attempt at a Solution


Part a)

Well I can form the equations

P(h >= 1.78) =0.2
P(h >= 1.65) = 0.7

so what we're saying is the probability the height will be atleast 1.78m is 0.2
and
so what we're saying is the probability the height will be atleast 1.65m is 0.7

okay

so how do i go about drawing these on a normal distrubution. I think I have to do the flip around thing but I am not sure why?

Thanks :)
 
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  • #2
First thing you need to do is find the z values from a table of the standard normal distribution corresponding to P(z)= 0.2 and P(z)= 0.7. I'll call those z0.2 and z0.7.
Here's a good table: http://www.itl.nist.gov/div898/handbook/eda/section3/eda3671.htm

The formula for changing from a normal distribution with mean [itex]\mu[/itex] and standard deviation [itex]\sigma[/itex] is [itex]z= (x-\mu)/\sqrt{\sigma}[/itex]. Solve [itex]z_{0.2}= (1.64- \mu)/\sqrt{\sigma}[/itex] and [itex]z_{0.7}= (1.78- \mu)/\sqrt{z}[/itex] for [itex]\mu[/itex] and [itex]\sigma[/itex].

Use that information to draw the appropriate "bell shaped curve" with correct mean and standard deviation and to find [itex]P(h\ge 1.74)[/itex].
 
  • #3
Ahh yes, I know about the standardising using the formula, ill need that for part B

so P(z) = 0.2

z = 0.07926

P(z) = 0.7
z = 1 - phi(0.7)
= 1 - 0.11791
= 0.8209

Is that right?

Thanks :)
 

1. What is a normal distribution?

A normal distribution is a type of probability distribution that is symmetric and bell-shaped. It is often used to describe natural phenomena such as height, weight, or IQ scores.

2. What are the characteristics of a normal distribution?

A normal distribution is characterized by its mean, median, and mode all being equal, as well as its symmetrical shape with the majority of data falling within one standard deviation of the mean.

3. How is a normal distribution calculated?

A normal distribution can be calculated using a mathematical formula known as the Gaussian function, which involves the mean, standard deviation, and the value of x at a given point.

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

The purpose of using a normal distribution is to model and understand real-world data that tends to cluster around a central value with fewer extreme values occurring on either side.

5. How is a normal distribution used in scientific research?

A normal distribution is commonly used in scientific research to analyze and interpret data, make predictions, and test hypotheses. It is also used in statistical tests such as t-tests and ANOVA to determine the significance of differences between groups.

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