Solving Normal Distribution Homework: μ, σ, X, p

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  • #1
TyErd
299
0

Homework Statement


I've attached the question.


Homework Equations


μ=np and σ=√(np(1-p))
Im using the normal distribution function on my calculator to avoid using z tables


The Attempt at a Solution


The mean I calculated it to be 160/4 = 40. standard deviation sqrt(160*1/4*3/4)=5.47723
The question is asking for at least 40(greater or equal to 40) that will choose biscuits but because this is a normal distribution it will be the same as greater than 40 so if I use an X value of 40 the probabilities should just equal 0.5000 right? however the answer is 0.5364
 

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  • #2
TyErd said:

Homework Statement


I've attached the question.

Homework Equations


μ=np and σ=√(np(1-p))
Im using the normal distribution function on my calculator to avoid using z tables

The Attempt at a Solution


The mean I calculated it to be 160/4 = 40. standard deviation sqrt(160*1/4*3/4)=5.47723
The question is asking for at least 40(greater or equal to 40) that will choose biscuits but because this is a normal distribution it will be the same as greater than 40 so if I use an X value of 40 the probabilities should just equal 0.5000 right? however the answer is 0.5364

You have not used the so-called "continuity correction" or "1/2 correction". If we approximate the binomial B(n,p) by the normal distribution when n is "large" but not really huge, it is better to apply the normal to points half-way between. In this case, it means the following. For the exact Binomial (on 0,1,2,...,160), the event {X ≥ 40} is the same event as {X ≥ 39.5}, because X can take only integer values. If you approximate P{X ≥ 40} by P{Normal ≥ 39.5} you will get a much more accurate answer. Here are the three results:
(1) Exact binomial P{X ≥ 40} = 0.53031930 ≈ 0.53
(2) Normal P{X ≥ 40} = 0.50
(3) Normal P{X ≥ 39.5} = 0.53636776 ≈ 0.54

RGV
 
Last edited:

What is a normal distribution?

A normal distribution is a type of probability distribution that is commonly used to model many natural phenomena, such as height, weight, and IQ. It is characterized by a bell-shaped curve and is symmetrical around the mean, with most values falling close to the mean and fewer values falling further away.

What do μ and σ represent in a normal distribution?

In a normal distribution, μ (pronounced "mu") represents the mean or average of the distribution, while σ (pronounced "sigma") represents the standard deviation, which measures the spread of the data around the mean. Together, these two parameters define the shape, center, and spread of the normal distribution.

What is X in a normal distribution?

X represents a random variable, which is a quantity that can take on different values in a given situation. In the context of a normal distribution, X can refer to a single value or a range of values that are being measured or predicted.

How do I calculate the probability of a specific value or range in a normal distribution?

The probability of a specific value or range in a normal distribution can be calculated using the standard normal distribution table or by using a statistical software or calculator. The formula for calculating the probability is P(X = x) = (1 / σ√(2π)) * e^-(x-μ)^2/2σ^2, where x is the specific value or the midpoint of the range.

How is the normal distribution used in statistics and scientific research?

The normal distribution is widely used in statistics and scientific research to model and analyze data. It allows researchers to make predictions and draw conclusions about a population based on a sample, as well as to determine the likelihood of certain events or values occurring. It is also used in hypothesis testing, quality control, and in many other applications in various fields such as psychology, economics, and engineering.

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