How Do You Calculate a 95% Confidence Interval for Potato Weights?

In summary: It is a measure of the variability of the sample mean and is equal to the square root of the sample size (n).
  • #1
Gregg
459
0

Homework Statement




3 (a) A sample of 50 washed baking potatoes was selected at random from a large batch.
The weights of the 50 potatoes were found to have a mean of 234 grams and a standard
deviation of 25.1 grams.
Construct a 95% confidence interval for the mean weight of potatoes in the batch.
(4 marks)


Homework Equations



[itex] \bar{x} = \mu[/itex]

[itex] s = \frac{\sigma}{\sqrt{n}}[/itex]


[itex] z = \frac{x-\mu}{s}[/itex]

The Attempt at a Solution



The confidence interval 95% means p = 0.975

[itex] z = \frac{x-\mu}{s}[/itex]


[itex] \pm 1.96 = \frac{x-234}{\frac{25.1}{\sqrt{50}}}[/itex]


[itex]\Rightarrow 227-241[/itex]

Why is the standard deviation

[itex]s = \frac{25.1}{\sqrt{50}}[/itex]

and not just 25.1. The question states that the s.d. is 25.1!
 
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  • #2
[itex]\frac{\bar{x} - \mu}{\frac{s}{\sqrt{n}}} [/itex] is approximately N(0,1) for large n (assuming that the original distribtuion is not skewed)
 
  • #3
Why is the standard deviation

[itex]s = \frac{25.1}{\sqrt{50}}[/itex]

and not just 25.1. The question states that the s.d. is 25.1!

There are two things going on here. On the one hand there are the population standard deviation ([itex]\sigma[/itex] and sample standard deviation s. On the other is the standard deviation of the mean, which is defined as:
[tex]\sigma_{mean} = \frac{\sigma}{\sqrt{n}}[/tex]

The wikipedia article here--http://en.wikipedia.org/wiki/Standard_deviation--talks about the st. dev. of the mean in the section titled Relationship between standard deviation and mean.
 
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  • #4
Mark44 said:
There are two things going on here. On the one hand there are the population standard deviation ([itex]\sigma[/itex] and sample standard deviation s. On the other is the standard deviation of the mean, which is defined as:
[tex]\sigma_{mean} = \frac{\sigma}{\sqrt{n}}[/tex]

The wikipedia article here--http://en.wikipedia.org/wiki/Standard_deviation--talks about the st. dev. of the mean in the section titled Relationship between standard deviation and mean.
That's what's confusing, the standard deviation of the mean is the same as the standard deviation of the sample divided by root n?
 
Last edited by a moderator:
  • #5
Gregg said:
That's what's confusing, the standard deviation of the mean is the same as the standard deviation of the sample divided by root n?

It's approximately the same.
 
  • #6
s =SIGMA/SQRT(N)

STANDS FOR STANDARD ERROR NOT FOR STANDARD DEVAITION!
 
  • #7
rclakmal said:
s =SIGMA/SQRT(N)

STANDS FOR STANDARD ERROR NOT FOR STANDARD DEVAITION!

The standard deviation of the sample mean is sometimes called the standard error.
 

Related to How Do You Calculate a 95% Confidence Interval for Potato Weights?

1. What is a normal distribution?

A normal distribution is a statistical concept that describes a symmetrical pattern of data where the majority of values cluster around the mean, with fewer values further away from the mean. It is also known as a bell curve due to its shape.

2. What are the characteristics of a normal distribution?

The characteristics of a normal distribution include a symmetrical shape, with the mean, median, and mode all being equal. It also follows the 68-95-99.7 rule, where approximately 68% of the data falls within one standard deviation of the mean, 95% within two standard deviations, and 99.7% within three standard deviations.

3. How is a normal distribution used in statistics?

A normal distribution is used in statistics to model real-world data and make predictions about the likelihood of certain events occurring. It is also used to calculate probabilities and determine the spread of data.

4. What is the significance of the mean and standard deviation in a normal distribution?

The mean is the central value of a normal distribution and represents the average of all the data points. The standard deviation measures the spread of the data around the mean. Together, they provide important information about the shape and characteristics of the distribution.

5. Can a data set have a perfect normal distribution?

In theory, a data set can have a perfect normal distribution. However, in practice, it is rare to find a data set that follows a perfectly symmetrical bell curve. Most data sets will have some degree of deviation from a normal distribution.

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