Understanding 95% Confidence Interval & Total Width <2.0

In summary, the problem is to find the least possible number of tests needed to achieve a 95% confidence interval for the mean of a memory test with a total width of less than 2.0. The total width refers to the difference between the upper and lower bound of the confidence interval, and in this case, it should be less than 2.0. To achieve this, we need to find the value of n, which is the number of tests, that satisfies the equation P(mew-1< X< mew+1)= 0.95. Plugging in the values, we get n^.5/1.9=z, where z is the z-score that gives a probability of 0.475
  • #1
inv
46
0
[Solved]Is a stats question,just need some clarity on it-"total width of less than 2.

Homework Statement


Hi.The result of a memory test is known to be normally distributed with mean mew and standard deviation 1.0. It's required to have a 95% confidence interval for mew with a total width of less than 2.0.Find the least possible number of tests needed to achieve this.*The "total width of less than 2.0" mean what?


Homework Equations


?


The Attempt at a Solution


P(Z<2.0)=0.95
(X-mew)/(1.9/n^.5)<2.0,where X=the mean
mew<2.0
I'm stuck here,I'm sure something is wrong with it.So pls explain the thing with the * above?
 
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  • #2
inv said:

Homework Statement


Hi.The result of a memory test is known to be normally distributed with mean mew and standard deviation 1.0. It's required to have a 95% confidence interval for mew with a total width of less than 2.0.Find the least possible number of tests needed to achieve this.*The "total width of less than 2.0" mean what?
Any confidence interval for the true mean is of the form [a,b]. The "total width" is b-a. In particular, if you take the interval to be symmetric about mew (since the normal distribution is symmetric about its mean) then you want [mew- a,mew+ a] with "total width"= 2a< 2 or a< 1.

Homework Equations


?


The Attempt at a Solution


P(Z<2.0)=0.95
(X-mew)/(1.9/n^.5)<2.0,where X=the mean
mew<2.0
I'm stuck here,I'm sure something is wrong with it.So pls explain the thing with the * above?
No, You want P(mew-1< X< mew+1)= 0.95. (X-mew)/(1.9/n^.5) with X= mew+ 1 gives z= 1/(1.9/n^.5)= n^.5/1.9. Look up the z score that gives .95/2 = .475 (for a table that uses only positive values) and then solve for n.
 
  • #3
Thx.Problem solved~The End~
 

1. What is a 95% confidence interval?

A 95% confidence interval is a range of values that is likely to contain the true value of a population parameter with a 95% probability. It is calculated using a sample of data and is used to estimate the true value of a population parameter, such as a mean or proportion.

2. How is a 95% confidence interval calculated?

A 95% confidence interval is calculated using the sample mean and standard deviation, along with the sample size and the appropriate z or t-value. The formula for a 95% confidence interval is: sample mean ± (z or t-value * standard deviation / √sample size).

3. What does a total width <2.0 mean in a 95% confidence interval?

A total width <2.0 means that the upper and lower limits of the confidence interval are within 2.0 units of each other. This indicates a relatively narrow range and a higher level of precision in the estimate of the population parameter. A wider interval may indicate more variability in the data and a lower level of precision.

4. Why is a 95% confidence interval commonly used?

A 95% confidence interval is commonly used because it provides a balance between having a high level of confidence in the estimate and a narrow enough interval to be useful. It is also a standard convention in statistical analysis and is considered to be a good compromise between precision and practicality.

5. Can a confidence interval be interpreted as a probability?

No, a confidence interval should not be interpreted as a probability. It is a statement about the likelihood that the true population parameter falls within the given range, not a probability that a particular value is the true parameter. Additionally, a confidence interval is based on a sample and does not consider all possible values of the parameter, so it cannot be assigned a probability.

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