Ance is known ,18-24, Ance is unknown ,18-24 – HP 50g Graphing Calculator User Manual
Page 591
Page 18-24
Θ The parameter α is known as the significance level. Typical values of α are
0.01, 0.05, 0.1, corresponding to confidence levels of 0.99, 0.95, and
0.90, respectively.
Confidence intervals for the population mean when the
population variance is known
Let
⎯X be the mean of a random sample of size n, drawn from an infinite
population with known standard deviation
σ. The 100(1-α) % [i.e., 99%, 95%,
90%, etc.], central, two-sided confidence interval for the population mean
μ is
(
⎯X−z
α/2
⋅σ/√n , ⎯X+z
α/2
⋅σ/√n ), where z
α/2
is a standard normal variate that
is exceeded with a probability of
α /2. The standard error of the sample
mean,
⎯X, is ⋅σ/√n.
The one-sided upper and lower 100(1-
α) % confidence limits for the population
mean
μ are, respectively, X+z
α
⋅σ/√n , and ⎯X−z
α
⋅σ/√n . Thus, a lower, one-
sided, confidence interval is defined as (-
∞ , X+z
α
⋅σ/√n), and an upper, one-
sided, confidence interval as (X
−z
α
⋅σ/√n,+∞). Notice that in these last two
intervals we use the value z
α
, rather than z
α/2
.
In general, the value z
k
in the standard normal distribution is defined as that
value of z whose probability of exceedence is k, i.e., Pr[Z>z
k
] = k, or Pr[Z k ] = 1 – k. The normal distribution was described in Chapter 17. Confidence intervals for the population mean when the Let ⎯X and S, respectively, be the mean and standard deviation of a random sample of size n, drawn from an infinite population that follows the normal σ. The 100⋅(1−α) % [i.e., 99%, 95%, 90%, etc.] central two-sided confidence interval for the population mean μ, is (⎯X− t n-1, α/2 ⋅S /√n , ⎯X+ t n-1, α/2 ⋅S/√n ), where t n-1, α/2 is Student's t variate with ν = n-1 degrees of freedom and probability α/2 of exceedence. The one-sided upper and lower 100 ⋅ (1-α) % confidence limits for the population mean μ are, respectively, X + t n-1, α/2 ⋅S/√n , and ⎯X− t n-1, α/2 ⋅S /√n.
population variance is unknown
distribution with unknown standard deviation