For a two-tailed interval, they are -1.645 to 1.645
The answer will depend on whether the interval in one or two sided. One-sided: Z < 1.28 or Z > -1.28 Two-sided: -1.64 < Z < 1.64
You don't. There are times when you use 99% or 99.5%, and others where you will settle for 90%. The percentage chosen will depend on the implications of making the wrong decision.
90 is 100 percent. 90/100 = 0.9 is 1 percent. This value times 25 gives you 25 percent. Solution: 22.5
It may stand for the number 150 (Roman numbers). In statistics, CL usually refers to "Confidence Level," which establishes a likelihood (typically 90 or 95%) an estimated value will fall within a given Confidence Interval (a range of estimated values). For example... [I'll get more done on this later]
With silver over $30.00 per ounce the intrinsic value is about $11.00.
decrease
For a 90 percent confidence interval, the alpha (α) level is 0.10, which represents the total probability of making a Type I error. This means that there is a 10% chance that the true population parameter lies outside the interval. The confidence level of 90% indicates that if the same sampling procedure were repeated multiple times, approximately 90% of the constructed intervals would contain the true parameter.
The answer will depend on whether the interval in one or two sided. One-sided: Z < 1.28 or Z > -1.28 Two-sided: -1.64 < Z < 1.64
The answer depends on whether the test is one-tailed or two-tailed.One-tailed: z = 1.28 Two-tailed: z = 1.64
1.0966
The user selects the confidence level. It could also be 90 or 99 or 99.9 or another value.
To shorten a confidence interval, you can either increase the sample size or reduce the confidence level. Increasing the sample size decreases the standard error, leading to a narrower interval. Alternatively, lowering the confidence level (e.g., from 95% to 90%) reduces the range of the interval but increases the risk of capturing the true population parameter.
You don't. There are times when you use 99% or 99.5%, and others where you will settle for 90%. The percentage chosen will depend on the implications of making the wrong decision.
The confidence level for a confidence interval cannot be determined solely from the interval itself (46.8 to 47.2) without additional context, such as the sample size or the standard deviation of the data. Typically, confidence levels (e.g., 90%, 95%, or 99%) are established based on the statistical method used to calculate the interval. To find the exact confidence level, more information about the underlying statistical analysis is needed.
To reduce the width of a confidence interval, one can increase the sample size, as larger samples tend to provide more precise estimates of the population parameter. Additionally, using a lower confidence level (e.g., 90% instead of 95%) decreases the interval's width. Finally, reducing the variability in the data, such as by controlling for extraneous factors or using a more homogenous sample, can also lead to a narrower confidence interval.
The confidence interval will be Pi+-z*spz5%= 1.6449Pi = x/nSp = Sqrt(Pi(1-Pi)/n)Pi ~= 0.5694Sp = Sqrt(.5694*0.4306/144) ~= 0.0413Pi - 0.0679 < p < Pi + 0.06790.5016 < p < 0.6373You can do this on your TI-83/84 with 1-PropZInt (Stat->Tests->A)
To find 90 percent of a value, multiply the value by 0.9. In this instance, 0.9 x 2 = 1.8 kilometres.