Confidence Intervals Flashcards
Binomial Distribution
a discrete random variable (RV) which arises from Bernoulli trials; there are a fixed number, n, of independent trials. “Independent” means that the result of any trial (for example, trial 1) does not affect the results of the following trials, and all trials are conducted under the same conditions. Under
Confidence Interval
an interval estimate for an unknown population parameter. This depends on:
- the desired confidence level,
- information that is known about the distribution (for example, known standard deviation),
- the sample and its size.
Confidence Level
the percent expression for the probability that the confidence interval contains the true population parameter; for example, if the CL = 90%, then in 90 out of 100 samples the interval estimate will enclose the true population parameter.
Degrees of Freedom (df)
The number of objects in a sample that are free to vary
Error bound for the Population Mean (EBM)
the margin of error; depends on the confidence level, sample size, and known or estimated population standard deviation.
Inferential Statistics
also called statistical inference or inductive statistics; this facet of statistics deals with estimating a population parameter based on a sample statistic. For example, if four out of the 100 calculators sampled are defective we might infer that four percent of the production is defective.
Normal Distribution
a continuous random variable (RV), where μ is the mean of the distribution and σ is the standard deviation, notation: X ~ N(μ,σ). If μ = 0 and σ = 1, the RV is called the standard normal distribution.
Parameter
A numerical characteristic of the population
Point Estimate
a single number computed from a sample and used to estimate a population parameter
Standard Deviation
a number that is equal to the square root of the variance and measures how far data values are from their mean; notation: s for sample standard deviation and σ for population standard
