STATISTICS 11 - Definitions of Estimating Parameters

FINAL TERM 1ST SEM

Inferential statistics

- uses a sample of data to make predictions, generalizations, and conclusions

- divided into two categories (estimation and tests of hypotheses)

Estimation

process of assigning a value, α values to a population parameter based on the value of a corresponding sample statistic

Testing a hypothesis

process of arriving at a decision about a pre-stated hypothesis. after this procedure, the decision maker rejects or accepts this hypothesis

Estimate

the value assigned to a population parameter based on the value of a sample

Estimator

the sample statistic that is used to estimate the population parameter

Point estimate

a single value that estimates the population parameter, such as x̄ as estimate for μ or s as estimate for σ

Point estimate of a population mean

the value of the x̄, computed from the sample size which is the estimate of the population mean

Interval estimate of a population parameter

a range of values that is likely to contain the true parameter value

Confidence limits

- the endpoints of an interval

- depends on the value of the sample statistic and its sampling distribution

Confidence interval

- the range of values that estimates a population parameter, computed from the selected sample

- denoted by (1 - α) times 100%; where α is the Greek letter alpha

- a range or interval with lower and upper limits

Confidence coefficients/degree of confidence

it is denoted by 1 - a, and is the probability that an interval contains the population parameter

Confidence level

part of all possible samples (in percent) taken from a population

1.645

the zα/2 of 90%

1.96

the zα/2 of 95%

2.17

the zα/2 of 97%

2.33

the zα/2 of 98%

2.58

the zα/2 of 99%

Margin of error

is the maximum likely difference (in percentage) between the sample mean and the real population

Descriptive statistics

method of organizing and summarizing information