3: Estimation and Confidence Intervals

Question 1

A ___ is the statistic, computed from sample information, that estimates a population parameter.

Answer 1

Point estimate

Question 2

A ___ is a range of values constructed from sample data so that the population parameter is likely to occur within that range at a specified probability. The specified probability is called the level of confidence.

Answer 2

Confidence interval

Question 3

To demonstrate the idea of a confidence interval, what is the one simplifying assumption?

Answer 3

We know the value of the population standard deviation, σ

Question 4

The width of the interval is determined by two factors:

1. ___
2. ___

Answer 4

1. The level of confidence

2. The standard error

Question 5

A ___ is the fraction, ratio, or percent indicating the part of the sample or the population having a particular trait of interest.

Answer 5

Proportion

Question 6

To develop a confidence interval for a proportion, we need to meet two requirements:

1. ___
2. ___

Answer 6

1. The binomial conditions have been met
2. The values nπ and n(1 − π) should both be greater than or equal to 5. This allows us to invoke the central limit theorem and employ the standard normal distribution, that is, z, to complete a confidence interval.

Question 7

Our decision for choosing an appropriate sample is based on three variables:

1. ___
2. ___
3. ___

Answer 7

1. The margin of error
2. The level of confidence desired
3. The variation or dispersion of the population being studied

Question 8

A ___ occurs when sampling without a replacement in a finite population, a correction term is used to reduce the standard error of the mean according to the relative size of the sample to the size of the population; used when the sample is more than 5% of the population for more precise measures.

Answer 8

Finite-population correction factor (FPC)

Question 9

The major characteristics of the t distribution are:

1. ___
2. ___
3. ___
4. ___

Answer 9

1. It is a continuous distribution.
2. It is mound-shaped and symmetrical.
3. It is flatter, or more spread out, than the standard normal distribution.
4. There is a family of t distributions, depending on the number of degrees of freedom.