Stats: Review Chapter 8

A Confidence Interval consists of:

• statistic

• t and z

• statistic, critical value, and standard deviation of statistic

• statistic, critical value, and probability

The correct formula for a Confidence Interval is:

• Statistic ± (critical value) * (standard deviation of statistic)

• Statistic + (critical value) * (standard deviation of statistic)

• Statistic + (critical value) * (confidence level)

• Critical Value ± (statistic) * (sample size)

To interpret a Confidence Level you would say:

• 95% of all possible samples of a given size from a population will result in a probability greater than the alpha level

• 95% of all samples of a given size will result in an interval that is greater than the unknown parameter

• 95% of all samples of a given size will result in an interval that is smaller than the unknown parameter

• 95% of all possible samples of a given size from a population will result in an interval that captures the unknown parameter

What is the correct way to interpret a Confidence Interval?

• The interval from .375 to .478 does not capture the parameter value.

• We are 95% confident that the interval from .375 to .478 captures the actual value of the population parameter

• We are 95% confident that the interval from .375 to .478 captures the actual value of the confidence level

• 95% of all possible samples of a given size from a population will result in a interval that capture the unknown parameter

Confidence Intervals are statements about:

• parameters

• statistics

• confidence levels

• chi square statistics

If you were given

statistic: .426

Critical Value: 1.96

Standard Deviation: .031

the correct way to construct an interval would be:

• .426 + (1.96) * (.031)

• .426 ± (1.96) * (.031)

• 1.96 ± (.426) * (.031)

• .426 ± (1.96)

The statistic for a 95% confidence level would be

• 1.96

• 1.28

• 2.575

• 2.326

What would the calculator function be when finding the critical value of a 99% Confidence Level?

• InvNorm(.99, 0, 1)

• InvNorm(.90, 0, 1)

• InvNorm(.99, 1, 0)

• InvNorm(.995, 0, 1)

What is the Independent condition?

• Condition stating that the individual observations are independent and that our sample size is less than a tenth of the population.

• Condition stating that our successes and failures must be greater than 10

• Condition stating that the individual observations are independent

• Condition stating that our successes and failures must be less than 10

What are the appropriate conditions that must be met first in order to estimate a confidence interval?

• The successes and failures are greater than 10

• Random, Normal, Independent

• Random

• Random and 10% condition