Chapter 18

Question 1

These involve categorical variables, are represented by a fraction or % of population or sample in a category, and if there exists two categorical outcomes then we can invoke the Binomial Distribution.

Answer 1

Proportions.

Question 2

What are two types of estimation methods in inferential statistics?

Answer 2

Point estimation: Sample statistics like sample population.

Interval estimation: Confidence interval.

Question 3

This method provides single value, based on observations from 1 sample. Gives no information about how close value is to the unknown population parameter.

Answer 3

Point estimation.

Question 4

This method provides a range of values based on observation from 1 sample. It gives information about closeness to unknown population parameter that is stated in terms of probability. Knowning exact closeness requires knowing unknown population parameter.

Answer 4

Interval Estimation.

Question 5

Probability that the unknown population parameter falls within interval, it denoted by (1 - α) %. α is the probability that parameter in Not within interval.

Answer 5

Confidence Level.

Question 6

What are the factors affecting interval width?

Answer 6

1. Data Dispersion, measured by σ.
2. Sample size, σÿ.
3. Level of confidence, (1 - α).

Affects Z.

Question 7

What assumptions do we test to be able to use the confidence interval formula?

Answer 7

Two categorical outcomes, Random sample, is the sample large enough.

To test if it is large enough we will use np > 10 and n(1-p) > 10.

p = p hat = sample statistic called proportion.

(The bold is shown to be the most important assumption for the class).

Question 8

Interpret the confidence interval.

Answer 8

I am % confident that the population proportion/mean of (context) is between # and #’.