Chapter 17

Question 1

What does Inferential Statistics involve and it’s pupose?

Answer 1

It involves estimation, hypothesis, and testing.

It’s purpose is to make decisions about population characteristics.

Question 2

What allows us to say that Y (Sample Mean) is a good estimate of µ (Population Mean)?

Answer 2

Sampling Distributions.

Question 3

Name 4 characteristics of a sampling distribution.

Answer 3

1. Theoretical Probability Distribution
2. Random Variable is Sample Statistics
3. Results from drawing all possible samples of a fixed size.
4. List of all possible [Y, P(Y)] pairs.

Question 4

What does an uniform distribution mean?

Answer 4

The probability of each value of the random variable would be the same.

Question 5

The standard deviation of all possible sample means measures what?

Answer 5

It measures scatter in all sample means.

Question 6

Is the standard deviation of all possible sample means more/les than the population standard deviation?

Answer 6

less.

σ_Ŷ = σ / n^½.

Question 7

When sampling from a normal or non-normal population, the central tendency and dispersion are all related by

µ_ÿ = µ and σ_ÿ = σ / n^½. What are the differences of the two?

Answer 7

The population of a normal population is symmetric, whereas a non-normal popualtion is skewed.

The sampling distribution of either will be normal, as long as n >= 30 for the non-normal population.

Question 8

The ______ _____ ______ states that if you have a population with mean μ and standard deviation σ and take sufficiently large random samples from the population with replacement , then the distribution of the sample means will be approximately normally distributed.

Answer 8

central limit theorem.

Question 9

Different random samples give different values for a statistic. The distribution of the statistics over all possible samples is called the _________ __________. The _________ __________ model shows the behavior of the statistic over all the possible samples for the same size n.

Answer 9

Sampling distribution.

Question 10

Because we can never see all possible samples, we often use a model as a practical way of decribing the theoretical sampling distribution.

Answer 10

Sampling distribution model.

Question 11

The variability we expect to see from one random sample to another. It is sometimes call sampling error, but ________ _________ is the better term.

Answer 11

sampling varability.

Question 12

The Central Limit Theorem is a ______ theorem.

Answer 12

limit.

Question 13

The sampling distribution of the mean is ______, no matter what the undelying distribution of the data is.

Answer 13

Normal.

Question 14

What assumptions are required to apply the central limit theorem?

Answer 14

1. Independence Assumptions
2. Randomization Condition
3. Sample Size Condition

(The sample size, n, should be no more than 10% of the population.)