Sampling distribution and hypothesis testing

Question 1

What is a sampling distribution and why is it important?

Answer 1

Distribution of scores that would be generated if one were to repeatedly draw random samples of a given sample size from the population and calculated the statistics of interest for each sample

Importance: provides us with the amount of variation that we can expect for a statistic due to sampling variation

Need this for inferential statistics

Question 2

What is standard error and why is it important?

Answer 2

The standard deviation of the frequency distribution

Measures how much random variation to expect from samples of equal size from same population.

Question 3

The size of standard error is a function of what two things?

Answer 3

The size of the sample

The population standard deviation

Question 4

What is a test statistic?

Answer 4

Signal to noise ratio

observed effect/standard error of effect

Question 5

What is the general goal of hypothesis testing?

Answer 5

To rule out chance (sampling error) as a plausible explanation for our results.

Question 6

What are the four steps of hypothesis testing?

Answer 6

1. State hypothesis and specify alpha level.
2. Locate the critical region.
3. Calculate the test statistic.
4. Make a decision (accept or reject the null hypothesis).

Question 7

What is a p-value?

Answer 7

the probability that the null hypothesis is correct; probability of getting your results given that the null hypothesis is true

Question 8

What is alpha level?

Answer 8

The probability value that is used to define very unlikely sample outcomes if the null hypothesis is true;
probability of falsely rejecting the null hypothesis