# Week 6 Flashcards

1
Q

What is a population?

A

all units of interest,(which can’t all be

measured)

2
Q

What are samples?

A

subsets of units taken for analysis

3
Q

What does sampling introduce?

A

sampling introduces uncertainty, because

properties of samples differ from true population values simply by chance

4
Q

What is sampling error?

A

chance deviations of sample values from true population values are called sampling error

5
Q

What is the goal of statistics?

A

Estimate the values of important parameters, including:

• means
• proportions
• variances
• effects
6
Q

What are the steps in hypothesis testing?

A
1. State the hypotheses
2. Compute the test statistic with the data
3. Determine the P-value
4. Draw the appropriate conclusions
7
Q

What is the null hypothesis(H0)?

A

is a specific statement about its value

no effect, no difference, nothing interesting going on

8
Q

What is the alternate hypothesis (HA)?

A

covers every other possibility
some effect, some difference, something
interesting going on

9
Q

if data is consistent with null hypothesis what should be done?

A

If data are consistent with the null hypothesis, we fail to reject it
we never say it’s accepted or true!

10
Q

if data is inconsistent with null hypothesis what should be done?

A

If data are inconsistent with the null hypothesis, we reject it and say that the alternate hypothesis is supported instead

11
Q

What are test statistics used for?

A

to see whether mismatch compatible with chance, or too extreme for chance to explain

12
Q

When should a t test be used?

A
```when hypotheses compare
• a mean to a null value
• two means
• two paired means (e.g., before/after)
• slopes or trends to null values```
13
Q

When should an F test or ANOVA be used?

A

more than two means

with numerical response and categorical explanatory variable

14
Q

When should χ2 (chi-squared) be used?

A

When hypotheses compare
• frequencies or proportions to null values
• frequencies or proportions

15
Q

What is the p-value?

A

the probability of obtaining a test statistic as extreme as we did if the null hypothesis is true

16
Q

What is the null distribution?

A

The sampling distribution of the test statistic when the null is true

17
Q

What are the characteristics of the null distribution?

A
• values of the statistic are on the x-axis
• probabilities of values are on the y-axis
• probabilities depend on sample size, but
decline as values get more extreme
18
Q

A

A one-sided test is more likely to reject the null hypothesis
- but we fail to reject H0 if an effect occurs in the opposite direction to HA

19
Q

What is the advantage of a two-sided test?

A

A two-sided test can detect any effect of interest

20
Q

What is a type I error?

A

rejecting H0 when true (a false positive)

21
Q

What is a type II error?

A

not rejecting H0 when false (a false negative)

22
Q

What is the probability of a type I error?

A

it has a probability of α (the significance level)

23
Q

What is the probability of a type II error?

A
• it has a probability of beta(and 1 - beta equals power)

- which depends on sample size, effect size, and precision