PASS Statistical Concepts Flashcards

1
Q

Population meaning in stats

A

All possible observations of an experiment/study variable

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

Sample meaning in stats

A

A selection of observation taken from the population - a small group of the population

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Types of errors

A

Random error due to chance
Systematic error due to bias

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

What is random error due to?

A

Due to chance + sampling variation

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

How to reduce random error

A

Increasing sample size reduces random error

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

What is bias quantified by?

A

The difference between the true value and the expected value

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

Relationship between random error and sample size

A

As sample size increases, random error decreases

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

Relationship between systematic error and sample size

A

Changing sample size has no effect no systemic error - does not reduce

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

What is a hypothesis?

A

A statement that an underlying truth of scientific interest takes a particular quantitative value

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

What is a p-value?

A

The probability of getting an observation as extreme as or more extreme than the one observed in the hypothesis is true

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

When do you reject the null hypothesis at the 5% level?

A

When p-value < 0.05

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

What do you do with the null hypothesis at the 5% level when the p-value < 0.05?

A

Reject null hypothesis

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

Limitation of hypothesis testing

A

Rejecting a hypothesis is not always useful:
-statistically significant ≠ clinically important
- statistical significance depends on sample size

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

What is a 95% confidence interval?

A

The range within which we can be 95% certain that the true value of the underlying truth really lies

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

Relationship between confidence interval andsample size increases

A

As sample size increases, random variation + uncertainty decreases

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

Null value of ratio

A

1

17
Q

Null value for a difference

A

0

18
Q

What is a null value?

A

An estimate that shows no difference between two groups

19
Q

Relationship between confidence interval and p-value

A

Will always agree on statically significance

Null hypothesis inside 95% CI - p >0.05
Null hypothesis outside 95% CI - p<0.05

20
Q

When is the 95% confidence interval wider?

A

Greater the variation in the population values
Smaller the size of thesample used to calculate it

21
Q

What does PICO stand for?

A

Population
Intervation
Comparison
Outcome
What is the population to be studied?
What is the intervention of interested?
What is the comparision/control?
What is the outcome of interest?

22
Q

Descriptive epidemiology study designs

A

Ecological study
Cross sectional surgery

23
Q

Unit of analysis in ecological study

A

Groups

24
Q

Unit of analysis of cross sectional survey

A

Individuals

25
Q

Analytical epidemiology study designs

A

Case-control study
Cohort study

26
Q

What ratio is related to case-control study?

A

Odds ratio

27
Q

What ratio is related to cohort study?

A

Rate or odds ratio

28
Q

Issues for ecological studies

A

Definition of characteristics
Measurement variation
Confounding
Random error