Medical Statistics

Question 1

What is ontology?

Answer 1

The study of being, theory of knowledge, concerned with what is true.

Question 2

What is epistemology?

Answer 2

What can be known and what we can know about it.

Question 3

What key idea of quantitative research?

Answer 3

Scientific method
Focus on what is measurable and observable.
Concrete objective
Positivism - something is only true when it can be measured or observed, this is how we know it is true.

Question 4

What is the purpose of concepts in stats?

Answer 4

Can be measured or manipulated.
Dependent, independent, confounding, control.

Question 5

What is meant by descriptive stats?

Answer 5

When large data is condensed and represented
For example measures of central tendedency and dispersion
Different techniques for normal,y distributed and not normally distributed data.
E.g mean, std dev, median IQR.

Question 6

What is the difference between using a sample or a population in stats?

Answer 6

Sample - only some of population, can make inferences. If our sample better reapresents the population we can be more confident in these inferences to mirror the correct conclusion.
Population - whole population can draw conclusions

Question 7

What is inferential statistics?

Answer 7

Using data nd measurement s from a sample to make assumptions about a population.
Inference based on the balance of probability

Question 8

What is hypothesis testing?

Answer 8

Taking an assumption or idea and testing it, by considering how much doubt or support evidence places on the hypothesis.

Question 9

What is meant by a null hypothesis?

Answer 9

Default position, most reasonable explanation assumes nothing is going on.
The effect being studied does not exist, no significant difference between different independent values.
Most try to prove null hypothesis wrong to show significance.
Symbol is Ho

Question 10

What is binomial distribution?

Answer 10

Statistical Value based on the likelihood of success occurring for a certain number of repeats when there are two possible outcomes for each repeat and the probability of success remains the same for each repeat.

Question 11

What is frequentism?

Answer 11

The interpretation of probability, how likely an event is to reoccur in a set number of trials.

Question 12

What is a P value?

Answer 12

Probability
The probability of what you observed occurring if the null hypothesis is true
Therefore small number encourages to reject the null hypothesis.

Question 13

What is an alternative hypothesis?

Answer 13

H1 indicates something else above the default position is going on
The theory or relationship we are trying to prove, is accepted when there is enough evidence to reject the null hypothesis

Question 14

What is probability?

Answer 14

The likelihood of getting a sample as or more xtreme than our observed results assuming the null hypothesis is true

Question 15

What p value is often sued to reject the null hypothesis?

Answer 15

P =< 0.05
This is statistical significance

Question 16

What is a type 1 error?

Answer 16

False positive

Question 17

What is a type 2 error?

Answer 17

A false negative

Question 18

What are the four different outcomes from a study?

Answer 18

False positive
True negative
True positive
False. Egative

Question 19

What is meant by power in statistics?

Answer 19

The ability of a test to find an affect if there us one, asleaus want to maximise power .

Question 20

What is a confounding variable?

Answer 20

An unmeasured variable that affects both the dependent and independent variable, can sometimes make it appear that their is a relationship between the dependent and independent whilst in reality this is not true.

Question 21

What is meant by high power of a test?
How does this relate to the outcome of hypothesis testing?

Answer 21

Power is the ability of a test to find an effect if there is one.
A high power test gives a true positive result (H0 is false and we have rejected H0)

Question 22

How does our decision regarding the null hypothesis and the actual true situation of the null hypothesis influence the outcome of the study?

Answer 22

We can never know the true situation of the null hypothesis therefore we are only balancing hypothesis.
H0 rejected and H0 true - false positive -as assuming effect whilst none
H0 rejected and H0 false - true positive
H0 accepted whilst H0 true - true negative - assume no effect when is no effect
H0 accepted with H0 false - false negative - assume no effect when there is one.

Null - negative
Alternative - positive.

Question 23

What is the significance level and how does it effect error rates?

Answer 23

Significance level - the p value at which you decide to reject the null hypothesis
Lower P value - less type 1 errors, more type 2 errors

Question 24

What is meant by effect size in stats?

Answer 24

How meaningful the relationship between variables is
Indicates the practical significance of research - e.g how likely is it to influence medical practise.

Question 25

How does population size effect power in stats?

Answer 25

A larger sample size increases power Power analysis can identify the number of participants required to achieve a certain effect.

Question 26

What is a confidence interval in stats?

Answer 26

The probability or confidence that you have in your population parameter falling within your sample values Gives an upper and a lower band - the number e.g 95% - is the likelihood that you are correct and that the population parameter or a repeated on a different sample value will be found here

Question 27

How do confidence intervals relate to the null and alternative hypothesis?

Answer 27

Null hypothesis rejected if larger interval or no overall between confidence interval Null hypothesis is assumed correct if confident intervals overlap.

Question 28

What are some different types of research design?

Answer 28

Descriptive Correlational Experimental Review Meta-analytic

Question 29

What effects the research design?

Answer 29

The variable type (what is sampled and how it is collected)

Question 30

What is a descriptive research design?

Answer 30

Often a case study Naturalistsi observation - qualitative observe and record individuals in natural environments Cannot statistically infer unless we have the entire population

Question 31

What is a correlation research design?

Answer 31

Often from a case control Considers the relationship between two variables free from manipulation Cannot determine cause and effect The third variable problem can cause spurious correlations Modelling a line of best fit to your data can be predictive

Question 32

What methods can be used to analyse a correlational study?

Answer 32

Pearson Spearman rank Point biserial

Question 33

What is an experimental research design?

Answer 33

When researchers manipulate a variable and tests the effect of this change on another variable For example - random control trials Can compare two groups or the same group (pre and post change)

Question 34

What is the idea of a randomised control trial?

Answer 34

Simple test of difference. Compares similarity of two sample estimates Or use ANOVAs to compare more than two groups, generalise t test to more sample estimates

Question 35

What is a review as a method of research design?

Answer 35

Literature review: overview of previously published works, generally descriptive Systematic review: more detailed and comprehensive plan/search stratergy

Question 36

What is a meta-analysis as a method of research design?

Answer 36

Analysis that combines findings of multiple studies Contrasts results across studies Provide better estimate of the unknown population size effect.