Stats Flashcards

1
Q

Define bias

A

Systematic difference between the observed effect and the true effect. Not due to chance.

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2
Q

Define categorical data

A

categorical data refers to data is qualitative, describes a quality. It can either be ordinal or nominal

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3
Q

Define evidence based medicine

A

The use of the best available scientific research to guide clinical decision making

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4
Q

Define NNT

A

Number needed to treat refers to the number of patients needed to be treated with an intervention for 1 patient to have a benefit. Equals 1/ ARR

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5
Q

Define PPV and NPV

A

PPV: given the test is positve, what proppriton actually have disease= TP/ TP+ FP NPV: given that the test is negative, which porpotion don’t have disease: TN/ FN + TN

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6
Q

Define quantitative data

A

Quantitative data is numerical. It can be continuous or discrete. Continuous data can either be ratio (a zero point exists) or interval

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7
Q

Define relative risk reduction; absolute risk reduction

A

RRR= differnece between the incidence in the unexposed verus exposed / the incidnece in the unepxosed ARR: difference in the incidence between the unexposed and exposed.

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8
Q

Define risk ratio; define odds ratio;

A

risk ratio= relative risk: incidence in the exposed/ incidence in the unexposed.Used for RCT/cohort studies Odds ratio: odds of event in the exposed/ odds of the event in unexposed. Use in case control studies when can not determine incidence. Approximates relative risk, especially for rare events.

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9
Q

Define standard deviation; define variance

A

standard deviation: square root of the variance; vairance: the average of the squared differences from the mean = E (x- average x)** / (n-1)

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10
Q

define standard error of the mean (SEM)

A

SEM is the standard deviation of the sampling distribution. SEM= s/sqr(n) (sqr=square root)

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11
Q

Define Standardised Mortality ratio

A

Defined as the observed mortality rate/ expected mortality rate (as estimated from scoring systems such as APACHE II)

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12
Q

List non- parametric tests

A

Chi squared Wilcoxon Mann Whitney U test Kruskal wallis

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13
Q

What are the features of a normally distributed population

A

mean= mode= median bell shaped curve 68% of poupulation within 1 SD of mean 95% of populatio within 2 SD of mean

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14
Q

What are the parametric tests

A

t-test ANOVA

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15
Q

What are the Wilcoxon rank sum test, Wilcoxon paired sample test; Mann Whitney U test and Krsukal Wallis tests?

A

Wilcoxon rank sume test: non parametric equivalent of t test Wilcoxon paired sample test: non paramertric equivlanet of paited t test Mann Whitney U test: Non parametric equivalnet of t test Kruskal Wallist test: non parametric equivalent of ANOVA (i.e. more than 3 groups with continuous variables)

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16
Q

What assumptions are made in parametric tests

A

The data is continuous. The samples have the same variance and have been taken from a normally distributed population

17
Q

What factors affect the power of a study

A
  1. The sample size 2. The effect size 3. the variation in the study population for the effect 4. the significance level chosen (alpha)
18
Q

what is a meta analysis

A

a mathematical process which seeks to provide a pooled estimate of effect from several trials

19
Q

What is a systematic review

A

a planned unbiased summary of evidence adressing a specific clinical question

20
Q

what is ANOVA

A

ANOVA- analysis of variance - a paramtric test which determines if there is a difference amongst 3 or more groups with continous vairbales. Does not tell you which group is differnt.

21
Q

What is statisitical Power

A

measures the chance of detecting a significant difference when such a difference exists. Equals 1- type II erorr. Usually want it to be at least >80%

22
Q

What is the chi squared test

A

tests whether there is a real differnce in the frequency of categerocial events between two or more groups

23
Q

What is the confidence interval

A

CI is the range around a sample mean within which you predict the true mean lies

24
Q

What is the null hypothesis

A

states that there is no effect.

25
Q

What is the P value

A

The probability of of the observed difference having occured by chance. Therefore give the likelihood of the Null Hypothesis being true.If P large: can not reject the null hypothesis. If P small: reject null hypothesis , knowing there is a smallchance that it is true.

26
Q

What is the Receptor Operator Characteristic curve

A

Plots sensitvity (y axis) against 1-specificty (equivalent to the false positive rate) (x axis)

27
Q

What is type 1 and type 2 error

A

Type 1: conclude there is a difference, when there isn’t. False positives. Determined by the significance level set Type 2 error: conclude that there isn’t a difference when there is on.e Flase negatives. Commonly caused by small sample size.