Probability and Statistics Flashcards

1
Q

2 ways a study can screw the pooch

A

caused by chance (random error)

not caused by chance (bias or systematic error)

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2
Q

what deals with random errors

A

statistical inference

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3
Q

T/F random errors bias a study

A

false

may be wrong but not biased

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4
Q

what is a systematic error

A

error that is inherent to the study method being used and results in a predictable and repeatable error for each observation

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5
Q

T/F systemic errors bias a study

A

true

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6
Q

T/F there is a formal method to deal with systematic errors

A

false

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7
Q

tests of statistical inference

A

estimate the likelihood that a study result was caused by chance

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8
Q

T/F statistically significant means clinically important or meaningful

A

false

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9
Q

what is a chance occurrence

A

something that happen unpredictably without discernible human intention or with no observable cause

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10
Q

random variation

A

there is error in every measurement

if measure something over an over again will get slight variations in measurements

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11
Q

what does statistical inference tell us

A

if we measure something only once, how sure are we that our measurement has been caused by chance

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12
Q

what 2 methods are used to estimate random variation in a study

A

confidence intervals

p-values

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13
Q

T/F width of the CI is related to sample

A

true

  • small samples have large CI
  • large samples have small CI
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14
Q

T/F if the 95% CI for the OR does not include one the OR is statistically significant

A

true

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15
Q

T/F the same rules apply for OR, PR, RR when it comes to CI

A

true

if CI spans one they are statistically insignificant and there is no association

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16
Q

what do P-values estimate

A

whether a measured association was likely to have been caused by chance

17
Q

Does P-value give you information on size of sample and range of true value

A

it sure as shit doesn’t

18
Q

to be statistically significant p-value must be less than

A

0.05

19
Q

how do you calculate p-value

A

chi-squared test

student’s T-test

correlation

20
Q

null hypothesis

A

hypothesis of no association

21
Q

alternative hypothesis

A

the research question

there is an association between exposure and disease

22
Q

T/F we use p-values or CIs accept or reject the null hypothesis

A

true

23
Q

wha is a type 1 error

A

false positive

  • reject the null when it is not false
  • saying there is an association when there isn’t
24
Q

what is a type II error

A

false negative

  • not rejecting the null when it is false
  • saying there is no association when there is
25
Q

types of data

A

categorical

continuous

26
Q

categorical data

A

broken into discrete categories

  • nominal
  • ordinal
27
Q

continuous data

A

variable is numeric and can have any one of many possible values

28
Q

nominal

A

named, not ordered

horse vs. donkey; stallion vs. gelding vs mare vs colt vs filly

29
Q

ordinal

A

named ad ordered by nor constant value between ranks

neonate vs juvenile vs adult vs geriatric

30
Q

describe categorical data

A

frequency distribution

may be represented as a table or bar chart

statistical test

31
Q

describe continuous data

A

frequency distribution and histogram

describe the center of the distribution

describes the amount of dispersion

describe the shape of distribution

statistical tests

32
Q

what is central tendency

A

describes the center of the distribution

mean, median, mode

33
Q

what is dispersion (spread)

A

describes how closely the values are gathered around the center of distribution
range, standard deviation

34
Q

Chi-squared test

A

test of independence between 2 categorical variables

p-value

used for categorical data

35
Q

student’s T-test

A

difference in means
compare averages of 2 groups
used for continuous data

H0=means of 2 groups are the same

Ha= can be one or two tailed

36
Q

correlation

A

measures the strength and direction of a linear relationship between 2 continuous variables

37
Q

correlation coefficient (r)

A

often used for dose response relationships

both variables are numerical, usually continuous

  • strong: r>0.80
  • weak: r