Lecture 7 Flashcards

1
Q

Each research question has…

A

A numerical answer… counts… probabilities… proportions

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2
Q

Inference definition

A

Inference is the formal name given to learning from data using statistical tools

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3
Q

What is the parameter?

A

The numerical measure of the quantity of interest in the population
- parameters are generally unknown, but can be hypothetical
- will never find the parameter

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4
Q
A

Mean of the population

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5
Q
A

Standard deviation for the population

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6
Q
A

Proportion for the population

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7
Q

What is a random variable

A

An unknown quantity that varies in an unpredictable way

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8
Q

Random variable once observed we refer to it as…

A

An observed or realised value

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9
Q

Notion of random variables

A
  • random variables are represented by upper case Roman letters
  • observed or realised value is represented by lower case Roman letters
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10
Q

What does Pr(X=x) mean?

A

‘The probability that the random variable X takes the value x’

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11
Q

Random variables are describes by

A

Probability distubutions

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12
Q

Observed values of random varieables are

A

Data

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13
Q

Random variables are describes by_______
Observed values of random variables are_____

A

-probability distubutions
-data

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14
Q

What is a statstic?

A

A numerical summary of data

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15
Q

What is an estimate

A
  • a special kind of statistic used an as intelligent guess for a parameter
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16
Q

Often estimates are denoted by adding a circumflex…

A

Û is an estimate of the parameter U

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17
Q

What is used to denote the parameter of U

A
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18
Q

x is a statistic and an estimate; U is a prarmeter

A

Yep

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19
Q

What is a statistical model

A

A mathematical description of the way the data are generated

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20
Q

What is the statistical model expressed in terms of?

A
  • parameters (Greek characters)
  • random variables (capitals)
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21
Q

The scientific equations the types of ___ and the _____ we use in our___

A

The scientific question determines the types of variable and the parameters we use in our model

22
Q

Different types of _____ give rise to different types of ___ (____)

A

Different types of variables give rise to different types of data (realisations)

23
Q

Variables - continuous

A

Can be expressed on a continuous scale in which every value is possible

24
Q

Variables - discrete

A
  • can be put in one-to-one correspondence with the counting numbers
25
Q

Variables - categorical

A
  • restricted to one of a set of categories e.g ‘heads’ or ‘tails’
26
Q

Categorical variables - binary

A
  • give rise to categorical data
  • two
  • 0-1 data - refers to the codes we use for different outcomes
27
Q

Catagerial data - more then 2

A

More then two lol
- ethnicity isn’t per se a categorical variable because people can identify with more then one

28
Q

When is categorical data nominal

A

If there is no natural (or relevant) ordering
- super market
- blood group
- prioritised ethnicity

29
Q

When is data ordinal

A

If there is no natural ordering
- exam result
- degree of pain
- socio-economic deprivation

30
Q

Discrete variables give rise to..

A

..descrete data

31
Q

With descrete data ________ take only certain _______ ____, typically ____ or _____ numbers

A

With discrete data, observations take only certain numerical values, typically integers or whole numbers

32
Q

Categorical data has no…

A

Numerical relationship

33
Q

Why are descrete data not like catergorical data

A

Because in discrete the numerical representations are always consistent
- can be treated as categorical but it discards information about the maginitue of the relationships between the numbers

34
Q

Continuous variables give rise to

A

Continuous data

35
Q

Continuous data arise from..

A

… some form of measurement

36
Q

In practice many continuous variables only take positive / negative values

A

Positive

37
Q

Restrictions on continuous variables

A

No restriction on values other then that caused by the accuracy of the equipment for recording values

However, while the underlying variable may be truely continuous, the data may be coarsened e.g age in years no seconds

38
Q

Wide range of continuous vairiable patterns

A
39
Q

Ratio

A

Fraction given by one quantity over another - both quantities have the same units

40
Q

Proportion

A

Fraction of one quantity when compared to the whole

41
Q

Proportions are often expressed in terms of…

A

… percentages

42
Q

What are rates

A
  • same as rations but for quantities with different units

E.g
- number of children per family
- number of new diagnoses of HIV in NZ per year
- to simplify rates to a ‘per unit’ measure

43
Q

Scores

A
  • obtaining measures of continuous phenomena is not always easy
  • where exact measurement is not possible a score may be used
44
Q

Scores are treated as..

A

Ordinal categories rather then continuous data
- the responses may be numbered (e.g 0,1,2,3,4) but care must be taken interpreting these as numerical data

45
Q

3 types of censored data

A
  • right censored
  • left censored
  • interval-censored
46
Q

What kind of distribution for censored data

A
  • the underlying variable follows a continuous distubution, but some values are not known exactly
47
Q

Right censored data

A
  • the true value is known to be larger then a recorded value

E.g: we know that someone lives until at least 31 December 2017

48
Q

left censored data

A
  • the true value is known to be smaller than a recorded value

E.g: we know that a measurement is less then a known limit of detection

49
Q

Interval censored data

A
  • the true value is known to lie between two values

E.g we know the date of infection with HPV is after a negative and before a positive test 2 days later

50
Q

Censored data is characterised by ____ varieables

A

Two
- e.g: for right censored data one variable gives the last known value and another indicated whether or not the measurement is censored

51
Q

Example of right censored data

A