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RDS > RDS statistics > Flashcards

RDS statistics Flashcards

1
Q

what is social accountability

A

re-orientate teaching and the research towards addressing the needs of the community that they’re based in.

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2
Q

what are the components of social accountability

A

involve patients, community members

who is benefiting from your research

addressing priority health and social needs

sustainability and best use of resources

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3
Q

define hypothesis

A

A prediction of what the answer to the research question may be
(stated at the outset of a piece of work)

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4
Q

types of hypothesis

A 
Null hypothesis
Alternative hypothesis (or several alternative hypotheses)
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5
Q

what is null hypothesis

A

states that there is no dependent relationship between two variables

e.g. Staying up all night before an exam will not affect exam performance

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6
Q

what is alternative hypothesis

A

predicts a specific and reproducible relationship between variables

e.g. Staying up all night before an exam will reduce exam performance

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7
Q

how is the hypothesis analysed

A

A statistical test is used to determine whether we can reject – or fail to reject the hypothesis.

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8
Q

what is the p value

A

likelihood that the observed difference (or something more extreme) was observed by chance.

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9
Q

what is the alpha value

A

is the probability of rejecting a null hypothesis when it is true.

For example, a significance level of 0.05 indicates a 5% risk of concluding that a difference exists when there is no actual difference. That is to say rejecting the hypothesis when it should not be rejected.

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10
Q

when is there a significant difference

A

Most authors would consider a p-value to indicate a significant difference when the probability is less than a = 0.05 (less than one in a twenty chance of being wrong)

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11
Q

A small p-value (p ≤ 0.05) indicates…..

A

strong evidence against the null hypothesis, so you reject the null hypothesis.

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12
Q

A large p-value (p > 0.05) indicates…..

A

weak evidence against the null hypothesis, so you fail to reject the null hypothesis.

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13
Q

If the p-value is equal to the a-value

A

we reject the null hypothesis

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14
Q

critical appraisal

A

critical appraisal

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15
Q

give an example of primary and secondary research outcomes with regards to Sipuleucel-T Immunotherapy for Castration-Resistant Prostate Cancer

A

primary outcome: effect of sipuleucel-T on overall survival among men with castration-resistant prostate cancer.

Secondary outcome: the effect of sipuleucel-T disease progression was observed.

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16
Q

which statistical tests can be used to assess for differences

e.g. “there is a difference exists between male and female systolic blood pressure”

A 
Chi squared test
ANOVA
T-tests
Kruskal-Wallis
Wilcoxon
Mann-Whitney U-test
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17
Q

which statistical tests can be used to assess for similarities (links)

e.g. taller people have larger feet

A

Chi squared test
Pearson
Spearman Rank

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18
Q

define quantitative data

A

numerical information about quantities

Magnitude, occurrence, association

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19
Q

quantitative data can be subdivided into:

A

Information that can be measured and have continuous dimensions

Information that can be counted but are not continuous

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20
Q

define Qualitative data

A

information about qualities; that is information that can’t actually be measured.

deals with descriptive information

Who? What? Why? When? How?

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21
Q

define and give examples of continuous data

A

data can be divided and reduced to finer and finer levels (measured)

height, temperature, blood pressure etc

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22
Q

define and give examples of discrete data

A

a count of that cannot be made more precise (counted)

number of children in a family or the number of patients in a clinic

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23
Q

define Categorical data

A

in-between quantitative and qualitative data because the ordinal aspects can be easily converted into numerical data.

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24
Q

give an example of categorical data

A

For example a scale on happiness can be given in numbers instead of words. Whereas nominal categorical data is more like qualitative data but the data consists of individual terms rather than sentences in qualitative data.

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25
Q

There are some variables that could be measured quantitatively or qualitatively such as….

A

eye colour can be measured quantitatively by assessing the RGB scale or qualitatively by categorising into blue, brown or green etc.

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26
Q

Categorical data can also be subdivided into two types:

A

nominal and ordinal

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27
Q

what is nominal data

A

items that are assigned individual named categories that do not have an implicit value .

e.g. gender (male or female) or fracture incidence (yes or no).

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28
Q

what is Ordinal data

A

items which are assigned to categories that do have some kind of implicit order, such as ‘small, medium, or large’

often used to describe a patient’s characteristics e.g. stage of hypertension, pain level, and satisfaction.

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29
Q

what does normality measure

A

the central tendency and dispersion of data and is used to decide how to describe the properties of large data-sets

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30
Q

normal distribution is often described as….

A

‘bell curved’ or ‘Gaussian’

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31
Q

what is skewed data

A

data which is a-symmetric with many data points in the high or low end of the range and an uneven tail (long on one side and short on the other)

32
Q

describe left skew

A

long left tail (refereed to as -ve skew)

The mean and median are also to the left of the peak

33
Q

describe right skew

A

long right tail ( referred to as +ve skew)

The mean and median are also to the right of the peak

34
Q

what is kurtosis

A

data that are heavy-tailed or light-tailed relative to a normal distribution

35
Q

Data sets with high kurtosis tend to have….

A

heavy tails, or outliers that create a very wide distribution

36
Q

Data sets with low kurtosis tend to have…..

A

light tails, or lack of outliers that create a very narrow distribution.

37
Q

Normality can be visually assessed by…

A

evaluating a frequency bar-chart or histogram

38
Q

The statistical tests of normality are:

A

Shapiro-Wilks test: used to test for normality with small sample sizes (n<50)

Kolmogorov-Smirnov: used to test for normality with large sample sizes (n>50)

39
Q

how is the p value used to asses normality

A

p-value <0.05 is considered to indicate a violation of normality

40
Q

median equation

A

(n + 1)/ 2 = what value in the list to look for

41
Q

define range

A

difference between largest data value and smallest data value

42
Q

define Variance

A

a measure of the spread of the numbers away from the mean value.

It is calculated by working out the average of the squared differences from the mean

43
Q

define Standard deviation

A

square root of the variance. Measures the spread of a set of data.

44
Q

define Interquartile range

A

calculated by subtracting the value of the lower quartile from the value of the upper quartile

45
Q

what are paired observations (dependent)

A

arise from measuring the same variable in the same subject at different time-points

longitudinal study

46
Q

what are unpaired observations (independent)

A

seen when comparing two groups with no common factors

cross sectional study

47
Q

give examples of parametric data sets

A

t-test (2 groups paired/unpaired)

ANOVA (3 or more groups unpaired/paired)

48
Q

when is parametric statistics used

A

quantitative data which is normally distributed.

49
Q

give examples of Non-parametric tests

A

Mann-Whitney (2 groups, unpaired)

Wilcoxon signed rank test (2 groups, paired)

50
Q

when are non parametric tests used

A

when quantitative data is not normally distributed.

51
Q

which test type is better parametric or non parametric

A

Parametric tests are easier to understand, the analyses are more powerful and they are less likely the incorrectly reject or fail to reject a hypothesis.

52
Q

types of ANOVA test

A

paired = Repeated-measures, one-way ANOVA

unpaired = One-way ANOVA

53
Q

what are 2 non-parametric equivalents of the one-way ANOVA

A

Kruskal-Wallis test ( groups or more, unpaired)

Friedman test (3 groups or more, paired)

54
Q

if data is normally distributed and you want to assess correlation what test would you use

A

Pearson’s correlation

55
Q

if data is NOT normally distributed and you want to assess correlation what test would you use

A

Spearman rank correlation

56
Q

A Pearson correlation coefficient will give you an r-value, which tells you….

A

how strong the relationship is. It will vary between -1 (represents a perfect negative correlation) and +1 (represents perfect positive correlation).

(±) 0-0.2: very low correlation
(±) 0.2-0.4: low correlation
(±) 0.4-0.6: reasonable correlation
(±) 0.6-0.8: high correlation
(±) 0.8-1.0: very high correlation
57
Q

A Pearson correlation may also give you a p-value. The p-value in this case tells you…

A

how reliable the r-value is. The smaller the p-value, the more reliable the r-value.

58
Q

The r2-value can also be reported from a Pearson correlation. This represents……….

A

how closely your data is fitted to the correlation line

59
Q

what are r and p equivalents of spearman’s test

A

A correlation coefficient (Spearman’s rho, denoted by ρ) is the equivalent of the Pearson r-value.

The p-value, once again, tells you how reliable the rho-value is.

60
Q

define correlation

A

indicates the strength of the relationship between two variables

61
Q

define Regression

A

quantifies the association between the two variables i.e. it tells us the impact that changing one variable will have on the other variable.

62
Q

regression equation

A

It is defined by a simple equation: y = a + bx

Where:

a= the y-axis intercept value

b= the gradient of the the line, i.e. the regression coefficient

63
Q

When to use the chi square test

A

used when you counted quantitative data and you want to see if there is an association/difference between your data-sets

64
Q

look at chi squared example

A

chi squared

65
Q

when to use pie chart

A

used to show the relative sizes of the parts of whole

66
Q

when to use bar chart

A

representing comparative data when one of the comparators is categorical (nominal or ordinal) and the other is numerical

67
Q

difference between histogram and bar chart

A

a histogram can have continuous numerical data on both of the axes but a bar-chart can only have continuous numerical data on one of the axes

68
Q

what is an advantage of Dot-plot over bar chart

A

provides a better visual representation of the data dispersion but it is more suitable for smaller data-sets.

69
Q

what does Box & whiskers plot show

A

5-number summary of a data-set

lower extreme
lower quartile
median
upper quartile
upper extreme
70
Q

what kind of data sets are box and whiskers plots used for

A

used to summarise a single data-set

primarily used for non-parametric numerical data

71
Q

what is scatter plot used for

A

A scatter-plot is used to identify similarities/ relationship between two data-sets

72
Q

look at Other types of graph

A

Other types of graph

73
Q

what graphs can be used to determine normal distributions

A

histograms or a box & whiskers plots ONLY

74
Q

examples of qualitative research

A

Individual interviews
Focus groups
Observations take place in natural settings and involve the researcher either videoing, photographing and/or taking lengthy and descriptive notes
Action research (or participatory action research)

75
Q

examples of Quantitative research

A

Surveys or questionnaires, observation (counting the number of times a specific phenomenon occurs), Document screening, Experiments

76
Q

what are the 6 key steps of qualitative research

A

Familiarisation
Focus
Code (categorise/organise data)
Mapping (looks for similarities, contradictions of codes)
Themes (studying the commonalities, contrasts, importance)
Interpret and explain

77
Q

appraising qualitative research

A

Was the sample used in the study appropriate to its research question?
Were the data collected appropriately?
Were the data analysed appropriately?
Can I transfer the results of this study to my own setting?
Does the study adequately address potential ethical issues?
Overall: is what the researchers did clear?

RDS (2 decks)

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