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OTHY 104 - Evidence Based Practice and Measurement in Occupational Therapy > Statistics in Allied Health > Flashcards

Statistics in Allied Health Flashcards

1
Q

What is the purpose of statistics?

A
  • control sources of variation; detect outliers
  • analysis of data
  • interpret the statistical and practical significance of results
  • in making scientifically sound decisions and communicating them
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2
Q

What are descriptive statistics?

A
  • describe what was observed in the sample numerically or graphically
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3
Q

What are some common numerical descriptors?

A

Mean and standard deviation for continuous data types (i.e. age)

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4
Q

Frequency and percentages are useful for describing what data?

A

categorical data i.e. gender

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5
Q

What is inferential statistics?

A

uses patterns in the sample to draw inferences about the population represented

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6
Q

What are some examples of inferential statistics?

A
  • Hypothesis testing: yes/no questions about the data
  • Estimation: estimating numerical characteristics of data
  • Correlation: describing associations within the data
  • Regression analysis: modelling relationships with the data
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7
Q

What can inferential stats be used for?

A
  • forecasting, prediction and estimation of unobserved values either in or associated with population studies
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8
Q

What is a sample as compared to a population?

A
  • sample is a subset of the population

- population is a group of people with a common trait

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9
Q

What is one of the most important factors of the sample?

A

It’s representation on behalf of the population as we use the sample to infer about the population.

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10
Q

What are the two types of sample selections?

A
  • probabilistic: everyone has a similar chance of being selected
  • non-probabilistic: not everyone has the same chance of being selected
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11
Q

What are some probabilistic sampling methods?

A
  • simple/stratified random sampling

- systematic random sampling

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12
Q

What are some non-probabilistic sampling methods?

A
  • convenience sampling
  • snowball sampling
  • purposive sampling
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13
Q

What are the 4 types of variables?

A

Nominal, ordinal, interval and ratio

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14
Q

What is nominal data?

A

numbers given to a variable have no significance

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15
Q

What is an example of nominal data?

A

0 = male, 1 = female

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16
Q

What is a dichotomous variable?

A

a variable (nominal) with two possibilities

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17
Q

What is ordinal data?

A

the order of the number holds significance

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18
Q

Give an example of ordinal data

A
  • pain scale

- likert scale

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19
Q

What is interval data?

A

continuous variable, the value of 0 does not indicate the absence of a quality

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20
Q

Give an example of interval data

A

temperature

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21
Q

What is ratio data?

A

continuous variable where the value of 0 does indicate the absence of a quality

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22
Q

What is an example of ratio data?

A

weight

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23
Q

When is a continuous variable classified as discrete?

A

if it is restricted to a fixed number of values

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24
Q

What is raw data?

A

value the same unit as it was measured in

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25
Q

What is scaled data?

A

units of measurement given a relative value that makes it comparable to other values in the general population

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26
Q

What is the criterion variable/outcome variable?

A

The presumed effect in a study

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27
Q

What is the predictor variable/covaraite

A

The presumed cause in a experimental study (potentially associated with the outcome variable)

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28
Q

What is relative frequency?

A

The frequency in a subgroup relative to the total number

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29
Q

What are mutually exclusive variables?

A

Variables that don’t overlap

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30
Q

What is a example of a mutually exclusive variable?

A

age

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31
Q

What data does bar graphs show?

A

crude data not relative data

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32
Q

What data does pie graphs show?

A

can show both crude and relative data

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33
Q

What do scatter plots show?

A

correlation between two continuous variables simultaneously

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34
Q

What do line graphs show?

A

time trends where the x axis shows the unit of time and the y axis displays the values of the variable being plotted

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35
Q

What do histograms show?

A

differences in frequencies or percentages among categories of continuous variables

36
Q

In a histogram, what is the 1) width of the bars 2) height of the bars proportional to?

A

1) width of the category

2) frequency of percentage of that category

37
Q

What does the histogram present?

A

distribution of data, gives an estimate of the probability distribution of continuous variable. Shows how skewed/shifted data is

38
Q

In a histogram, if the data is left tailed what does it mean?

A

negative skew

39
Q

In a histogram, if the data is right tailed what does it mean?

A

positive skew

40
Q

What does a box plot body represent?

A

the first to third quartile

41
Q

How are outliers plotted in a box plot?

A

separately as positions on the chart

42
Q

What is the line in the box plot body?

A

median of data set

43
Q

What are the whiskers in a blot plot represent?

A

bottom whisker - Quartile 1 to lowest non-outlier

top whisker - Quartile 3 to largest non-outlier

44
Q

What are some measures used in quantitative research?

A
  • counts i.e. number of patients
  • proportion: relative frequency, must be divided by the total number in the group
  • rates: used to involve or imply a relationship
  • measures of central tendency: measures that best represents the data
45
Q

What are some measures of central tendency?

A
  • mean
  • median
  • mode
46
Q

How is the mean calculated?

A

add all observations and divide by number of observatios

47
Q

What is the mean effected by?

A

In repeated measures but is easily effected by extreme values

48
Q

What is the median

A

The middle value i.e. 50% of data above and below the median

49
Q

Is the median effected by extreme values?

A

no

50
Q

What is the mode?

A

most commonly occurring value

51
Q

Is the mode effected by extremes?

A

no

52
Q

What are measures of variability?

A

Inform of the spread of the ata

53
Q

What are some measures of variability?

A

standard deviation, range and interquartile range

54
Q

What is variance?

A

average of the squared differences of each of the observations from their mean

55
Q

What does a low and high standard deviation mean?

A
  • low: little spread of data

- high: large spread of data

56
Q

What must the sum of deviations around the mean equal?

A

0

57
Q

What is the normal distribution?

A

a curve that is bell-shaped and symmetrical around the mean

58
Q

What is the area under a bell-curve equal to?

A

1

59
Q

In normal distribution, what values are equal?

A

mean, median and mode

60
Q

How many values lie 1 standard deviation away from the mean?

A

68%

61
Q

How many values lie 1.96 standard deviations away from the mean?

A

95%

62
Q

How many values lie 2.58 standard deviations away from the mean?

A

99%

63
Q

What is the confidence interval?

A

limits within which the true population probably lies. Gives a range of values that may reasonably contain the true population parameter

64
Q

What are the parameters of the confidence interval?

A

lowest value (lower confidence limit) and highest value (upper confidence limit)

65
Q

What is the 95% confidence interval?

A

the range of scores or values in which it is 95% confident that the true population mean lies

66
Q

What is a null hypothesis?

A

A is similar to B or A is not different to B

67
Q

What is alternative hypothesis?

A

A is different from B or A is larger/smaller than B (there is a relationship between variables)

68
Q

What is a type 1 error?

A

when we reject the null hypothesis when it’s true

69
Q

What is a type 2 error?

A

when we accept the null hypothesis when it’s not true

70
Q

What is the power?

A

the probability of rejecting the null hypothesis when it’s false

71
Q

What is the P value?

A

significance of comparison

72
Q

What does a P value smaller than 0.05 mean?

A

researcher is confident enough the reject the null hypothesis and accept alternative hypothesis

73
Q

What can a P value tell us?

A

observed difference between compared measures could have been obtained by chance alone

74
Q

How can nominal data be analysed?

A

non-parametric statistic techniques i.e. counting individuals in groups

75
Q

What are some weaknesses of ordinal scales?

A

may be subjective - terms need to be clearly defined

76
Q

How can ordinal data be analysed?

A

non-parametric statistic techniques

77
Q

What are the continuous variables?

A

interval and ratio data

78
Q

How can interval and ratio data be analysed?

A

parametric statistical techniques

79
Q

What is an accurate measure?

A

One which close to true population value

80
Q

What is a precise measure?

A

one which yields close to the same value with many repetitions

81
Q

Where does systematic error arise from?

A

measuring, collecting, analyzing and interpreting data

82
Q

What does a CI of 90% mean?

A

90% sure the patient’ true score lies within a determined range

83
Q

What does a P values of >0.05 indicate?

A

results were chance findings

84
Q

What do percentiles indicate?

A

how many lie above and below the score

85
Q

What are the quartiles?

A

1st quartile: 25th percentile
2nd quartile: 50th percentile
3rd quartile: 75th percentile

86
Q

What are the deciles?

A

First Decile: 10th percentile

Second decile: 20th percentile etc.

OTHY 104 - Evidence Based Practice and Measurement in Occupational Therapy (6 decks)

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