Study design, data types and distributions Flashcards

1
Q

What are the different study desgins

A
  • Experimental study
  • Observational study
  • Prospective vs retrospective
  • Cross sectional vs longitudinal
  • Representative
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2
Q

What is an Experimental study

A
  • Randomised controlled trial (RCT)
  • Intervention group (e.g. new drug) vs placebo group
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3
Q

What is an observational study

A
  • No interventions, just observations
  • Cohort study: A group of subjects linked in some way, e.g. geographical region
  • Case-control study: e.g. people with a disease vs those without
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4
Q

What is the difference between Prospective vs Retrospective

A
  • Prospective (real-time) vs Retrospective study (data collected about past)
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5
Q

What is the difference between Cross-sectional and longitudinal study

A
  • Cross-sectional (a point in time) vs longitudinal study (collection of data on same participants over an extended period of time)
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6
Q

What counts as a Representative sample

A
  • Random Sample
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7
Q

What are the two different types of data

A
  • Quantitative and Qualitative
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8
Q

What is Qualitative data

A
  • Subjective characteristics and opinions
  • Things that cannot be expressed as a number
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9
Q

What type of quantitative data is there

A
  • Continuous and discrete data
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10
Q

What is continuous data and give examples

A
  • Data that can be measured
  • e.g. height, weight, age, tempreature
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11
Q

What is discrete data and what are the 3 different types of discrete data is there

A
  • Can be counted
  • 3 different types are nominal, ordinal and interval
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12
Q

What is Nominal data and give examples

A
  • Categories with no ordering
  • e.g. number of students
  • e.g. male, female
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13
Q

What is ordinal data and give examples

A
  • Ordered categories
  • e.g. first, second, third
  • o hours, 1-4 hours, 5+ hours
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14
Q

What is interval data and give examples

A
  • Known, equal intervals
  • e.g. £0-10k, £10-20k, £20-30k
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15
Q

what words can describe the distribution of data

A
  • Normal (also called the Gaussian distribution)
  • Uniform
  • Exponential
  • Binomial
  • Geometric
  • Poisson
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16
Q

What is the purpose of descriptive statistics?

A
  • To describe the distribution of a phenomenon
  • e.g. height in a population
  • e.g. proportion of highly educated in a population
17
Q

Descriptive statistics cannot be used to make an inference without what?

A
  • Statistical test
18
Q

What does descriptive statistics measure?

A
  • Location, dispersion (spread) of data, association (for two variables)
19
Q

What statistical measurements are used to describe a middle point or central tendency

A
  • Arithmetic mean, median
20
Q

What is the purpose of the mode

A
  • To describe the most common value in data
21
Q

What statistical measurements is used to describe the cut-off point where the distribution reaches a certain probability, e.g. 25% of the sample?

A
  • Fractile, e.g. quartiles, frequencies, percentage
22
Q

What statistical measurements are used to describe how spread out the data is?

A
  • Standard deviation, range (min, max), interquartile range
23
Q

What statistical measurements is used to describe the association between two variables

A
  • Contingency tables (cross-tabulations), Correlation
24
Q

What is the standard deviation?

A
  • The most commonly used measure of spread or variability in the sample
  • Measure how spread the data are around the mean
25
What is the relationship between variance and standard deviation
- SD = squared variance
26
What does a high and low SD indicate
- High SD = very spread out data, lots of variability - Low SD = data are tightly grouped, very similar values, there is little variability
27
What does SEM mean
- Standard Error of the Mean
28
What does SEM measure?
- Measure the variability across many samples in a population
28
What is skewness used to measure?
- Measure the degree of asymmetry of a distribution. - Quantifies the degree of distortion from the normal distribution.
28
For skewed distribution is it better to report median or mean
- Median
29
What is Kurtosis used to measure?
- measure that describes how heavily the tails of a distribution differ from the tails of a normal distribution
30
What are the two commonly used measurements for correlation
- Pearson correlation and Spearman correlation
31
Both Pearson and Spearman correlation both give us what?
a correlation coefficient
32
Name the qualities of the Pearson correlation
- Quantitative traits - Linear relationships
33
What are the qualities of Spearman correlation
- Quantitative or ordinal data, e.g. Likert scale (1,2,3,4,5) - Does not require a linear relationship; however, needs the data to follow a monotonic relationship - Good for non-normal data - Based on ranks of the data
34
Explain correlation of two variables
- If the two variables are not associated, their correlation is 0 but it is not true and vice versa - correlation 0 does not necessarily imply no associations
35
What are the different graphical ways of describing data
- Bar chart - Histogram - Boxplot - Density plot - Scatter plot