descriptive statistics

Question 1

categoric variable

Answer 1

individual fall into one of several categories
binary: 2 categories e.g. yes/no
ordinal:>2 categories, with a natural ordering e.g. low/medium/high
Nominal: >2 categories but no ordering e.g. hair colour

Question 2

numerical variables

Answer 2

variables measured on a numeric scale

discrete: there is a distinct number of values e.g. years in age
continuous: any value within a particular range e.g. blood pressure

Question 3

descriptive statistics (categorical)

Answer 3

• Probability/ proportion = the number with outcome/ the total number (scale 0 to 1)
• Percentage = (proportion)*100 (scale 0 to 100)
• Rate= the number of times something happens per a quantifier (x per 100 people) (scale 0 to infinity)
• Odds = the number with the outcome/the number without the outcome (scale 0 to infinity)

Question 4

quantifying differences

Answer 4

• Not sufficient to say ‘one looks more effective’, want to quantify that measure

Question 5

risk ratio (RR)

Answer 5

• Divide one probability/percentage by the other
• Whichever group goes on the top is the focus
• When we divide two numbers together, there are 3 potential outcomes (>1,=1,<1)

Question 6

odds ratio (OR)

Answer 6

• Divide the odds in one group by the other

* Same rules apply as RR

Question 7

odds

Answer 7

Odds = probability/ 1-probability

Question 8

standard deviation (SD)

Answer 8

• Calculate difference between each value and the mean
• Square those values to make them all positive
• Add all those squared differences together
• Divide by the number of values
• Then square root the number
• It is affected by extreme values, but uses all values so more powerful, can be used if skewed data

Question 9

measures of spread

Answer 9

• Range
• inter-quartile range (more representative, representing middle 50% of the data, calculate 25th centile and 75th centile, associated with the median)
• standard deviation (average distance from mean for individual picked at random, measure of how spread out the values are, used for comparison)

Question 10

symmetric distribution

Answer 10

mean and SD

Question 11

non-symmetric distribution

Answer 11

median and IQR

Question 12

normal distribution

Answer 12

• Most people have values around the middle (mean) some with extremes but roughly the same on each side
• when we know the mean &SD, we can work out where a certain % of the sample are within
• Can use properties of normal distribution to create ‘normal ranges’ – where 95% of the data lie

Question 13

quantifying differences

Answer 13

• One numeric and one categoric variable
• Two numeric variables
• If we can use difference in means we do
• If any of groups not normally distributed, difference in medians
• Concluding whether that difference is big enough to be important

Question 14

comparing 2 numeric variables

Answer 14

• Pearson’s correlation coefficient (denoted r)
• R must be between -1 and +1
• +1 = perfect positive linear association
• -1 = perfect negative linear association
• 0= no linear relation at all