Discrete categories
No sense of order or importance
Example: blood type
Present percentages of each category (pie or bar chart)
Ordinal Data
Natural sense of order
Distance between groups isn’t meaningful
Example- frequency of sleeping (never, sometimes, always etc.)
Use median (n+1/2)
Spilt into quartiles (1st=25% AND 3RD= 75%)
Use mode to show most frequent
Use bimodal if two main peaks shown in data
Scale/Interval/Continuous Data
Meaningful in order and difference
Example (temperature or weight)
Ratio is used to describe when 0 is meaningful (can have less than 0)
Use when data is symmetrical (histogram)
Can use median or mode
Mainly use mean Σx/n
Describe spread using standard deviation (great SD= more spread)
SD= Σ(x-m)2/n-1
m= mean
SD= root of variance
Symmetrical Data
95.2% of data within ±2SDs when data is normal
68.3% within 1SD and 99.7% in 3SDs
Presented as Mean (SD)= 100 (10)
Standard Error and Confidence Intervals
Standard error of the mean (SEM)= SD/√n
95% CI= SEMx1.96 then ± of the mean
If CI overlap then they likely came from the same population
Nominal Data
Standard error of a proportion (SE)= ((p(1-p)/n)
Example- 80%=0.8
(0.8(1-0.8)/n)
Then 1.96xSE then ± the mean
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