Bistatistics Flashcards
Statistics
The science dealing with the systematic gathering and analysis of data in medical forms
Bistatistics
Applications of statistics in biology, Medicine, and public health
Dichotomous
Two categories Example: Affected (positive) unaffected (Negative) Also known as binary
Ordinal
3 or more ranked categories Normal affected (high) severely affected (very high)
Nominal
Qualitative eye color, blood groups
Quantitative
Interval, ration
Pearson test
Two intervals Is there a linear relationship? -1< r < 1 spearman correlation compares two ordinal variables
Chi-square
2 nominal any number of groups
T-test
1 interval, 1 nominal 2 groups
One way Anova
1 interval, 1 nominal 2 or more groups, F-Statistic
Match pairs t-test
1 interval, 1 nominal 2 groups, linked data pairs
Repeated measures Anova
1 interval, 1 nominal more than 2 groups, linked data, F-statisitc
Standar deviation
Population mean = mu, sd = sigma, variance = sigma squared Sample X, sd, variance = s squared
Sample variance
s(squared) = 1/(n-1) * sum (Xi-X)squared
Standard Variable (Z)
measures the deviation of X from the mean in terms of standard deviation Population Z = X-mu/sigma Sample Z= X-Xmean/s
Frequency distribution
Qualitative or discrete: Bar Quantitative discrete: Bar, pie Continuous: Histogram, Bar Chart Tren: Quantitative: Line
Probability (Mutually Exclusive)
Combine probabilities for mutual exclusive events by addition
If two evens are not mutually exclusive
Combination of probabilities is accomplished by adding the two together and subtracting out the multiplied probabilities
Combined probabilities for independent events by multiplication
Events are independent if the occurrence of one tells you nothing about the occurrence of another. The issue here is the intersection of two sets.
if events are dependent
Multiply the probability of one event by the probability of the second, assuming that the first has occurred
