Statistics Flashcards
What do the bottom and top represent on the box-and-whisker plot?
Lower and upper quartile
What type of variable is BMI ?
Continuous
How to calculate standard error of the mean?
SEM = SD/√n
In statistics population consists of
all subjects or objects whose characteristics are being studied
for a negatively skewed data, mean will be
mean < median < mode
for a Postively skewed data, mean will be
mean > median > mode
Axises of ROC curve
Sensitivity/ (1-Specificty)
Standard deviation:
Square root of Variance
The ability of a test to correctly identify those who have the disease
Sensitivity
The proportion of well people who are correctly classified by the screening test as negative
Specificity
The proportion of people with a positive screening test who are diseased.
Positive Predictive value (PPV)
The proportion of people with a negative screening test who are well.
Negative predictive value (PPV)
Formula of PPV
All the positives
TP/TP+FP
Formula of NPV
All the Negatives
TN/TN+FN
Formula of sensitivity
TP/TP+FN
Formula of Specificity
TN/TN+FP
to know the number of occurrences of an event at any given interval.
Poisson Distribution
What is Variance?
measures the degree of spread (dispersion) in a variables value
FORMULA: V= ( SD2)
Standard Deviation
measure of how spread out the numbers are from the mean
FORMULA: SD = √ Variance
Interquartile Range
dividing data set into quartiles and getting the midspread or middle 50%
FORMULA : IQR= Q3-Q1
Standard error of the mean SEM:
is an estimate of how far the sample mean is likely to be from the population mean
FORMULA: SEM = SD/ √n
Significant level α
is the probability of the study rejecting the null hypothesis, given that the null-hypothesis is true.
Significance level is set at α= 0.05 or 5%
Significant P value: Probability value (probability of chance)
any number between 0 to 1
the lower the p value the more statistically significant the study is.
Low p-value < 0.05 indicates
strong evidence against the null hypothesis. So your study can REJECT the null hypothesis.