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 Home > topics> Biostatistics Email this page
Biostatistics High Yield Notes
Biostatistics Section - Biostatistics MCQ Bank Forum - Biostatistics Books


Conception of Variables in Biostatistics
by shuvo - 7838 reads, based on 4 votes
Characteristics which show variability or variation are known as variable. eg. Height, WBC count, sex, religion, vomiting episodes etc.... More

Z-test : A Brief Overview
by - 2902 reads, based on 5 votes
In some situations the sequence of steps used in t-test can be done using z-scores instead of t-scores. Then such a test is called z-test. Use: z-test is/can be used in place of t-test when • The population standard deviation is known which allows the standard error, rather than the estimated SE to be found • The sample is sufficiently large (n > 200) for the SD to provide a reliable estimate of SE.... More

All the Biostatistics notes you will need for a quick revision
by willpower - 4249 reads, based on 15 votes
BIOSTATISTICS NOTES POPULATION: Universe of all units being studied. If we want to study lung cancer among Indians, then the study population will be all Indians. If we want to study lung cancer among Indian women, then the population will be all Indian women. SAMPLE: Subset of the population RANDOM SAMPLE: Each member of the population has an EQUAL CHANCE of being chosen for the sample ... More

Principles of Diagnostic Tests
by akil - 1799 reads, based on 4 votes
A summary of diagnostic tests principles! Test Positive or Negative The definition of normal for continuous variables is a statistical determination At what point "abnormal" becomes an illness or disease is a judgment based upon the desire to identify those with disease (true positives), but not include a significant portion of patients without the disease (false positives). Furthermore, most tests are not positive in all the patients with a given disease, so there will be patients with the disease who are missed by the test (false negatives). Finally, we want to be sure that a very high proportion of patients who don't have the disease, have a negative test (true negatives). ... More


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