SantΓ© Publique Test

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SantΓ© Publique Test

 

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What is the statement of specificity of a diagnostic test:

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If an event has a probability of 0.1 it is:

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αžαžΎαž’αŸ’αžœαžΈαžαŸ’αž›αŸ‡αž‡αžΆαž•αŸ’αž“αŸ‚αž€αžšαž”αžŸαŸ‹ Descriptive statistics?

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The upper bound and lower bound of confidence interval are calculated using (chose the correct answer):

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The standard error of the mean of a sample is:

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In inferential statistics, we study

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What is the probability of getting an odd number when you roll a dice?

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What is the correct statement of validity of a screening test:

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The width of a confidence interval is influenced by:

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What is the statement of sensitivity of a diagnostic test:

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The branch of biostatistics that deals with testing of hypothesis, making predictions using data collected is called:

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A numerical value used as a summary measure for a sample, such as sample mean, is known as a

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On the statements below which are validstatements of probability:

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If a positive predictive value was 44%, it means that:

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On the statements below which are valid statements of probability:

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Which below statement is not correct:

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Which branch of statistics deals with the techniques that are used to organize, and summarize and simplify data:

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The Negative Predictive Value was 98% means that:

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If we want less chance of error we could calculate (chose the correct answer):

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In statistics, a population consists of

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A group of 100 people are asked to state their favourite colour. 60 say blue. This experiment says that the probability of someone choosing blue is:

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Which below statement is not correct:

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A screening test result for cervical cancer show that PPV= 67%. It means that:

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On the statements below what is valid statements of probability:

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If a specificity of a screening test was 89%, it means that:

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αžƒαŸ’αž›αžΆαžαžΆαž„αž€αŸ’αžšαŸ„αž˜αž“αŸαŸ‡αžŸαž»αž‘αŸ’αž’αžαŸ‚αžαŸ’αžšαžΉαž˜αžαŸ’αžšαžΌαžœ αž›αžΎαž€αž›αŸ‚αž„αžαŸ‚αŸ–

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Prevalence is useful in:

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αž“αŸ…αž€αŸ’αž“αž»αž„αžαŸαžαŸ’αžαž”αŸ‰αŸƒαž›αž·αž“αž˜αžΆαž“αž”αŸ’αžšαž‡αžΆαž‡αž“ ៦០០០០ αž“αžΆαž€αŸ‹ αž“αŸ…αžŠαžΎαž˜αž†αŸ’αž“αžΆαŸ† αŸ’αŸ αŸ‘αŸ€αŸ” αž‘αžΆαžšαž€αž€αžΎαžαžšαžŸαŸ‹αž€αŸ’αž“αž»αž„αž†αŸ’αž“αžΆαŸ†αž“αŸαŸ‡αž˜αžΆαž“ ្ៀ០០ αž“αžΆαž€αŸ‹αŸ” αž’αžαŸ’αžšαžΆαž‘αžΆαžšαž€αž€αžΎαžαžšαžŸαŸ‹αž€αŸ’αž“αž»αž„αž†αŸ’αž“αžΆαŸ†αž“αŸ„αŸ‡αž€αŸ’αž“αž»αž„αžαŸαžαŸ’αžαž”αŸ‰αŸƒαž›αž·αž“ αž˜αžΆαž“:

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All of them are the true answers only one is the false answer. Find the false answer: Defining disease occurrences: the method used to define cases affects the accuracy of frequency measures is:

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To measure risk of death among person in a specific age and sex group. by calculation of:

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The numerator of calculation neonatal mortality rate is:

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Proportion is the expression:

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αž‚αŸαž”αŸ’αžšαžΎαž”αŸ’αžšαžΆαžŸαŸ‹αž”αŸ’αžšαŸαžœαŸ‰αžΆαž‘αž„αŸ‹ (Prevalent) αžŠαžΎαž˜αŸ’αž”αžΈαž”αž„αŸ’αž αžΆαž‰:

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αž“αŸ…αž€αž˜αŸ’αž–αž»αž‡αžΆ αž’αžαŸ’αžšαžΆαž˜αžšαžŽαŸˆαž—αžΆαž–αžšαž”αžŸαŸ‹αž˜αžΆαžαžΆαž˜αžΆαž“ ៦០ αž—αžΆαž‚ ៑០០០ αž€αžΎαžαžšαžŸαŸ‹αž˜αžΆαž“αž“αŸαž™αžαžΆ:

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The use of a diagnostic test with a high false positive rate (poor specificity) will:

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αž’αŸŠαžΈαžŸαŸ’αžŠαžΌαž€αŸ’αžšαžΆαž˜ (Histogram) αž‚αžΊαž‡αžΆαž€αŸ’αžšαžΆαž αŸ’αžœαž·αž€αž˜αž½αž™:

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Neonatal mortality rate is used to measure the:

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αž’αžαŸ’αžšαžΆαž˜αžšαžŽαŸˆαž—αžΆαž–αž“αŸƒαž€αž»αž˜αžΆαžš (Infant mortality Rate, Taux de mortalitΓ© infantile) αž‚αžΊαž‡αžΆαž€αžΆαžšαž‚αžŽαž“αžΆαž’αžαŸ’αžšαžΆαž˜αžšαžŽαŸˆαž—αžΆαž–αžŸαŸ†αžŠαŸ…αž‘αŸ…αž›αžΎαž€αž»αž˜αžΆαžšαžŠαŸ‚αž›αž˜αžΆαž“αž’αžΆαž™αž»:

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αž’αžΆαŸ†αž„αžŸαŸŠαžΈαžŠαž„αŸ‹ αžαŸ’αžšαžΌαžœαž”αžΆαž“αž‚αžŽαž“αžΆαžŠαžΌαž…αžαž‘αŸ…:

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αž“αŸ…αž€αŸ’αž“αž»αž„αžαŸαžαŸ’αžαž”αŸ‰αŸƒαž›αž·αž“αž˜αžΆαž“αž”αŸ’αžšαž‡αžΆαž‡αž“ αŸ¦αŸ αŸ αŸ αŸ αž“αžΆαž€αŸ‹ αž“αŸ…αžŠαžΎαž˜αž†αŸ’αž“αžΆαŸ†αŸ’αŸ αŸ‘αŸ€αŸ” αž‘αžΆαžšαž€αž€αžΎαžαžšαžŸαŸ‹αž€αŸ’αž“αž»αž„αž†αŸ’αž“αžΆαŸ†αž“αŸ„αŸ‡αž˜αžΆαž“ αŸ’αŸ€αŸ αŸ αž“αžΆαž€αŸ‹αŸ” αž˜αžšαžŽαŸˆαž—αžΆαž–αž‘αžΌαž‘αŸ…αž˜αžΆαž“ αŸ¦αŸ αŸ αž“αžΆαž€αŸ‹ αž“αž·αž„αž”αŸ’αžš/αž‡αž…αž»αž„αž†αŸ’αž“αžΆαŸ†αž˜αžΆαž“:

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Bias due to sampling error is:

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To measure the risk of fetal death occurring after 28 completed weeks of gestation: by calculation of:

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αž“αŸ…αž€αž˜αŸ’αž–αž»αž‡αžΆ Taux de mortalitΓ© PΓ©rinatal, Perinatal Mortality Rate αž˜αžΆαž“ ៦០ αž—αžΆαž‚β€‹αŸ‘αŸ αŸ αŸ  αž€αžΎαžαžšαžŸαŸ‹αž€αŸ’αž“αž»αž„αž†αŸ’αž“αžΆαŸ† αŸ’αŸ αŸ αŸ αŸ” αž˜αžΆαž“αž“αŸαž™αžαžΆαž€αŸ’αž“αž»αž„αž€αŸ†αž‘αž»αž„αž†αŸ’αž“αžΆαŸ† αŸ’αŸ αŸ αŸ αŸ–

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This formula for calculated:

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The numerator of calculation maternal mortality rate (MMR) is:

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To measure the risk of dying within 28 days of birth, by calculation of:

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αž€αŸ’αž“αž»αž„αž…αŸ†αžŽαŸ„αž˜αž‘αžΆαžšαž€ ៑០០០ αž€αžΎαžαžšαžŸαŸ‹αž˜αžΆαž“αž˜αžΆαžαžΆαžŸαŸ’αž›αžΆαž”αŸ‹ ៦០ αž“αžΆαž€αŸ‹αž‘αžΆαž€αŸ‹αž‘αž„αž€αžΆαžšαž˜αžΆαž“αž•αŸ’αž‘αŸƒαž–αŸ„αŸ‡ αž“αž·αž„ αž†αŸ’αž›αž„αž‘αž“αŸ’αž›αŸ αžŸαž»αž…αŸ’αž…αž“αžΆαž€αžšαž“αŸαŸ‡αž”αž‰αŸ’αž‡αžΆαž€αŸ‹αž€αžΆαžšαž‚αžŽαž“αžΆ:

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The mean population in Rattanakiri province is 30000 populations (P) in year 2005.All cases of mortality is 200 cases. # Live births = 1500 live births. Infant death under 1 year have 90 cases. # Live births of infant < 28 days of age = 200 Live births. Neonatal mortality = 45 cases and Maternal mortality = 50 deaths. Maternal mortality rate is:

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The categories of variable show that Male, Female and Blood type: type A, type B, type O, type AB is the type of:

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αž“αŸ…αž€αŸ’αž“αž»αž„αžαŸαžαŸ’αžαž”αŸ‰αŸƒαž›αž·αž“αž˜αžΆαž“αž”αŸ’αžšαž‡αžΆαž‡αž“ αž˜αž’αŸ’αž™αž˜ ៦០០០០ αž“αžΆαž€αŸ‹ αž˜αžΆαž“αž‡αŸ†αž„αžΊαžšαž”αŸαž„αžŸαž€αž˜αŸ’αž˜αž—αžΆαž–αž€αžΎαžαžαŸ’αž˜αžΈαžαŸ’αžšαžΌαžœαž”αžΆαž“αžšαž€αžƒαžΎαž‰αž“αŸ…αž€αŸ†αž‘αž»αž„αž†αŸ’αž“αžΆαŸ† αŸ’αŸ αŸ‘αŸ€αž˜αžΆαž“αž…αŸ†αž“αž½αž“ ៦០ αž“αžΆαž€αŸ‹, αž‡αŸ†αž„αžΊαžšαž”αŸαž„αžŸαž€αž˜αžŸαž›αŸ‹αž–αžΈαž†αŸ’αž“αžΆαŸ†αž…αžΆαžŸαŸ‹ (្០៑៣) αž˜αžΆαž“αž…αŸ†αž“αž½αž“ ្០ αž“αžΆαž€αŸ‹ αž αžΎαž™αžˆαžΊαž”αž“αŸ’αžŠαžŠαž›αŸ‹αž…αž»αž„αž†αŸ’αž“αžΆαŸ† αŸ’αŸ αŸ‘αŸ€αŸ” αž’αžαŸ’αžšαžΆαž’αžΆαŸ†αž„αžŸαŸŠαžΈαžŠαž„αŸ‹αž‡/αž„ αžšαž”αŸαž„αž‚αžΊ:

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Variation in clinical measurement including:

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The numerator of calculation age- and sex specific death rate is:

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αž’αžΆαŸ†αž„αžŸαŸŠαžΈαžŠαž„αŸ‹αž€αžΎαž“αž‘αžΎαž„αž€αŸ’αž“αž»αž„αž€αžšαžŽαžΈ:

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αž€αŸ’αž“αž»αž„αž…αŸ†αžŽαŸ„αž˜αž‘αžΆαžšαž€ ៑០០០ αž€αžΎαžαžšαž„αžŸαŸ‹ αž˜αžΆαž“αž‘αžΆαžšαž€αžŸαŸ’αž›αžΆαž”αŸ‹ ៦០ αž“αžΆαž€αŸ‹ αž’αžΆαž™αž»αž€αŸ’αžšαŸ„αž˜ ្៨ αžαŸ’αž„αŸƒ αžŸαž»αž…αŸ’αž…αž“αžΆαž€αžšαž“αŸαŸ‡αž”αž‰αŸ’αž‡αžΆαž€αŸ‹ αž€αžΆαžšαž‚αžŽαž“αžΆαŸ–

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In an epidemic ( or outbreak ) of food poisoning, there were 10 cases of male and 40 cases of female among 120 female and 80 male exposed. Female attack rate is:

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Properties and uses of the median. The median is / has:

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Ratio expresses the relationship between:

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αž€αžΆαžšαžŸαž·αž€αŸ’αžŸαžΆαž‘αŸ…αž›αžΎαžŸαŸ†αžŽαžΆαž€αž“αŸƒαž“αž·αžŸαŸ’αžŸαž·αžαž†αŸ’αž“αžΆαŸ†αž‘αžΈαŸ’B αž…αŸ†αž“αž½αž“αŸ‘αŸ₯αž“αžΆαž€αŸ‹ αžšαž€αžƒαžΎαž‰αžαžΆαž“αž·αžŸαŸ’αžŸαž·αžαž”αžΆαž“αž…αŸ†αžŽαžΆαž™αž–αŸαž›αžŸαž·αž€αŸ’αžŸαžΆαž“αŸ…αž”αžŽαŸ’αžŽαžΆαž›αŸαž™αž‡αžΆαž˜αž’αŸ’αž™αž˜ 50 αž“αžΆαž‘αžΈ αž€αŸ’αž“αž»αž„αŸ‘ αžαŸ’αž„αŸƒαŸ” αž‚αŸαž…αž„αŸ‹αž’αŸ’αžœαžΎ hypothesis testing αžŠαŸ„αž™αžŸαžšαžŸαŸαžαžΆ H0: αžšαž™αŸ‡αž–αŸαž›αžŸαž·αž€αŸ’αžŸαžΆαž€αŸ’αž“αž»αž„αž”αžŽαŸ’αžŽαžΆαž›αŸαž™αžŸαŸ’αž˜αžΎ αŸ¦αŸ αž“αžΆαž‘αžΈ αž“αž·αž„ Ha: αžšαž™αŸ‡αž–αŸαž›αžŸαž·αž€αŸ’αžŸαžΆαž€αŸ’αž“αž»αž„αž”αžŽαŸ’αžŽαžΆαž›αŸαž™ β‰  αŸ¦αŸ αž“αžΆαž‘αžΈαŸ” αž€αžΆαžšαž’αŸ’αžœαžΎαžαŸαžŸαŸ’αžαž”αŸ‚αž”αž“αŸαŸ‡αž‡αžΆαž”αŸ’αžšαž—αŸαž‘

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αž€αžΆαžšαžŸαž·αž€αŸ’αžŸαžΆαž‘αŸ…αž›αžΎαžŸαŸ†αžŽαžΆαž€αž“αŸƒαž“αž·αžŸαŸ’αžŸαž·αžαž†αŸ’αž“αžΆαŸ†αž‘αžΈαŸ’A αž…αŸ†αž“αž½αž“αŸ‘αŸ₯αž“αžΆαž€αŸ‹ αžšαž€αžƒαžΎαž‰αžαžΆαž“αž·αžŸαŸ’αžŸαž·αžαž”αžΆαž“αž…αŸ†αžŽαžΆαž™αž–αŸαž›αžŸαž·αž€αŸ’αžŸαžΆαž“αŸ…αž•αŸ’αž‘αŸ‡αžšαž™αŸˆαž–αŸαž›αž˜αž’αŸ’αž™αž˜ αŸ‘αŸ’αŸ αž“αžΆαž‘αžΈβ€‹ αž€αŸ’αž“αž»αž„αŸ‘β€‹ αžαŸ’αž„αŸƒ αž αžΎαž™αž˜αžΆαž“ standard deviation αŸ¦αŸ αž“αžΆαž‘αžΈ αž αžΎαž™αž€αžΆαžšαžŸαž·αž€αŸ’αžŸαžΆαž‘αŸ…αž›αžΎαžŸαŸ†αžŽαžΆαž€αž“αž·αžŸαŸ’αžŸαž·αžαž†αŸ’αž“αžΆαŸ†αž‘αžΈ ្Cαž…αŸ†αž“αž½αž“ αŸ‘αŸ‘αž“αžΆαž€αŸ‹αž”αžΆαž“αžšαž€αžƒαžΎαž‰αžαžΆαž“αž·αžŸαŸ’αžŸαž·αžαž”αžΆαž“αž…αŸ†αžŽαžΆαž™αž–αŸαž›αžŸαž·αž€αŸ’αžŸαžΆαžšαž™αŸˆαž–αŸαž› αŸ‘αŸ αŸ αž“αžΆαž‘αžΈαž€αŸ’αž“αž»αž„αŸ‘αžαŸ’αž„αŸƒαž αžΎαž™αž˜αžΆαž“ standard
deviation 20 αž“αžΆαž‘αžΈαŸ”αž‚αŸαž…αž„αŸ‹αž”αŸ’αžšαŸ€αž”αž’αŸ€αž”αžαžΆαžαžΎαž“αž·αžŸαŸ’αžŸαž·αžαž†αŸ’αž“αžΆαŸ†αž‘αžΈ ្A αž“αž·αž„ 2 B αž”αžΆαž“αž…αŸ†αžŽαžΆαž™αž–αŸαž›αžŸαž·αž€αŸ’αžŸαžΆαžŸαŸ’αž˜αžΎαžšαž‚αŸ’αž“αžΆαžŠαŸ‚αžšαž¬αž‘αŸ αžαžΎαž‚αŸαžαŸ’αžšαžΌαžœαž’αŸ’αžœαžΎ hypothesis testing αž”αŸ’αžšαž—αŸαž‘αžŽαžΆ?

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αžαžΎαž’αŸ’αžœαžΈαžαŸ’αž›αŸ‡αž‡αžΆαž•αŸ’αž“αŸ‚αž€αžšαž”αžŸαŸ‹Descriptive statistics?

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