SantΓ© Publique Test

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SantΓ© Publique Test

 

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Which answer below is not correct about the confidence interval:

2 / 60

If an event has a probability of 0.1 it is:

3 / 60

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

4 / 60

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

5 / 60

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

6 / 60

When the new drug was clinically tested, 117 patients reported headaches and 617 did not. Based on this sample what is the probability that a new drug user will experience a headache:

7 / 60

In statistics, a sample mean:

8 / 60

A positive predictive value depend on:

9 / 60

In inferential statistics, we study

10 / 60

Which statement is not true about confidence intervals?

11 / 60

On the statements below what is valid statements of probability:

12 / 60

A population parameter is likely to occur (chose the correct answer):

13 / 60

Population census is conducted through

14 / 60

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

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Reliability of a test means that:

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The Positive Predictive Value depends on:

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If an event is impossible it has a probability of:

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On the statements below what is valid statements of probability:

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What is the correct statement of screening test:

20 / 60

Below is the common screening test except one:

21 / 60

ΞΌ is an example of a

22 / 60

On the statements below which are valid statements of probability:

23 / 60

In a study of Cambodian people over 65 years of age, it is found that 255 have heart disease and 2302 do not. If a Cambodian over 65 years of age is randomly selected, what is the estimated probability that he or she has heart disease:

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If a negative predictive value was 98%, it means that:

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What is the correct answer about a confidence interval statement:

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Which below statement is not correct:

27 / 60

Which of the following statements is true about the standard error of a proportion?

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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™αŸ‡αž–αŸαž›αž˜αž’αŸ’αž™αž˜ αŸ‘αŸ’αŸ αž“αžΆαž‘αžΈ αž€αŸ’αž“αž»αž„αŸ‘ 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“ ៑៑ 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’αŸ’αžœαžΎαžαŸαžŸαŸ’αžαž…αž„αŸ‹αžŠαžΉαž„αžαžΆαžαžΎαžšαž™αŸ‡αž–αŸαž›αžŸαž·αž€αŸ’αžŸαžΆαžšαž”αžŸαŸ‹αžαŸ’αž“αžΆαž€αŸ‹αž‘αžΆαŸ†αž„αž–αžΈαžŸαŸ’αž˜αžΎαžšαž‚αŸ’αž“αžΆαžŠαŸ‚αžšαž¬αž‘αŸ αž αžΎαž™αž‘αž‘αž½αž›αž”αžΆαž“ P-value αžšαž”αžŸαŸ‹αžαŸαžŸαŸ’αžαžŸαŸ’αž˜αžΎ αŸ₯%αŸ” αž™αŸ„αž„αžαžΆαž˜αž›αž‘αŸ’αž‹αž•αž›αž“αŸαŸ‡αž‚αŸαž’αžΆαž…αžŸαž“αŸ’αž“αž·αžŠαŸ’αž‹αžΆαž“αžαžΆ

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αž€αžΆαžšαžŸαž·αž€αŸ’αžŸαžΆαž‘αŸ…αž›αžΎαžŸαŸ†αžŽαžΆαž€αž“αŸƒαž“αž·αžŸαŸ’αžŸαž·αžαž†αŸ’αž“αžΆαŸ†αž‘αžΈ ្Aαž…αŸ†αž“αž½αž“ ៑៑ 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›β€‹ 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’αžœαžΎ hypothesis testing αžαžΆαž“αž·αžŸαŸ’αžŸαž·αžαž†αŸ’αž“αžΆαŸ†αž‘αžΈ ្ αž”αžΆαž“αž…αŸ†αžŽαžΆαž™αž–αŸαž›αžšαŸ€αž“αžšαž™αŸˆαž–αŸαž› αŸ’αž˜αŸ‰αŸ„αž„ αŸ” αžαžΎαž‚αŸαžαŸ’αžšαžΌαžœαžŸαžšαžŸαŸαžš Hypothesis αž™αŸ‰αžΆαž„αžŠαžΌαž…αž˜αŸ’αžαŸαž…?

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αžŸαŸ’αžαž·αžαž·αžœαž·αž‘αŸ’αž™αžΆ(statistics) αž˜αžΆαž“αž…αŸ‚αž€αž…αŸαž‰αž‡αžΆ

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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˜ αŸ¦αŸ αž“αžΆαž‘αžΈ αž€αŸ’αž“αž»αž„αŸ‘ αžαŸ’αž„αŸƒ αž αžΎαž™αž˜αžΆαž“standard deviation αŸ€αŸ αž“αžΆαž‘αžΈαŸ”αž‚αŸαž’αžΆαž…αž”αŸ’αžšαžΎ point estimation αžŠαžΎαž˜αŸ’αž”αžΈαž’αŸ’αžœαžΎαž€αžΆαžšαžŸαž“αŸ’αž“αž·αžŠαŸ’αž‹αžΆαž“αžαžΆ

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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™αŸ‡αž–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 ្C αž…αŸ†αž“αž½αž“ ៑៑ αž“αžΆαž€αŸ‹αž”αžΆαž“αžšαž€αžƒαžΎαž‰αžαžΆαž“αž·αžŸαŸ’αžŸαž·αžαž”αžΆαž…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αžΆαž˜αž€αžΆαžšαž–αž·αž“αž·αžαŸ’αž™αž˜αžΎαž›αž‘αŸ…αž›αžΎαž€αžΆαžšαžšαž€αžƒαžΎαž‰αž€αŸ’αž“αž»αž„αžŸαŸ†αžŽαžΆαž€αž‘αžΆαŸ†αžΆαž„αž–αžΈαžšαž“αŸαŸ‡ αž™αžΎαž„αž’αžΆαž…αžŸαž“αŸ’αž“αž·αžŠαŸ’αž‹αžΆαž“αž”αžΆαž“αžαžΆ

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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™αž˜αžΆαž“ H0: αžšαž™αŸ‡αž–αŸαž›αžŸαž·αž€αŸ’αžŸαžΆαž€αŸ’αž“αž»αž„αž”αžŽαŸ’αžŽαžΆαž›αŸαž™β‰₯ 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™ < 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αžΎαž’αŸ’αžœαžΈαžαŸ’αž›αŸ‡αž‡αžΆαž•αŸ’αž“αŸ‚αž€αžšαž”αžŸαŸ‹Descriptive statistics?

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αž˜αžΆαž“αž’αŸ’αž“αž€αž‡αŸ†αž„αžΊαž…αŸ†αž“αž½αž“αŸ₯αž“αžΆαž€αŸ‹αž˜αž€αžŸαŸ†αžšαžΆαž€αž“αŸ…αž€αŸ’αž“αž»αž„αž˜αž“αŸ’αž‘αžΈαžšαž–αŸαž‘αŸ’αž™αžŠαŸ„αž™ αž‡αŸ†αž„αžΊαž‚αŸ’αžšαž»αž“αž–αŸ„αŸ‡αžœαŸ€αž“ αžšαž™αŸˆαž–αŸ’αž™αžΆαž”αžΆαž›αž‚αž·αžαž‡αžΆαžαŸ’αž„αŸƒαž˜αžΆαž“αžšαž™αŸˆαž–αŸαž›αžŠαžΌαž…αžαž‘αŸ…: ្, ៣, ្, αŸ₯, αŸ£αŸ” αžαž˜αŸ’αž›αŸƒαž‚αŸ†αž›αžΆαžαžŸαŸ’αžŠαž„αŸ‹αžŠαžΆ (Standard Deviation) αž‚αžΊ:

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The numerator of calculation perinatal mortality rate is:

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The estimated mid interval population is determined by:

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αž“αŸαŸ‡αž‡αžΆαž…αŸ†αž„αžΆαž™αž•αŸ’αž›αžΌαžœαž‚αž·αžαž‡αžΆαž‚αžΈαž‘αžΌαž˜αŸ‰αŸ‚αžαŸ’αžšαž–αžΈαž•αŸ’αž‘αŸ‡αžšαž”αžŸαŸ‹αž’αŸ’αž“αž€αž‡αŸ†αž„αžΊ αŸ¦αž“αžΆαž€αŸ‹αž˜αž€αž˜αžŽαŸ’αžŒαž›αžŸαž»αžαž—αžΆαž–αž˜αž½αž™: 4,7,3,5,3,8αŸ” αž”αŸ’αžšαžŸαž·αž“αž”αžΎ 8 αžαŸ’αžšαžΌαžœαž”αžΆαž“αž‚αŸαž€αžαŸ‹αž…αŸ’αžšαž‘αŸ†αž‡αžΆ 80 αžœαž·αž‰ αžαžΎαž“αžΉαž„αž˜αžΆαž“αž€αžΆαžšαž”αŸ’αžšαŸ‚αž”αŸ’αžšαž½αž›αž’αŸ’αžœαžΈαž€αžΎαžαž‘αžΎαž„?

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True biologic variation in clinical measurement is the sum:

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Evaluating accuracy: The accuracy of a set of clinical measurements is determined by comparing the true underlying value of the variable with the:

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Neonatal mortality rate is used to measure the:

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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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Proportion is the expression:

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A high prevalence may be due to:

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The numerator of calculation infant mortality rate is:

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

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The inclusion of only “classic” cases of the disease, as defined by strict diagnostic criteria, will:

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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 under 1 year = 1500 live births. Infant death under 1 year has 90 cases. # Live births of infant < 28 days of age = 200 Live births. Neonatal mortality = 45 cases and Maternal mortality = 50 deaths. Crude death rate is:

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Add all of the observed values in the distribution and divide the sum by the number of observations is the formula for calculate the:

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The numerator of calculation Crude death rate (CDR) is:

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Prevalence is useful in:

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To measure the average risk of death in the population at large, by calculation of:

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Definition of median, Median is:

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Qualitative variables are measured at the:

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The scale uses names, numbers or other symbols to assign each measurement to one of a limit number of categories that cannot be ordered one above the other is:

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In epidemiological practice, incidence rate are:

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

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

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

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Variation in clinical measurement including:

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