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UNIT 1 Flashcards

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1
Q

it is the science that deals with the collection, organization, analysis and interpretation of numerical data

A

Statistics

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2
Q

T/F Biostatistics is a statistical science to analyze public health problems and further biomedical research

A

True

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3
Q

tendency of measurable characteristics to change with respect to person, place and time

A

Variation

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4
Q

T/F It is not necessary to analyze variability in order to describe certain characteristics or make valid conclusions

A

False

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5
Q

Give the roles of statistics in research

A
  1. Design a research project
  2. Processing, organizing, and summarizing research data
  3. Quantifying variability
  4. Interpreting results and drawing valid conclusions
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6
Q

T/F Statistics helps in quantifying variability and designing a research project

A

True

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7
Q

all subjects or samples of interest

A

Population

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8
Q

selected subjects / samples of interest

A

Samples

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9
Q

Difference between Population and Samples

A

Population - ALL subjects/samples; result = parameter

Samples - SELECTED subjects/samples; result = statistics

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10
Q

It is the estimate of the parameter

A

Statistics

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11
Q

Characteristics of interest to be measured

A

Variable

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12
Q

Fixed Variable

A

Constants

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13
Q

T/F The result of the population is called statistics while the result of the sample is called parameter.

A

False

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14
Q

act of studying or examining only a segment of population to represent the whole

A

Sampling

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15
Q

T/F Whatever findings we obtain from the sample, we do not generalize to the total population.

A

False

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16
Q

Modified T/F

Sampling is important because more comprehensive data is collected. Due to this, detailed procedures are best done only on larger groups

A

T,F

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17
Q

Modified T/F

One importance of sampling is that the information collected is of better quality. This is because there are fewer data collectors which allows them to have more rigid training and supervision.

A

T,T

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18
Q

Modified T/F

Sampling is more ethical in intervention studies. With larger study groups, the probability of exposing individuals to potentially useless or harmful intervention is less.

A

T,F

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19
Q

The entire group of individuals or items of interest in the study.

a. Population
b. Target Population
c. Sampling Population

A

Population

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20
Q

The group from which representative information is desired, and to which inferences will be made.

a. Population
b. Target Population
c. Sampling Population

A

Target Population

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21
Q

Population from which a sample will actually be taken.

a. Population
b. Target Population
c. Sampling Population

A

Sampling Population

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22
Q

T/F Sometimes the Target Population = Sampling Population

A

True

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23
Q

T/F The target population is not considered as the sampling population because of the unavailability of information for sampling purposes.

A

True

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24
Q

T/F The target population is not considered as the sampling population because of the inaccessibility of the target population.

A

True

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25
Units chosen in selecting the sample, and may be made up of non-overlapping collection of elements
Sampling Unit
26
Person or object on which measurement is actually taken, or an observation is made
Elementary Unit or Element
27
Determine the sampling unit and element : To determine the prevalence of asthma in first year college students
Sampling unit - school Element - all the first year students
28
It is the collection of sampling units.
Sampling Frame
29
T/F The availability of the sampling frame determines whether or not there is a gap between the target and sampling population.
True
30
It is the difference between the value of the parameter and estimates of this values based on different samples
Sampling Error
31
T/F In creating a good sampling design, the sample should be a representative of the population.
True
32
T/F In creating a good sampling design, the sample size should be adequate.
True
33
T/F In creating a good sampling design, the sampling procedure should be expensive but feasible.
False
34
T/F In creating a good sampling design, the sampling design should be economical and efficient.
True
35
The following are factors to consider in selecting a sample design except : a. Nature of the variables b. Statistics of the study c. Population being studied d. Purpose for which the research undertaken e. Availability of information relevant to sampling procedure
b. Statistics of the study
36
Two categories of sampling designs
Non-probability and Probability
37
It is a type of non-probability sampling that occurs when a sample is selected based on an expert's subjective judgement or on some pre-specified criteria.
Judgement or Purposive Sampling
38
This type of non-probability sampling selects study areas based on proximity.
Judgement or Purposive Sampling
39
It is a type of non-probability sampling that selects samples based on whatever items come first or whoever is available.
Accidental or Haphazard Sampling
40
Determine which type of non-probability sampling : Person-on-street sampling and Ambush interviews
Accidental or Haphazard Sampling
41
It is a type of non-probability sampling that involves the selection of items or individuals to include in the sample takes place until a pre-specified number (quota) is reached.
Quota sampling
42
Determine which type of non-probability sampling : Patient satisfaction surveys
Quota sampling
43
It is a type of non-probability sampling that is frequently used when studying hidden populations.
Snowball Technique
44
T/F Snowball technique is devised because of the difficulty producing the sampling frame and in identifying members of these populations.
True
45
It is the most basic type of probability sampling.
Simple Random Sampling
46
It is a type of probability sampling in which every element in the population has an equal chance of being included in the sample.
Simple Random Sampling
47
It is a variation of simple random sampling.
Systematic Sampling
48
This probability sampling design is used when sampling units are too numerous to list for purposes of simple random sampling.
Systematic Sampling
49
It is a type of probability sampling that involved dividing the population first into overlapping groups. (Strata)
Stratified Random Sampling
50
This probability sampling design increases the precision of estimates of parameters being considered.
Stratified Random Sampling
50
It is a type of probability sampling where sampling units are clusters of elements.
Cluster Sampling
51
This probability sampling design is used when sampling frame for elements is not readily available.
Cluster Sampling
52
It is a type of probability sampling that is appropriate for sample surveys that have a wide coverage.
Multi-stage Sampling
53
It is an experimental study design wherein samples or subjects are assigned randomly to groups to study the effects of one primary factor.
Completely Randomized Design / Randomized Controlled Trial
54
It is an experimental study design wherein samples or subjects are assigned randomly to groups to study the effects of two or more factors.
Factorial Design
55
It is an experimental study design wherein samples or subjects are assigned randomly to groups to study the effects of one primary factor across time.
Repeated Measure Design
56
It is a type of observational study design that involves the collection of data on the study participants' current status at one point in time.
Cross-Sectional
57
It is a type of observational study design that involves the collection of data about the study participants' current outcome status and past exposure status.
Case-Control
58
It is a type of observational study design that involves the collection of data at more than one point in time, following the participants forward to identify the outcomes.
Cohort
59
Enumerate the three observational study designs
1. Cross Sectional 2. Case-Control 3. Cohort
60
Enumerate the three experimental study design
1. Completely Randomized Design/Randomized Controlled Trial 2. Factorial Design 3. Repeated Measure Design
61
Enumerate the five probability sampling designs
1. Simple Random Sampling 2. Systematic Sampling 3. Stratified Random Sampling 4. Cluster Sampling 5. Multi-stage Sampling
62
Enumerate the four non-probability sampling designs
1. Judgement or Purposive Sampling 2. Accidental or Haphazard Sampling 3. Quota Sampling 4. Snowball Technique

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