1
Q
an act of studying or examining only a segment of the population to represent the whole
A
Sampling
2
Q
T or F
Sampling is only a segment of a WHOLE BUNCH?
A
True
3
Q
Advantages of Sampling
A
- Cheaper
- Faster
- Better quality of Information
- Obtain more comprehensive data
- The only possible method for destructive procedures
4
Q
refers to the entire group of individuals of items of interest in the study
A
Population
5
Q
the group from which representative information is desired and to which inferences will be made.
A
Target Population
6
Q
The population from which a sample will actually be taken
A
Sampling Population
7
Q
A list of all the items in your population
A
Sampling Frame
8
Q
It is a complete list of everyone or everything you want to study
A
Sampling Frame
9
Q
T or F
The difference between a population and a sampling frame is that the population is general and the frame is specific.
A
T
10
Q
an object or a person on which a measurement is actually taken, or an observation is made
A
Elementary Unit or Element
11
Q
the difference between the value of the parameter being estimated and the estimate of this value based on the different samples
A
Sampling Error
12
Q
The sample to be obtained should be
_________________ of the population
A
Representative
13
Q
T or F
The sample size should be adequate
A
True
14
Q
T or F
Practicality and Feasibility of the sampling procedure is not a criteria of a good sampling design
A
F
15
Q
Economy and efficiency of the sampling Design is considered?
A
T. it should effective and attained in the shortest amount of time
16
Q
T or F
There are a number of basic sampling designs that a researcher can choose from
A
T
17
Q
Familiarize the specific design that is best for a particular study
A
- nature of the variables
- population being studied
- purpose for which the research is undertaken
- availability of information relevant to the sampling procedure itself (e.g. sampling frame)
18
Q
what are the 2 types of Basic Sampling Designs?
A
- Probability sampling design
- Non-probability sampling designs
19
Q
What are the sampling under NON PROBABILITY?
A
- Judgment or purposive sampling
- Accident or haphazard sampling
- Quota sampling
- Snowball technique sampling
20
Q
The probability of each member of the population to be selected in the sample is difficult to determine or cannot be specified
A
Non-probability sampling design
21
Q
- Researchers select the samples based purely on the researcher’s knowledge and credibility.
- Choose only those people who they deem fit to participate in the research study
- Not a scientific method of sampling
A
Judgment or Purposive sampling
22
Q
What are the Downside of Judgmental or Purposive Sampling?
A
the preconceived notions of the researcher can influence the results, thus involving a high amount of ambiguity
23
Q
- a sampling method that does not follow any systematic way of selecting participants.
- Example: standing on a busy corner during rush hour and interviewing people who pass by.
A
Accident or Haphazard Sampling
24
Q
population is divided into subgroups or strata based on certain characteristics, and then participants are selected from each subgroup in proportion to the overall population distribution of those characteristics
A
Quota Sampling (def is from chat gpt)
25
If you see this card
Study how QUOTA SAMPLING work, its tad complicated
26
- Researchers use this technique when the sample size is small and not easily available.
- This sampling system works like the referral program.
Snowball sampling
27
Snowball sampling helps researchers find a
sample when they are difficult to locate, how?
The participants REFERS OTHER PEOPLE!!
28
Once the researchers find suitable subjects, he asks them for assistance to seek similar subjects to form a considerably good size sample.
Snowball Sampling
29
* Samples are selected from the population only because they are conveniently available to the researcher
* Researchers choose these samples just because they are easy to recruit, and the researcher did not consider selecting a sample that represents the entire population.
Convenience sampling
30
Why researchers considers convenience sampling as their sampling methods?
speed, cost-effectiveness, and ease of availability of the sample.
31
* Very similar to convenience sampling, with a
slight variation.
* The researcher picks a single person or a group of a sample, conducts research over a period, analyzes the results, and then moves on to another subject or group if needed.
Consecutive Samping
32
T or F
Consecutive sampling technique gives the researcher a chance to work with LEAST topics and fine-tune his/her research by collecting results that have vital insights.
F (many)
33
How consecutive sampling is used, and what kind of research it is best suited? (accrding to prof. sonny angels)
- Revise ng unti yung questionnaire then next sample
- QUALITATIVE RESEARCHES
34
The rules and procedures for selecting the
sample and estimating the parameters are
explicitly and rigidly specified
Probability Sampling Designs
35
Each unit in the population has a known non- zero chance of being included in the sample.
Probability Sampling Designs
36
* The most basic type
* It's main characteristic is that every element in the population has an equal chance of being included in the sample
* Used in studies involving relatively small populations within readily available sampling frame.
Simple Random Sampling
37
Nakita mo tong card baliew, so
Familiarize yourself with the procedure of Simple Random Sampling
38
What are the advantages of simple random sampling?
- Drawing the Sample is easy
- Analysis of data are simple and easy
39
What are the disadvantages of simple random sampling?
- Sample chosen may be widely spread, thus entailing higher costs
- The probability of obtaining an unrepresentative sample is higher than other designs, especially in studies of small size.
- A sampling frame is necessary.
40
- Sequence
- A variation of SRS
- A sampling interval 'K' is first determined where 'K' is the ratio of the population size (N) to the sample size (n)
Systematic Sampling
41
Formula for the Systematic Sampling
Formula – K=N/n
Ex: the calculated K is 10 – so every 10th patient is your participant
42
Familiarize the steps in Systematic Sampling Design
1. Determine the required sample size, n.
2. Determine the sampling interval (K = population size / Sample Size)
3. Select a number at random between 1 and k The population element in the frame corresponding to the random number selected will be the first to be included in the sample.
4. Include in the sample every kth population element after the first random number selected.
43
Advantages of Systematic Sampling:
1. Drawing a sample is easier
2. Easy to administer in the field
3. A frame is not necessary
4. May give more precise estimates than simple random sampling
44
Disadvantages of Systematic Sampling:
1. May give poor precision when unsuspected
periodicity is present in the population
Ex. may pattern na every 5th ay masungit, pero iba naman ay di masungit therefore lalabas sa conclusion panget service ng hospital
45
- The population is first divided into non- overlapping groups called strata.
- A simple random sampling is then selected
from each stratum
- Mutually exclusive
- The division is exclusive non overlapping and heterogenous
Stratified Random Sampling
46
Familiarize stratified random sampling procedure:
1. Identify the stratification variable.
2. Number the population elements within each category of the stratification variable.
3. Determine the sample size needed from each stratum
4. Within each stratum, select the required number of samples by simple random sampling
47
When a sampling frame for the elementary units is not readily available, or when cost considerations are important
Cluster Sampling
48
Familiarize yourself with the cluster sampling Procedure:
1. The population is first divided into clusters, which serve as the sampling units and a sample of units is selected
2. Every element found in each sampling unit drawn as a sample may or may not be included in the study; if only a subset Of the sampling units in the cluster is selected, we have a multi-stage sampling design.
3. If all the sampling units in a cluster are selected, we have a Single-stage Cluster Sampling Design.
49
T or F for Cluster Sampling
- Does not require a sampling frame of all elementary units; only a population list of clusters is needed.
True
50
T or F for Cluster Sampling
Listing cost and transportation increases
False (Reduced)
51
Bend that ass over
let that coochie breathe
52
When the sample survey to be conducted has a wide coverage as in a nationwide surveys
Multi Stage Sampling
53
T or F
Nationwide study, can also employ several types?
T
54
T or F
You use total summoning if there are very limited subjects, and sampling may not be required (e.g. rare conditions)
F (total enumeration)
55
T or F - Source of Bias in Sampling
Any pre-agreed sampling rules are deviated from
T
56
T or F - Source of Bias in Sampling
People in hard to reach groups are ommitted
T
57
T or F - Source of Bias in Sampling
Selected individuals are replaced with others (e.g. if
they are difficult to contact)
T
58
T or F - Source of Bias in Sampling
A dated list is used as the sample frame
F (edi hindi nayan bias)
59
the population is divided into clusters, and then entire clusters are randomly selected for inclusion in the study.
Cluster Sampling
60
the population is divided into subgroups or strata based on certain characteristics, and then random samples are independently selected from each stratum.
Stratified Random Sampling
61
If you see this card
Familiarize yourself with the steps and procedures of multi-stage sampling design
(diko nilagay here kasi sobrang dami, too overwhelming)
62
T or F - Sample Size Estimation
The rarer the condition, the smaller the sample
size
F (Larger)
63
T or F - Sample Size Estimation
Complex data analysis require larger sample
size than simple analysis
T
64
T or F - Sample Size Estimation
The more homosexual the values of the
parameter are, the larger the sample size.
F (heterogenous)
65
T or F - Sample Size Estimation
In general, longitudinal studies require a larger
sample size than case-control and crosssectional studies
T
66
T or F - Sample Size Estimation
It is a good practice to not provide a correction
factor for non-response or refusal rate in the
estimation of the sample size
F (do provide)
67
Mark Lee or Jeno Lee
BOTH, tf
68
T or F - Sample Size Estimation
The higher the level of accuracy and precision
desired for the resulting estimates, the larger
the sample size necessary.
T
69
T or F - Sample Size Estimation
When more than one item or parameter are to
be studied, sample sizes are estimated collectively
for important item part or parameter
F (Separately and it is for EACH ITEM)
70
T or F - Sample Size Estimation
When estimating for different units of analysis
(e.g., regional or provincial estimates), sample
sizes has to be estimated for each unit.
EURT
71
If you see this card
Please do study the formula part for Estimation of the Population Mean
72
If you see this card
STUDY THE SAMPLE SIZE ESTIMATION PPT, di kaya ilagay here kasi own computations
Biostatistics & Epidemiology
flashcards
Decks in class (18)
# Cards
-
Introduction to Biostatistics; Variables86
-
Sampling and Sample Size Estimation72
-
Descriptive Statistics67
-
Inferential Statistics125
-
Data Presentation108
-
(M) Introduction to Epidemiology75
-
(M) Theory of Disease Causation226
-
(M) Natural History and Spectrum of Disease; and The Levels of Disease Prevention182
-
(M) Descriptive - Epidemiologic Approach80
-
(M) Analytic - Epidemiologic Approach211
-
(M) Validity of Epidemiologic Studies45
-
(M) Modern concepts of disease (Bradford Hill criteria)10
-
(M) Clinical Trials8
-
(F) Rates and Ratio140
-
(F) Demography75
-
(F) Outbreak Investigation183
-
(F) Introduction to Surveillance83
-
(F) BIOEPI QUIZZES40
