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Biostat Lec > M2 > Flashcards

M2 Flashcards

1
Q

all items or individuals of interest.

A

population

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2
Q

A finite subset of statistical individuals obtained from the population.

A

sample

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3
Q

select a portion from the population

A

sampling

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4
Q
  1. Complete enumerations are not possible when the population is infinite.
  2. Results are needed in a short amount of time.
  3. The survey area is wide.
  4. Limited resources
  5. An item or unit is destroyed during an investigation.
A

Reason for selecting a sample

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5
Q
  1. Define Target Population
  2. Select sampling frame.
  3. Define if probability or non-probability.
  4. Procedure for selecting sampling.
  5. Determine sample size.
  6. Selection of actual sample
  7. Fieldwork
A

Stages in Sampling Collection

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6
Q
  • Simple Random
  • Systematic
  • Stratified Random
  • Cluster
A

Probability of Sampling Techniques

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7
Q

TRUE OR FALSE: All types of Probability Sampling Techniques can
be multi-Stage

A

true

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8
Q
  • Quota
  • Snowball
  • Self-Selection
  • Convenience
  • Purposive
A

Non-Probability Sampling Technique

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9
Q
  • Extreme Case
  • Heterogenous
  • Homogenous
  • Critical Case
  • Typical Case
A

Types of Purposive Sampling

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10
Q

The researcher chooses a sample that is readily available in some nonrandom way.

A

Non Prob - Convenience sampling

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11
Q

The respondent decides whether or not to participate, typically in one request without the chance for follow up.

A

Non prob - Self selection sampling

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12
Q

It asks respondents to recommend other respondents who might subsequently be invited to take the survey.

A

non prob - snowball sampling

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13
Q

The interview or study designer chooses sampled units who, by their judgment, will meet the specific purpose of the survey.

A

non prob - Purposive Sampling

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14
Q

representative of views on an issue but “to look at it from all angles”

A

Maximum Variance Sampling
(Heterogeneous Sampling)

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15
Q

deeply explore the views of a group of respondents with the same characteristics.

A

Homogenous Sampling

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16
Q

is interested in an in-depth assessment of the typical viewpoint

A

Typical Case Sampling

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17
Q

interested in understanding unusual cases such as successes or failures

A

Extreme Case Sampling

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18
Q

Studying those cases that have the most to offer in terms of understanding the population.

A

Critical Case Sampling

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19
Q

Surveying experts on a particular topic, with their expertise left to the judgment of the interviewer or study designer.

A

Expert Sampling

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20
Q

Surveying every single member of a qualifying subgroup

A

Total Population Sampling

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21
Q

the population of interest is represented almost exactly by the percentage of each cell (major demographic group) in the final survey results. “Strata may be joint or interlocking” – so you might have quotas of younger women, older women, younger men, and older men. Sometimes known as “hard quotas”.

A

Proportional Quota Sampling

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22
Q

Also known as “soft quotas”, it captures a minimum number of respondents in a specific group.

A

Non-Proportional Quota Sampling

23
Q

It should have both coverage or a non zero chance of selecting any member of target population and external selection which is the random selection of members of population to participate in the survey

A

Probability Sampling

24
Q
  • it refers to any sampling method that has the following properties.
    o The population consists of N objects.
    o The sample consists of n objects.
    o If all possible samples of n objects are equally likely to occur
A

Simple Random Sampling

25
Q

Each of the N population members is assigned a unique number. The numbers are placed in a bowl and thoroughly mixed. Then, a blind-folded researcher selects n numbers. Population members having the selected numbers are included in the sample.

A

Lottery method

26
Q

The population is divided into groups, based on some characteristic. Then, within each group, a probability sample (often a simple random sample) is selected.

A

stratified sampling

27
Q

In stratified sampling, the groups are called?

A

strata

28
Q

Every member of the population is assigned to only one group. A sample of clusters is chosen, using a probability method (often simple random sampling)

A

Cluster Sampling

29
Q

A list of every member of the population. From the list, we randomly select the first sample element from the first k elements on the population list. Thereafter, we select every kth element on the list

A

Systematic Random Sampling

30
Q

Combination of two probability sampling.

A

Multistage sampling

31
Q

True or false: There is no standard rule regarding the sample size. However, the higher the percentage of the sample, the higher the validity of the study or thesis. The bigger the population, the lesser percentage of the sample is taken.

A

True

32
Q

True or false: Researchers can use the Sloven’s Formula to calculate for the number of samples to use for a study.

A

true

33
Q

True or false: “Sloven’s Formula” was formulated by Slovin in 1961. Hence, some literature refer to it as “Slovin’s Formula”.

A

false. Sloven’s Formula” was formulated by Slovin in 1960

34
Q

The HIGHER the percentage of sample, the HIGHER the validity of the research

A

General Rule on Sample Size

35
Q

n = [N/(1 + N(e)^2)]

A

Slovin’s formula

36
Q

It is another term for accuracy

A

Confidence level

37
Q
  • Have not been summarized in any way.
  • Also called “raw data”
A

Ungrouped Data

38
Q
  • Data that has been organized into a frequency distribution table.
A

Grouped data

39
Q

often called the average of a numerical set of data, is simply the sum of the data values divided by the number of values

A

Mean

40
Q

symbol for mean

A

x bar or x̄

41
Q

sum of the values over the number of values

A

mean

42
Q

the number that falls in the middle position once the data has been organized from lowest to highest value.

A

Median

43
Q

Symbol for medial

A

Md

44
Q

(n+1) / 2

A

median

45
Q
  • a set of data is simply the value that appears most frequently in the set.
  • The symbol is Mo.
A

Mode

46
Q

Only one mode

A

Unimodal

47
Q

two modes

A

bimodal

48
Q

three modes

A

trimodal

49
Q

four or more modes

A

multimodal

50
Q

easy to compute and provides statisticians and the mathematician with a better understanding of the data set how varied it is. It is the simplest approach to calculate variance in statistics.

A

range

51
Q

Highest value minus lowest value

A

range

52
Q
  • It looks at how spread out a group of numbers is from the mean.
  • It is only used to measure spread or dispersion around the mean of a data set.
  • It is never negative.
  • If all values of a data set are the same, the standard deviation is zero (because each value is equal to the mean).
A

Standard Deviation

53
Q
  • is the ratio of the standard deviation to the mean.
  • The higher it is, the greater the level of dispersion around the mean. It is
    generally expressed as a percentage.
A

Coefficient of Variation

Biostat Lec (6 decks)

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