SAS 10 Flashcards

(41 cards)

1
Q

two types of data

A

primary data
secondary daya

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2
Q

are data collected directly by the researcher himself. These are first-hand original sources. data collection can be more effective and informative if given the necessary preparation and planning.

A

primary data

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3
Q

are information taken from published or unpublished materials previously gathered by other researchers or agencies such as books, newspapers, magazine, journals, published and unpublished thesis and dissertations.

A

secondary data

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4
Q

one of the most important parts of the research work that needs preparation and planning is choosing the right and appropriate sampling method

A

sampling techniques

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5
Q

two types of sampling technique

A

probability sampling
non-probability sampling

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6
Q

every unit has a chance of being selected and that chance can be quantified.

A

probability sampling

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7
Q

involves the selection of a sample from a population based on the principle of randomization or chance It is more complex, more time consuming and usually more costly than non- probability sampling.

A

probability sampling

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8
Q

every item in the population does not have an equal chances of being selected and the results are often biased.

A

non-probability sampling

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9
Q

types of probability sampling

A

simple random sampling
systematic random sampling
stratified random sampling
cluster random sampling

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10
Q

types of non-probability sampling

A

convenience sampling
snowball sampling/ respondent-driven sampling
voluntary sampling

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11
Q

is commonly recommended to prevent the possibility of bias or erroneous inference

A

simple random sampling

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12
Q

each member of the population has an equal chance to be included in the sample gathered

A

simple random sampling

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13
Q

2 ways can be done through simple random sampling

A

table of random numbers
lottery or fishbowl technique

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14
Q

write the name of each subject on small slips of paper and deposit them in a box. After they have been thoroughly mixed, the first pick is made followed by other until the chosen size is chosen.

A

lottery/fishbowl technique

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15
Q

2 ways using lottery fishbowl technique

A

sampling without placement
sampling with placement

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16
Q

in which the drawn papers are no longer returned in the container

A

sampling without placement

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17
Q

involves returning to the container every piece of paper drawn

A

sampling with placement

18
Q

every nth individual or item in the population is selected, starting with a randomly chosen starting point.

A

systematic random sampling

19
Q

This method is useful when the population is ordered, such as in a list or a production line.

A

systematic random sampling

20
Q

Select sample at regular intervals based on sampling fraction
• The items or individuals are arranged in some way- perhaps alphabetically or other sort

A

systematic random sampling

21
Q

the population is divided into non-overlapping strata or groups based on specific characteristics (e.g., age, gender, income level).

A

stratified random sampling

22
Q

A random sample is then drawn from each stratum, ensuring that each group is proportionally represented in the sample.

A

stratified random sampling

23
Q

Select random samples from within homogenous subgroups (strata)
• The strata are homogenous as possible and at the same time each stratum is different from one another as much as possible

A

stratified random sampling

24
Q

the population is divided into naturally occurring groups or clusters.

A

cluster random sampling

25
A random sample of clusters is then selected, and all individuals within the chosen clusters are included in the sample.
cluster random sampling
26
This method is useful when the population is spread out over a large geographic area.
cluster random sampling
27
select all units within randomly selected geographic clusters
cluster random sampling
28
• This can be done by subdividing the population into smaller units and then selecting only at random some primary units where the study would be concentrated
cluster random sampling
29
• Cluster sampling is sometimes referred to as an "_________" because it is frequently applied on a geographical basis
area sampling
30
is the process of organizing, summarizing, and displaying data in a dear, visually avealing, and meaningful way that facilitates Understanding, interpretation, and communication of this ressarch findings or insights.
data presentation
31
are collected in an investigation and they are not organized systematically.
raw data
32
Raw data are presented in the form of frequency distribution are called
grouped data
33
2 methods of organizing the raw data
setting up an array stem-and-leaf- diagram
34
An ordering of the observations from the smallest to the largest or vice versa is an
array
35
statistical tool used to organize and summarize data by showing the frequencies (number on tause is a sis or relative frequencies (proportions or percentages) of aditerive values or categories in a dataset.
frequency distribution table
36
A tabular arrangement or data by classes together with the corresponding class trequencies called
frequency distribution or frequency table
37
ways of constructing a frequency distribution table
first method second method
38
Choosing a convenient class size- to facilitate the construction of classes use multiple numbers for the class size that is easy to work such as 5, 10,20, or 50..
first method
39
may be used for more convenient class size. This method gives a more appropriate and direct way of computing the class size.
second method: the Sturge’s formula
40
a point that represents the halfway point between two successive classes is called
true limits or class boundary
41
is the midpoint of a class interval
class mark