SAS 10 Flashcards
two types of data
primary data
secondary daya
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.
primary data
are information taken from published or unpublished materials previously gathered by other researchers or agencies such as books, newspapers, magazine, journals, published and unpublished thesis and dissertations.
secondary data
one of the most important parts of the research work that needs preparation and planning is choosing the right and appropriate sampling method
sampling techniques
two types of sampling technique
probability sampling
non-probability sampling
every unit has a chance of being selected and that chance can be quantified.
probability sampling
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.
probability sampling
every item in the population does not have an equal chances of being selected and the results are often biased.
non-probability sampling
types of probability sampling
simple random sampling
systematic random sampling
stratified random sampling
cluster random sampling
types of non-probability sampling
convenience sampling
snowball sampling/ respondent-driven sampling
voluntary sampling
is commonly recommended to prevent the possibility of bias or erroneous inference
simple random sampling
each member of the population has an equal chance to be included in the sample gathered
simple random sampling
2 ways can be done through simple random sampling
table of random numbers
lottery or fishbowl technique
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.
lottery/fishbowl technique
2 ways using lottery fishbowl technique
sampling without placement
sampling with placement
in which the drawn papers are no longer returned in the container
sampling without placement
involves returning to the container every piece of paper drawn
sampling with placement
every nth individual or item in the population is selected, starting with a randomly chosen starting point.
systematic random sampling
This method is useful when the population is ordered, such as in a list or a production line.
systematic random sampling
Select sample at regular intervals based on sampling fraction
• The items or individuals are arranged in some way- perhaps alphabetically or other sort
systematic random sampling
the population is divided into non-overlapping strata or groups based on specific characteristics (e.g., age, gender, income level).
stratified random sampling
A random sample is then drawn from each stratum, ensuring that each group is proportionally represented in the sample.
stratified random sampling
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
stratified random sampling
the population is divided into naturally occurring groups or clusters.
cluster random sampling
A random sample of clusters is then selected, and all individuals within the chosen clusters are included in the sample.
cluster random sampling
This method is useful when the population is spread out over a large geographic area.
cluster random sampling
select all units within randomly selected geographic clusters
cluster random sampling
• 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
• Cluster sampling is sometimes referred to as an “_________” because it is frequently applied on a geographical basis
area sampling
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
are collected in an investigation and they are not organized systematically.
raw data
Raw data are presented in the form of frequency distribution are called
grouped data
2 methods of organizing the raw data
setting up an array
stem-and-leaf- diagram
An ordering of the observations from the smallest to the largest or vice versa is an
array
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
A tabular arrangement or data by classes together with the corresponding class trequencies called
frequency distribution or frequency table
ways of constructing a frequency distribution table
first method
second method
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
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
a point that represents the halfway point between two successive classes is called
true limits or class boundary
is the midpoint of a class interval
class mark
