Significance of Population and Sampling Techniques

Business Analysis
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Table of Contents
Introduction......................................................................................................................................3
Question 1:.......................................................................................................................................4
a) Significance of Population.......................................................................................................4
b) Significance of sampling techniques.......................................................................................5
Question 2........................................................................................................................................7
1. Difference between primary and secondary data.....................................................................7
2. Advantages and disadvantages of primary and secondary data...............................................9
Question3.......................................................................................................................................11
Question 4......................................................................................................................................14
Importance of management information system in decision making........................................14
Conclusion.....................................................................................................................................18
References......................................................................................................................................19
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Question 1:
a) Significance of Population
Population is a fundamental part of existence. Population data is defined as the collection of
individuals or groups of individuals with common characteristics. Population is highly dependent
on geographic location, like all California residents or all of the United States. Demographics
(those that study the population) naturally classify this population. All living beings are
considered peoples (Kwak and Kim, 2017).
Geography is one of the many ways to define and study a population. Times, political
movements, religious beliefs or physical characteristics are how people are divided into different
societies. Population surveys are conducted by examining these heterogeneous numbers and
monitoring cross-sectional variables. For example, you might learn about the American
Republican population and see the population living in Texas. In this case, you can study where
these numbers are interconnected and learn about Republicans and Texas.
Significance of population data
Important decisions about a country, group or family are based on population data. Demographic
data includes a number of important details such as demographic information such as birth,
death, age, gender, annual income, occupation, language, etc. The overall socio-economic,
economic, political and cultural development of a country depends on population data (Kaur et
al, 2018)
The socio-psychological concept of population
Social psychology is the study of how people think, influence and relate to others. This happened
at the crossroads of psychology and sociology in the early 20th century. Psychology analyzes
human nature, while sociology studies the nature of society. On the other hand, social
psychology is the study of a person's personality and relationship with society. The field of social
psychology is social and the focus is on the individual. This is the study of personality in social
situations. This social situation can be the interaction of people, the interaction of a person to a
group, and the partnerships of a group with other groups. Social psychologists use scientific
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methods to study how we perceive people and social events, how we influence and influence
others, social relationships and communication and group dynamics (Mishra et al, 2018).
Social psychology focuses on understanding the causes of social behavior and identifying the
factors that shape our feelings, behaviors and thoughts in social situations. Key hypothesis:
"Accurate and useful information on the most complex aspects of social behavior and thinking
can be obtained using basic scientific methods".
Population prediction method
The cohort component approach uses components of population change to predict population
growth. This tool assesses the population based on age group as well as other demographic
characteristics such as gender and ethnicity. This prediction method is based on the components
of demographic change, including pregnancy, mortality and migration.
To predict the total population and the number of males and females after the age of 5, find the
number of people who will or should be living in the future. Add the number of babies born and
the number of unique migrants to the surviving population. There are several ways to use the
cohort component approach. The method described here is easy to use and requires very little
demographic information (Majid, 2018).
b) Significance of sampling techniques
Definition: Sampling is a statistical approach that involves the selection of individual cases.
Helps to draw statistical conclusions about the population.
Probability Sampling Methods
1. Simple random sampling
In this situation everyone is completely chosen by some coincidence and everyone in the
population has the same chance, or probability, of being chosen. One way to give an irregular
example is to give a number to each person in a population and then use a table of irregular
numbers to choose which people should be included (Metelli et al, 2020).
2. Systematic sampling
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People will be selected at normal times from the test pattern. The races are selected to ensure an
appropriate sample size. Effective routine monitoring is more useful than basic resolution tests
and is not difficult to monitor. In any case, it may encourage bias, for example if there are hidden
examples in the application for people in the analyst scheme, to the extent that the method of
analysis agrees with the timeliness of the underlying example (Symonds, Kattirtzi and
Shalashilin, 2018).
3. Stratified sampling
In this strategy, the population is initially segmented into subgroups (or strata) that all offer a
comparative brand. It is used when we can reasonably expect the amount of interest between the
different subgroups to change and we must ensure that the subgroups are represented (Tse et al,
2018).
4. Clustered sampling
In a collected example, subgroups of the population are used as test units, as opposed to humans.
The population is divided into subgroups, called aggregates, which are randomly selected to be
remembered for study. Groups are usually effectively identified, for example individual practices
or GP practices may be identified as groups (Amato et al, 2017).
Non-probability Sampling Methods
1. Convenience sampling
The accommodation test is perhaps the least sought-after method, as members are selected on the
basis of accessibility and ability to participate (Kim and Wang, 2019)
2. Quota sampling
This monitoring strategy is routinely used by economists. Users are given a set of preset topics to
try and list.
3. Judgment (or Purposive) Sampling
Also known as a specific or abstract study, this method relies on the scientist's judgment when
choosing who he wants to participate in. Analysts can then realistically choose a "representative"
test based on their needs or target people with specific characteristics. This approach is routinely
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used by the media when seeking the general public for emotion and in thematic studies (Otzen
and Manterola, 2017).
4. Snowball sampling
This strategy is used consistently in sociology when studying hard-to-reach collections. Existing
subjects are asked to choose other familiar subjects, so the example is growing in size like a
moving snowball. It is possible to perform a snowball survey when it is difficult to identify a test
pattern. However, in selecting companions and co-workers of previously sought-after subjects,
there is a high risk of being overemphasized (selecting a very large number of people with
attributes or perspectives similar to the original one) (Sharma, 2017).
It is hard to conclude which sampling method is most reliable, because it’s mainly depends on
situation or researcher requirement. The type of sampling has to be chosen based on availability
of time, cost and research scope.
Question 2
1. Difference between primary and secondary data
Data collection plays an important role in the statistical study. Research uses a combination of
strategies to collect data and falls into two categories: critical information and optional
information. As the name suggests, essential information such as basic information is collected
by the unexpected scientist and supporting information is information that has been collected or
is now provided passed by another (Johnston, 2017).
A study uses a combination of methods to collect data that falls into two categories: primary data
and secondary data. As the name suggests, essential information is basic information collected
by the unexpected scientist and optional information is information that is currently collected or
passed on by another person. There are many differences between the essential and supporting
information described in this article. In any case, the main difference is that essential information
is authentic and unique and optional information is only a revision and translation of essential
information. While essential information is collected for purpose purposes, optional information
is collected for a variety of purposes (Sánchez-Llorens et al, 2019).
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