True Love Story - Jay Steve

Story Story?

Once upon a time I was living on my own,

Having peace of my own and enjoying my single Joy,

Then all of a sudden I fall in love with this guy that is so handsome,

We walk together, play together and eat together,

The love was so sweet and beautiful,

We always want to hear the voice of each other,

And when ever we see each other we just can't stop smiling,

Things are going well,

One day we had a little misunderstanding and he just went off,

I tried to get him back but he refused and just left into the world of another lady,

I was heartbroken and devastated,

I stayed inside my room and cried,

I find it very difficult to move on for over two years because he was my first guy and I gave him my heart and my love,

But right now I am stronger,better and wiser.

Yes I am in love again, because love is a beautiful thing,

But am not stupid this time around,

I will love him,but unless we are married I will not give him my whole heart,

Is not as if I will not be faithful to him but there are some boundaries that I will not allow him to cross.

Love is actually good but when you find true love,

Heartbreak has never killed anyone but makes us stronger,

All we need to know is there is a reason behind everything that happens,

Nothing just happens,

Suicide is not the way of solving your problem,

Just take hard and with time you will understand that time will give you the  best love you dreamt of.

Let your love have sense,simply because you are in love does not mean that you should be foolish,

Our Creator loves us but in as much as He loves us, there are certain standard that if we break he punnish us for breaking it.

Enjoy your day friends.

@jaysteve

Creativity Spokenword - Jay Steve

Creativity 

Is so pathetic that people are celebrating the down fall of people over there success this days,

You are living with your neighbor and your neighbor don't want to see you wearing good clothes or eating good food,

Anytime you wear good clothes and eat some good food your neighbor will give you that pretending smiles that has the indepth of jealousy and hatred within,

People in the Low level are fighting themselves and doing evil to their fellow low level people,

And they want growth and progress,

People in the middle level are giving bribes to the low class to help them suppress other low lives,

In other to maintain their medium class position,

People in the Highest class are trying to control the middle and the low class by killing anyone that is against them,just to main wealth and power,

Each level of life has it own problem,

We are praying for a better Country and a better Nigeria when Corruption has eaten us up from  bottom to top,

One of the things killings us as a country today is we hate creative people from bottom to top,

If a friend notice that  his/her friend or brother or sister is creative,

They will look for a way to frustrate the person or kill the creativity,

And if meddle level  notice that the creativity of their friend will take him or her from that level to the high class level they look for a way to eliminate such person,

In the high class if they notice that one of them is trying to bring innovation to his people they will silently eliminate the person and nothing will be done about it because they believe they are the Law,

Is so pathetic that being Creative has become a problem in a country call Nigeria,

So people hide and die with their creativity,

No wonder if a Nigerian secured a job in another country where the person creativity is well acknowledge,

They become the best and give their best,

No wonder Nigeria is still a consuming nation because people of creativity have become a prey in our society today.

But does it mean that we should keep hiding with our creativity and allow the nation to suffer because of fear?

We need to come forth and stand for what is right,

In our families we need to encourage those that are creative among us,

In our local communities and religious levels we need to encourage those that are creative among us,

Our society need to give  room for creativity.

Creativity is what makes a nation great.

Show me a nation with creativity and I will show you a nation that is prospering 

A nation that don't appreciate creativity  will always be a dependent and  a consuming nation.

Give love for creativity a space,

In our family, community,state,nation and in the world.

And the continents will experience overflow of greatness.

@jaysteve

Importance of Strategic and Breakdown of Effective Communication

I am here to Stand against the motion; Breakdown of effective communication in an organization.

Below are my following points:

What is a communication breakdown? 

If communication is the exchange of information between two or more individuals, a communication breakdown means not being able to get your message across properly. 

When communication breakdown occurs, it usually results in a lack of communication.

1. The effects of communication breakdowns on mental health 

Communication breakdowns cause stress and low morale in your employees. 

Namely, according to the 2021 report The Evolution of Communication, 7 in 10 Americans agree that mental health is tied to communication. 

Therefore, when communication fails, employees’ mental health deteriorates, making them more stressed and anxious.   

2.The effects of communication breakdowns on work culture

Communication breakdowns affect your work culture, too. 

They may demotivate your employees and create tension amongst the team. 

Furthermore, that kind of work culture may cost you your clients or business opportunities.

3.Unpredictable Work Environment

Poor communication causes a lack of predictability and stability within the workplace, leading to an uneasy environment for employees to work in. Employees might not clearly understand their objectives for the week or might misunderstand the process for a project, leading to unproductivity and ineffectiveness at their job. Employees and employers have a responsibility to facilitate an active dialogue in order to create a stable work environment to get their best work done.

4.Less Effective Collaboration

Collaboration and communication go hand in hand. If employees are unable to communicate effectively, it is very likely for collaboration to be effective as well. Collaboration in the workplace is important in many ways from promoting self-analysis and resulting in efficient problem solving. The effects of poor communication in the workplace set every collaborative project for failure, and almost everything in the 21st century workplace is a collaboration. 

5. Workplace Conflict:

The effects of poor communication may cause tensions to rise, resulting in a potential conflict between employees. Failure to communicate may cause employees to make the wrong assumptions, such as leaving other employees to pick up their work, when this task was not previously discussed between a team. Good communication prevents workplace from arising in the first place.

6: Low Morale

With poor communication, employees may have a harder time meeting expectations and catching up with their deadlines, resulting in them getting behind. This could leave them with a sense of guilt, embarrassment or even low self-esteem. Low workplace morale should be addressed immediately, so that employees can maintain a healthy work-life balance and continue working efficiently.

I am here to to stand with the motion that says:

Strategy for effective communication.

Strategy Communication is a combination of both theory and practice that seeks to understand the effect of culture on all aspects of marketing communications. Globalization, global branding strategies, and classification models of culture are all issues covered within this study. Strategic Communications studies the dynamics of consumer behavior, trends in marketing strategies, and shifts in global culture.

Points:

1. Enables you to lead your business:

As a CMO you need a comms strategy because it will make your job easier and more rewarding, it will also help you to lead the business and perform your duties at a higher level altogether.

The nature of being responsible for a company’s marketing means you must respond to multiple demands from the business. This can lead to a kind of tactical myopia. Your colleagues in sales will demand qualified leads – and rightly so – but if you haven’t got a mutually agreed understanding of your target sector priorities and a tight definition of your target personas, then the likelihood for disagreement or disappointment is almost inevitable.

2.    Provides focus and efficiency:

Low hanging fruitA well-formed comms strategy keeps you both focussed and aligned. It ensures you are more efficient, by focussing your time and money on the strategic priorities. The natural optimism, energy and opportunism characteristic of salespeople means that they can be distracted by whoever or whatever appears to be a quick win. That’s not to say low-hanging fruit shouldn’t be picked if it falls outside the specified target – but it must be recognised for what it is and should not distract everyone from the wider strategic intent.

A comms strategy provides a yardstick by which every effort and initiative can be assessed for efficacy. Everyone needs to understand when the pursuit of low hanging fruit has turned into an unhelpful distraction and drain on resources. If you own a comms plan, this will be as clear as the nose on your face.

3.    Results in more effective messaging:

Your audience is ...article quoteYour target audience will rarely comprise a disciplined cohort equipped with all the information they need to select your products and services. Your audience is most likely made up of broad groups of people, with similar sets of responsibilities, who are at different stages of the buying cycle. They are probably ill-informed, confused and/or insecure in their knowledge or options. Creating typical, representative personas helps to focus attention and effort. Furthermore, understanding that your target persona will be at different stages of the buying cycle enables you to develop messaging which talks to their individual information needs, while addressing their fears, motivations and irritations. This approach, which respects your target audiences’ differences, will be more persuasive because you are telling them things that matter to them in a way that helps them to move along their buying journey.

4.    It forearms you:

Your comms strategy captures your sales needs, sector priorities, personas, positioning and messaging. It provides you, and your extended team and colleagues, with many of the essential tools you need to enable you to deliver your business objectives. I’m a great believer in active decision-making. The process of formulating your comms strategy will enable you to identify knowledge gaps. Then, you can decide whether you need to secure the missing information or not.  It’s important to recognise and understand the implications of your action or inaction so that outcomes don’t come as a surprise – forewarned is forearmed.

 

5.    Brings clarity of purpose:

a communications strategy quoteWhatever your objectives and whatever your requirements, a communication strategy just makes the process of getting there more efficient, more effective and the journey so much more rewarding. Having clarity of purpose also allows you to lead the business, fend off unnecessary or irrelevant requests and direct your resources with intent.

6. Employees are more productive when they have all the necessary information in a clear, concise format.

7. All employees receive the information they need to do their jobs correctly and to meet deadlines.

8. Collaboration improves because employees bounce ideas off one another and build off each other’s thoughts and experiences. 

9. Employees can better handle conflict when they know how to communicate their ideas and listen to their peers to create a solution.

10  Effectively sharing ideas can enhance creativity and innovation, which can help grow your business.

11. The company culture improves because people feel heard and know what’s happening.

Relationships between employees and with clients are strengthened.

 

Conclusion:

Reference;

https://www.indeed.com/recruitment/c/info/business-communication-strategies

https://pumble.com/blog/communication-breakdown/

https://www.simpplr.com/blog/2021/causes-effects-poor-communication-workplace/

https://ec-pr.com/six-reasons-why-you-need-a-communication-strategy/

Decision Support System (DSS)

Table of Contents

Introduction/Definition of Decision Support System (DSS)

 Decision Support System Components

Types of Decision Support System

Examples of Decision Support System

Characteristics of Decision Support System

Benefits of Decision Support System

Advantages and disadvantages of Decision Support System

Conclusion

Reference

Introduction;

A decision support system gathers and analyzes data, synthesizing it to produce comprehensive information reports. In this way, as an informational application, a DSS differs from an ordinary operations application, whose function is just to collect data.The DSS can either be completely computerized or powered by humans. In some cases, it may combine both. The ideal systems analyze information and actually make decisions for the user. At the very least, they allow human users to make more informed decisions at a quicker pace

What is a decision support system (DSS)?

• A decision support system (DSS) is a computer program application used to improve a company's decision-making capabilities. It analyzes large amounts of data and presents an organization with the best possible options available.

• Decision Support Systems (DSS) are a class of computerized information system that support decision-making activities. DSS are interactive computer-based systems and subsystems intended to help decision makers use communications technologies, data, documents, knowledge and/or models to complete decision process tasks.

• A decision support system (DSS) is a computerized program used to support determinations, judgments, and courses of action in an organization or a business. A DSS sifts through and analyzes massive amounts of data, compiling comprehensive information that can be used to solve problems and in decision-making.

Decision support systems bring together data and knowledge from different areas and sources to provide users with information beyond the usual reports and summaries. This is intended to help people make informed decisions.

Typical information a decision support application might gather and present include the following:

comparative sales figures between one week and the next;

projected revenue figures based on new product sales assumptions; and

the consequences of different decisions.

A decision support system is an informational application as opposed to an operational application. Informational applications provide users with relevant information based on a variety of data sources to support better-informed decision-making. Operational applications, by contrast, record the details of business transactions, including the data required for the decision-support needs of a business.

Decision Support System Components

A typical DSS consists of three different parts: 

- knowledge database

-software 

- user interface.

Knowledge base. 

A knowledge base is an integral part of a decision support system database, containing information from both internal and external sources. It is a library of information related to particular subjects and is the part of a DSS that stores information used by the system's reasoning engine to determine a course of action.

Software System

. The software system is composed of model management systems. A model is a simulation of a real-world system with the goal of understanding how the system works and how it can be improved. Organizations use models to predict how outcomes will change with different adjustments to the system.

For example, models can be helpful for understanding systems that are too complicated, too expensive or too dangerous to fully explore in real life. That's the idea behind computer simulations used for scientific research, engineering tests, weather forecasting and many other applications.

Models can also be used to represent and explore systems that don't yet exist, like a proposed new technology, a planned factory or a business's supply chain. Businesses also use models to predict the outcomes of different changes to a system -- such as policies, risks and regulations -- to help make business decisions.

User Interface

The user interface enables easy system navigation. The primary goal of the decision support system's user interface is to make it easy for the user to manipulate the data that is stored on it. Businesses can use the interface to evaluate the effectiveness of DSS transactions for the end users. DSS interfaces include simple windows, complex menu-driven interfaces and command-line interfaces.

Decisions

Based on user requirements, results are generated by the Decision Support System.

Types of Decision Support Systems

Decision support systems can be broken down into categories, each based on their primary sources of information.

Data-driven DSS

A data-driven DSS is a computer program that makes decisions based on data from internal databases or external databases. Typically, a data-driven DSS uses data mining techniques to discern trends and patterns, enabling it to predict future events. Businesses often use data-driven DSSes to help make decisions about inventory, sales and other business processes. Some are used to help make decisions in the public sector, such as predicting the likelihood of future criminal behavior.

Model-driven DSS

Built on an underlying decision model, model-driven decision support systems are customized according to a predefined set of user requirements to help analyze different scenarios that meet these requirements. For example, a model-driven DSS may assist with scheduling or developing financial statements.

Communication-driven and group DSS

A communication-driven and group decision support system uses a variety of communication tools -- such as email, instant messaging or voice chat -- to allow more than one person to work on the same task. The goal behind this type of DSS is to increase collaboration between the users and the system and to improve the overall efficiency and effectiveness of the system.

Knowledge-driven DSS

In this type of decision support system, the data that drives the system resides in a knowledge base that is continuously updated and maintained by a knowledge management system. A knowledge-driven DSS provides information to users that is consistent with a company's business processes and knowledge.

Document-driven DSS

A document-driven DSS is a type of information management system that uses documents to retrieve data. Document-driven DSSes enable users to search webpages or databases, or find specific search terms. Examples of documents accessed by a document-driven DSS include policies and procedures, meeting minutes and corporate records.

Decision Support System Examples

Organizations use decision support systems in several different contexts, including the following:

GPS routing.

 GPS route planning is an example of a typical DSS. It compares different routes, taking into account factors such as distance, driving time and cost. The GPS navigating system also enables users to choose alternative routes, displaying them on a map and providing step-by-step instructions.

ERP dashboards.

 ERP (enterprise resource planning) dashboards can use a decision support system to visualize changes in production and business processes, monitor current business performance against set goals and identify areas for improvement. ERP dashboards let business owners see a snapshot of their company's most important numbers and metrics.

Clinical decision support system. 

A clinical decision support system (CDSS) is a software program that uses advanced decision-making algorithms to help physicians make the best medical decisions. Healthcare professionals often use these to interpret patient records and test results, and to calculate the best treatment plan. CDSS in healthcare can help providers identify abnormalities during specific tests, as well as monitor patients after certain procedures to determine if they are having any adverse reactions.

Characteristics of a DSS

The primary purpose of using a DSS is to present information to the customer in an easy-to-understand way. A DSS system is beneficial because it can be programmed to generate many types of reports, all based on user specifications. For example, the DSS can generate information and output its information graphically, as in a bar chart that represents projected revenue or as a written report.

As technology continues to advance, data analysis is no longer limited to large, bulky mainframe computers. Since a DSS is essentially an application, it can be loaded on most computer systems, whether on desktops or laptops. Certain DSS applications are also available through mobile devices.

The flexibility of the DSS is extremely beneficial for users who travel frequently. This gives them the opportunity to be well-informed at all times, providing them the ability to make the best decisions for their company and customers on the go or even on the spot.

Benefits of a Decision Support System?

Broadly speaking, decision support systems help in making more informed decisions. Often used by upper and mid-level management, decision support systems are used to make actionable decisions, or produce multiple possible outcomes based on current and historical company data. At the same time, decision support systems can be used to produce reports for customers that are easily digestible and can be adjusted based on user specifications. 

Advantages of a Decision Support System

- It Saves Time by speeding up the process of decision making.

- It Improves communication between people through meetings, brainstorming sessions, etc.

- Reports generated by the Decision Support System can be used as evidence.

- It helps to automate processes.

- Reduction of cost

Disadvantages of a Decision Support System

- Overload Information

- Reduction of status

- Unanticipated effects

- Cost in Monetary

- Too much DSS dependency

Computer File System

  

  TABLE OF CONTENTS

Introduction

•Definition of Computer file System

•Types of Computer file system 

•Advantages and disadvantages of •computer file system

•Elements of Computer Files System

•Classification of Computer files System 

•Uses of Computer file System

•Conclusion

•Reference

Introduction;

If we talk about what a file system is from the perspective of the computer, there are a lot of details that don’t really matter to the average user, which confuses the whole topic.

If we break it down from the point of view of the average user, all of a sudden, the file system is easy to understand, and it’s useful to know about. It can actually help you in your day-to-day computer use.

A file system allows you to organize and store files on your computer hard drive. They are organized in a system of folders that create a tree-type structure. The main folder or root folder is represented as your hard drive. All of the other folders in the root folder are considered subfolders.

That being said, they’re usually just called folders. Any folder in the file system can hold files and subfolders of its own. This is a great system for searching and sorting files and folders. Without the file system, all of the data on your computer would just be lumped together on the hard drive without a way to reference it or look it up easily.

Definition;

A computer file system is used to organize files & data in your computer’s non-volatile memory or hard drive in a hierarchy of nested folders. It’s typically organized in a tree data structure, with one parent folder being the hard drive & other folders existing in subfolders below that. 

A computer file system  is a method and data structure that the operating system uses to control how data is stored and retrieved. The structure and logic rules used to manage the groups of data and their names is called a "file system.

A file system is the way in which files are named and where they are placed logically for storage and retrieval.

What is a file in a file system?

A file in a file system is a digital representation or marker created to hold information about the data it’s for. The file marker holds the name of the file, the size of the file, and the location of the file on the hard drive. Other details like when it was created are also available.

An interesting property is that it allows you to control access to the file through the read/write/execute permissions, as discussed above. You can copy files, paste files, or create shortcuts to them.

How do I set up a file system on a computer?

The file extension tells the user and the computer what type of file it is. Documents, images, and videos are common file types.

Some file systems are already installed when you buy your computer, such as program files and system files. But you can arrange your own folder hierarchy for basic file types however you like, typically by dragging and dropping documents and images into folders you create yourself.

A folder hierarchy is a visual representation of how folders and subfolders are organized. You can include multiple file extensions in one folder; for example, you can include XLS, DOC, PPT, WMV, PDF, and JPG in one folder.

Can I transfer a file to another computer?

Yes, but you may not be able to open, read, or modify the file if the new computer doesn’t have the proper hardware installed.

There are multiple ways to transfer files. For example, you can transfer files using an external hard drive or through the web. But you’ll need to have the executable program file installed before you can open, read, and modify (and save) the file.

There are several different files systems, but seven are worth covering for the average computer user.

1. Disk file system

A Disk file system is the most common files system because it exists on hard drives and other long-term storage devices. It’s comprised of the typical tree-like structure and can hold multiple layers of folders and files.

2. Flash file system

A flash file system is optimized to leverage the strengths of a flash memory device like a USB stick or SD card. Their use is, of course, limited, especially since the disk file system often gets extended to removable media like thumb drives and memory cards.

3. Database file systems

Database file systems are organized using features of the various files rather than their location so that you can search the database by a certain feature set. A great application for this type of file system is in a company with many drawings or corporate documents that they want to search for a given system or author.

4. Transactional file system

The transactional file system exists within the microcosm of a single piece of software. It’s the file system that a piece of software sets up for itself when it gets installed. Thus, it gets set up in a single move and is used on a transactional basis as the software gets used. Naturally, therefore, it must get maintained during updates or the application of extensions.

5. Network file system

A network file system is a file system that is accessed across a network. It can be accessed by more than one machine, so priorities and resource sharing become an issue. Usually, this involves specialized technology leveraging something like FTP or NFS.

6. Shared disk file system

The shared disk file system is often realized with network shares or shared drives like you may see at work. Usually, these shared drives are accessed across a network, meaning shared access is an issue here. Often, they get added to your computer using a process called “Mounting.” You mount network drives. Once it has been mounted, you can access it like an additional hard drive.

7. Flat file system

The flat file system has all but gone extinct. It was more of a common system during the days of floppy drives. As it sounds, a flat file system is flat with only one folder with files in it.

Some of the advantages of computerized filing system include:

information takes up much less space than the manual filing.

It is much easier to update or modify information.

it offers faster access and retrieval of data.

It enhances data integrity and reduces duplication.

It enhances security of data if proper care is taken to secure it.

Disadvantages of Computer file system;

Data Inconsistency: Data inconsistency means that different files may contain different information of a particular object or person. Actually redundancy leads to inconsistency. When the same data is stored in multiple locations, the inconsistency may occur.

       Data Sharing: In computer file-based processing systems, each application program uses its own private data files. The computer file-based processing systems do not provide the facility to share data of a data file among multiple users on the network.

       Data Isolation: In computer file-based system, data is isolated in separate files. It is difficult to update and to access particular information from data files.

A computer file is made up of three elements:

Which are;

characters, fields and records.

Characters

A character is the smallest element in a computer file and refers to letter, number or symbol that can be entered, stored and output by a computer. A character is made up of seven or eight bits depending on the character coding scheme used.

Field

A field is a single character or collection of characters that represents a single piece of data. For example, the student’s admission number is an example of a field.

Records

A record is a collection of related fields that Represents a single entities, e.g. in a class score sheet, detail of each student in a row such as admission number, name, total marks and position make up a record.

Classification of Computer files;

Logical files;

A computer file is referred to as logical file if it is viewed in terms of what data item it contains and details of what processing operations may be performed on the data items. It does not have implementation specific information like field, data types, size and file type.

Physical files

As opposed to a logical file, a physical file is viewed in terms of how data is stored on a storage media and how the processing operations are made possible. Physical files have implementation specific details such as characters per field and data type for each field.

Uses of Computer file System

Directories;

File systems typically have directories (also called folders) which allow the user to group files into separate collections. This may be implemented by associating the file name with an index in a table of contents or an inode in a Unix-like file system.

Metadata 

A file system stores all the metadata associated with the file—including the file name, the length of the contents of a file, and the location of the file in the folder hierarchy—separate from the contents of the file.

Filenames

 filename (or file name) is used to identify a storage location in the file system. Most                                                         file systems have restrictions on the length of filenames.

Restricting and permitting access

There are several mechanisms used by file systems to control access to data. Usually the intent is to prevent reading or modifying files by a user or group of users. Another reason is to ensure data is modified in a controlled way so access may be restricted to a specific program. Examples include passwords stored in the metadata of the file or elsewhere and file permissions in the form of permission bits, access control lists, or capabilities.

Maintaining integrity

One significant responsibility of a file system is to ensure that the file system structures in secondary storage remain consistent, regardless of the actions by programs accessing the file system. This includes actions taken if a program modifying the file system terminates abnormally or neglects to inform the file system that it has completed its activities. This may include updating the metadata, the directory entry and handling any data that was buffered but not yet updated on the physical storage media.

User data

The most important purpose of a file system is to manage user data. This includes storing, retrieving and updating data.

Some file systems accept data for storage as a stream of bytes which are collected and stored in a manner efficient for the media.

Conclusion;

Computer file system is very important to the computer system itself and not just the computer but also to the individual,families,business organizations,companies,governments,scienti scientists,social science and arts inclusive. Because without the file system we can not operate the computer or even think of saving our files in the computer,the sectorial break down of the computer file systems enable us to save and search for various informations on time without stress.

Humanbeings today can't do without the computer and the computer can't exist without the Computer file system in it.

Reference;

https://www.computerchum.com/what-are-computer-file-systems/

https://en.m.wikipedia.org/wiki/File_system

https://www.google.com/amp/s/www.techtarget.com/searchstorage/definition/file-system%3famp=1

https://dutable.com/2018/10/12/disadvantages-or-limitations-of/

https://peda.net/kenya/css/subjects/computer-studies/form-three/driac2/data-processing/computer-files

Sampling Techniques in Statistics

           Table of contents

Sampling Techniques: Introduction

Sampling

Different types of Sampling techniques

Choosing Between Probability and Non-Probability Samples

Probability Sampling 

Non-probability sampling

Sampling errors and biases

Introduction: 

Let’s take an example of COVID-19 vaccine clinical trials. It is very difficult to conduct the trials on the entire population, as it deals with time, money, and resources. So in research methodologies, sampling is a method that helps researchers to infer information about a population based on results from a subset of the population, without having to investigate every individual. 

A telecom company planning to build a machine learning model to predict, churn customers from their network. One way is to collect all the customers’ information and build a prediction model. This method requires high computational power and resources. So the best way is to take a sample (Subset of customers) from the population (All customers) which represents the population and build the machine learning model. This saves money and effort.

Sampling: 

Sampling is the process of selecting a group of individuals from a population to study them and characterize the population as a whole.

sampling is the selection of a subset (a statistical sample) of individuals from within a statistical population to estimate characteristics of the whole population.

The population includes all members from a specified group, all possible outcomes or measurements that are of interest. The exact population will depend on the scope of the study.

The sample consists of some observations drawn from the population, so a part of a subset of the population. The sample is the group of elements who participated in the study.

The sampling frame is the information that locates and defines the dimensions of the universe.

             A good sample should satisfy the below conditions-

             Representativeness: The sample should be the best representative of the population                         

             under study.

             Accuracy: Accuracy is defined as the degree to which bias is absent from the sample. An  

             accurate (unbiased) sample is one that exactly represents the population.

Size: A good sample must be adequate in size and reliability.

Different types of Sampling techniques:

There are several different sampling techniques available, and they can be subdivided into two groups-

1. Probability sampling involves random selection, allowing you to make statistical inferences about the whole group.

There are four types of probability sampling techniques

Simple random sampling

Systematic Sampling

Stratified random sampling

Cluster sampling

 Non-probability sampling involves non-random selection based on convenience or other criteria, allowing you to easily collect initial data. 

There are four types of Non-probability sampling techniques.

Convenience sampling

Quota Sampling

Judgmental or purposive sampling

Snowball sampling

Choosing Between Probability and Non-Probability Samples

The choice between using a probability or a non-probability approach to sampling depends on a variety of factors:

- Objectives and scope of the study

- Method of data collection 

- Precision of the results 

- Availability of a sampling frame and resources required to maintain the frame

- Availability of extra information about the members of the population

Probability Sampling 

Probability sampling is normally preferred when conducting major studies, especially when a population frame is available, ensuring that we can select and contact each unit in the population. Probability sampling allows us to quantify the standard error of estimates, confidence intervals to be formed and hypotheses to be formally tested. 

The main disadvantage is Bias in selecting the sample and the costs involved in the survey.

Simple random sampling 

In Simple Random Sampling, each observation in the population is given an equal probability of selection, and every possible sample of a given size has the same probability of being selected. One possible method of selecting a simple random sample is to number each unit on the sampling frame sequentially and make the selections by generating numbers from a random number generator.

Simple random sampling can involve the units being selected either with or without replacement. Replacement sampling allows the units to be selected multiple times whilst without replacement only allows a unit to be selected once. Without replacement, sampling is the most commonly used method.

Ex: If a sample of 20 needs be collected from a population of 100. Assign unique numbers to population members and randomly select 20 members with a random generator. Train and test split in ML problems. 

Applications

- Train and test split in machine learning problems

- Lottery methods 

Advantages

Minimum sampling bias as the samples are collected randomly.

Selection of samples is simple as random generators are used.

The results can be generalized due to representativeness.

Disadvantages

The potential availability of all respondents can be costly and time consuming.

Larger sample sizes.

Systematic sampling

In systematic random sampling, the researcher first randomly picks the first item from the population. Then, the researcher will select each nth item from the list. The procedure involved in systematic random sampling is very easy and can be done manually. The results are representative of the population unless certain characteristics of the population are repeated for every nth individual.

Steps in selecting a systematic random sample:

Calculate the sampling interval (the number of observations in the population divided by the number of observations needed for the sample).

Select a random start between 1 and sampling interval

Repeatedly add sampling interval to select subsequent households

Ex: If a sample of 20 needs to be collected from a population of 100. Divide the population into 20 groups with a members of (100/20) = 5. Select a random number from the first group and get every 5th member from the random number.

Applications

Quality Control: The systematic sampling is extensively used in manufacturing industries for statistical quality control of their products. Here a sample is obtained by taking an item from the current production stream at regular intervals.

In Auditing: In auditing the savings accounts, the most natural way to sample a list of accounts to check compliance with accounting procedures.

Advantages

Cost and time efficient.

Spreads the sample more evenly over the population.

Disadvantages

Complete population should be known.

Sample bias If there are periodic patterns within the dataset.

Stratified random sampling

In Stratified random sampling, the entire population is divided into multiple non-overlapping, homogeneous groups (strata) and randomly choose final members from the various strata for research. Members in each of these groups should be distinct so that every member of all groups get equal opportunity to be selected using simple probability. 

There are three types of stratified random sampling-

1. Proportionate Stratified Random Sampling

The sample size of each stratum in this technique is proportionate to the population size of the stratum when viewed against the entire population. For example, you have 3 strata with 10, 20 and 30 population sizes respectively and the sampling fraction is 0.5 then the random samples are 5, 10 and 15 from each stratum respectively.

2. Disproportionate Stratified Random Sampling

The only difference between proportionate and disproportionate stratified random sampling is their sampling fractions. With disproportionate sampling, the different strata have different sampling fractions.

3. Optimal stratified sampling

The size of the strata is proportional to the standard deviation of the variables being studied.

Ex: A company wants to do an employee satisfaction survey and the company has 300k employees and planned to collect a sample of 1000 employees for the survey. So the sample should contain all the levels of employees and from all the locations. So create different strata or groups and select the sample from each strata. 

Advantages

Greater level of representation from all the groups.

If there is homogeneity within strata and heterogeneity between strata, the estimates can be as accurate.

Disadvantages

Requires the knowledge of strata membership.

Might take longer and more expensive

Complex methodology.

Cluster sampling

Cluster sampling divides the population into multiple clusters for research. Researchers then select random groups with a simple random or systematic random sampling technique for data collection and data analysis.

Steps involved in cluster sampling:

Create the clusters from the population data.

Select each cluster as a sampling frame.

Number each cluster.

Select the random clusters. 

After selecting the clusters, either complete clusters will be used for the study or apply the other sampling methods to pick the sample elements from the clusters.

Ex: A researcher wants to conduct an academic performance of engineering students under a particular university. He can divide the entire population into multiple engineering colleges (Which are clusters) and randomly pick up some clusters for the study. 

Types of cluster sampling:

One-stage cluster : From the above example, selecting the entire students from the random engineering colleges is one stage cluster

Two-Stage Cluster: From the same example, picking up the random students from the each cluster by random or systematic sampling is Two-Stage Cluster

Advantages

Saves time and money.

It is very easy to use from the practical standpoint

Larger sample sizes can be used

Disadvantages

High sampling error

May fail to reflect the diversity in the sampling frame

Non-probability sampling

Non-Probability samples are preferred when accuracy in the results is not important. These are inexpensive, easy to run and no frame is required. If a non-probability sample is carried out carefully, then the bias in the results can be reduced.

The main disadvantage of Non-Probability sampling is “dangerous to make inferences about the whole population.”

Convenience sampling 

Convenience sampling is the easiest method of sampling and the participants are selected based on availability and willingness to participate in the survey. The results are prone to significant bias as the sample may not be a representative of population.

Applications

Surveys conducted in social networking sites and offices

Examples: The polls conducted in Facebook or Youtube. The people who are interested in taking the survey or polls will attend the survey and the results may not be accurate as the results are prone to significant bias.

Advantages

It is easy to get the sample

Low cost and participants are readily available

Disadvantages

Can’t generalize the results

Possibility of under or over representation of the population

Significant bias

Quota sampling 

This method is mainly used by market researchers. The researchers divide the survey population into mutually exclusive subgroups. These subgroups are selected with respect to certain known features, traits, or interests. Samples from each subgroup are selected by the researcher.

Quota sampling can be divided into two groups-

Controlled quota sampling involves introduction of certain restrictions in order to limit researcher’s choice of samples.

Uncontrolled quota sampling resembles convenience sampling method in a way that researcher is free to choose sample group members.

Steps involved in Quota Sampling

Divide the population into exclusive sub groups.

Identify the proportion of sub groups in the population.

Select the subjects for each subgroup.

Ensure the sample is the representative of population.

Ex: A painting company wants to do research on one of their products. So the researcher uses the quota sampling methods to pick up painters, builders, agents and retail painting shop owners.

Advantages

Cost effective.

Doesn’t depend on sampling frames.

Allows the researchers to sample a subgroup that is of great interest to the study.

Disadvantages

sample may be overrepresented

Unable to calculate the sampling error

Great potential for researcher bias and the quality of work may suffer due to researcher incompetency and/or lack of experience

Judgement (or Purposive) Sampling

In Judgement (or Purposive) Sampling, a researcher relies on his or her judgment when choosing members of the population to participate in the study. Researchers often believe that they can obtain a representative sample by using sound judgment, which will result in saving time and money.

As the researcher’s knowledge is instrumental in creating a sample in this sampling technique, there are chances that the results obtained will be highly accurate with a minimum margin of error.

Ex: A broadcasting company wants to research one of the TV shows. The researcher has an idea of the target audience and he can choose the members of the population to participate in the study.

Advantages

a  Cost and time effective sampling method.

Allows researchers to approach their target market directly.

Almost real-time results.

Disadvantages

Vulnerability to errors in judgment by researcher

Low level of reliability and high levels of bias

Inability to generalize research findings

Snowball sampling

This method is commonly used in social sciences when investigating hard-to-reach groups. Existing subjects are asked to nominate further subjects known to them, so the sample increases in size like a rolling snowball. For example, when surveying risk behaviors amongst intravenous drug users, participants may be asked to nominate other users to be interviewed.

This sampling method involves primary data sources nominating other potential primary data sources to be used in the research. So the snowball sampling method is based on referrals from initial subjects to generate additional subjects. Therefore, when applying this sampling method members of the sample group are recruited via chain referral.

There are three patterns of Snowball Sampling-

Linear snowball sampling; Recruit only one subject and the subject provides only one referral.

Exponential non-discriminative snowball sampling; Recruit only one subject and the subject provides multiple referrals.

Exponential discriminative snowball sampling; Recruit only one subject and the subject provides multiple referrals. But only one subject is picked up from the referrals.

Ex: Individuals with rare diseases. If a drug company is interested in doing research on the individuals with rare diseases, it may be difficult to find these individuals. So the drug company can find few individuals to participate in the study and request them to refer the individuals from their contacts.

Advantages

Researchers can reach rare subjects in a particular population 

Low-cost and easy to implement

It doesn’t require a recruitment team to recruit the additional subjects

Disadvantages

The sample may not be a representative

Sampling bias may occur

Because the sample is likely to be biased, it can be hard to draw conclusions about the larger population with any confidence.

Sampling errors and biases

             Sampling errors and biases are induced by the sample design. They include:

- Selection bias: When the true selection probabilities differ from those assumed in calculating the results.

- Random sampling error: Random variation in the results due to the elements in the sample being selected at random.

- Non-sampling error

Non-sampling errors are other errors which can impact final survey estimates, caused by problems in data collection, processing, or sample design. Such errors may include:

- Over-coverage: inclusion of data from outside of the population

- Under-coverage: sampling frame does not include elements in the population.

- Measurement error: e.g. when respondents misunderstand a question, or find it difficult to answer

- Processing error: mistakes in data coding

- Non-response or Participation bias: failure to obtain complete data from all selected individuals

Conclusion;

Reducing sampling error is the major goal of any selection technique.

A sample should be big enough to answer the research question, but not so big that the process of sampling becomes uneconomical.

In general, the larger the sample, the smaller the sampling error, and the better job you can do.

Decide the appropriate sampling method based on the study or use case.

Reference;

 • Lance, P.; Hattori, A. (2016). Sampling and Evaluation. Web: MEASURE Evaluation. pp. 6–8, 62–64.

• Salant, Priscilla, I. Dillman, and A. Don. How to conduct your own survey. No. 300.723 S3. 1994.

• Robert M. Groves; et al. (2009). Survey methodology. ISBN 978-0470465462.

• Lohr, Sharon L. Sampling: Design and analysis.

• Särndal, Carl-Erik; Swensson, Bengt; Wretman, Jan. Model Assisted Survey Sampling.

• Scheaffer, Richard L.; William Mendenhal; R. Lyman Ott. (2006). Elementary survey sampling.

• Shahrokh Esfahani, Mohammad; Dougherty, Edward (2014). "Effect of separate sampling on classification accuracy". Bioinformatics. 30 (2): 242–250. doi:10.1093/bioinformatics/btt662. PMID 24257187.

• Scott, A.J.; Wild, C.J. (1986). "Fitting logistic models under case-control or choice-based sampling". Journal of the Royal Statistical Society, Series B. 48 (2): 170–182. JSTOR 2345712.

• https://www.mygreatlearning.com/blog/introduction-to-sampling-techniques/

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Is_it_good_for_men_to_marry_early_now?

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@jaysteve