Sampling Models In Data Science

Why Do We Need Sampling?  We do Know in Inferential Statistics we deal with samplings that we take a sample data not the population data. This is because the population data is too large to handle and very complex to handle. 

Sampling Funnel is that it performs an analysis of the population. In general, we don't have access to perform any analysis of the population. So here with the use of sampling funnel, we can actually perform analysis over the population to know positive and negative areas of that product in business analytics.

To perform a general analysis of a particular product, it is difficult to analyze the whole population, because the use of a particular product/service by the people is widely spread all across the globe. It is difficult to spot out the people who are using a particular product/service. So we use sampling funnel method which we implement in data science and it can be conducted in the form of a survey to collect positive and negative feedback from the population.

Here the process of performing analysis which I have listed in the following serial steps 

Population

Sampling Frame

SRS (Simple Random Sampling) and finally 

Sample

The term population refers to a whole and the term sampling frame is that identifying the high use of product/service in various geographies. And the next serial step is Simple random sample, it is said to be known as picking up people to get feedback randomly (Blindfolded). Finally, by deriving the report followed by the serial steps described by the sampling funnel to get a sample. So this why we implement sampling funnel in Data science.

In short, Data science can be used extremely at exit poll results.

For your better understanding to gain practical knowledge and for your effective learning, one should be dedicatedly allocated time to put it into practice. An example of IPhone will be the right one to pick and to demonstrate about the process of performing sampling funnel. If you look right back to the days, we may find those days where people used to stand in a queue out of the store to purchase a major mobile brand “Apple Iphone”. And indeed it`s difficult to perform a survey with a questionnaire. Collecting opinions & feedback by asking people with a loaded set of questions will no longer work. Even to perform post analysis and to retrieve the outcome of the huge data, it is messy to understand and to conclude the quality of the product and its performance.  

Many tricks & techniques and many logics are incubated to perform the required analysis ensuring all the systems are meeting the needs  of the task. 

Suggestion box: An aspiring data scientist must learn plenty of things and those concepts can only be learned with the help of rightly chosen training and certification course. The guidance provided by data science course in mumbai will help you clear several doubts regarding this relatively new and challenging career path.

Scope of Data Science in Human Resources

Now, since Data Science has extended its long tentacles into almost all the fields be it information technology, healthcare, marketing, etc, its about time you think of human resource too. Human Resource is a vast field and with the help of Data Science, you can optimize your workflow to increase your productivity and profitability.

You may think, “What has Data Science got to do with Human Resource?”

Well, firstly the HR managers can use the techniques of Data Science to sort through and pick the best candidates suiting their needs, saving valuable time.

Secondly, we are living in a digital world and the need to keep up with trending concepts and technology is more than ever. Therefore, it is an inevitable fact that Data Science has to extend its arms to Human Resource.

Human Resource forms the kernel of any organization as the entire development and growth depends on their actions. Data Science aids the selection of the most suitable candidates for any business organization by analysing the data available at the company’s disposal.

It is a tedious task for HR managers to go through thousands of resumes in a short span of time and this is where Data Science comes to play. With Data Science it is possible to overcome problems encircling the selections procedure and choose the most eligible candidates without any bias.

Data Science helps to report on the number of recruitments/applications/qualified candidates/and to determine how many people you can actually employ.

You can also keep track of service and salaries data which will help you to ensure that you’re paying the right people the right amount.

You will have access to the turnover data from dozens of similar or competitive organizations which will help you to compare your number with theirs.

One more key area which requires the expertise of Data Science is employee retention. With the help of predictive analysis Data Scientists will be able to predict if an employee is on the verge of quitting his/her job and take suitable action to make sure they stay. You will be able to track their all your employee work patterns, gaining valuable insights into who is working overtime and who is not.

With Data Science at the helm of things, HR managers will find it a lot easier to manage the workflow, recruitment process, employee retention and many more.

Get yourself trained in Data Science course in mumbai from the best in business at ExcelR to explore the world of opportunities that lie ahead of you.