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## Advantages of Stratified Random Sampling

Stratified random sampling has advantages when compared to simple random sampling.

### Accurately Reflects Population Studied

Stratified random sampling accurately reflects the population being studied because researchers are stratifying the entire population before applying random sampling methods. In short, it ensures each subgroup within the population receives proper representation within the sample. As a result, stratified random sampling provides better coverage of the population since the researchers have control over the subgroups to ensure all of them are represented in the sampling.

With simple random sampling, there isn’t any guarantee that any particular subgroup or type of person is chosen. In our earlier example of the university students, using simple random sampling to procure a sample of 100 from the population might result in the selection of only 25 male undergraduates or only 25% of the total population. Also, 35 female graduate students might be selected (35% of the population) resulting in under-representation of male undergraduates and over-representation of female graduate students. Any errors in the representation of the population have the potential to diminish the accuracy of the study.

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## Types of Statistical Data:

Information on any field, when expressed qualitatively and/or quantitatively, is called data and they are usually classified into two main cate­gories—primary and secondary data, depending on their origin or source.

Information when collec­ted directly from the desired field for the use of a predetermined purpose is called the primary data e.g., heights and weights of the students in a class.

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It can thus be used with much confidence because of its direct nature of collection. The primary data are usually published by the autho­rities who are directly responsible for its collection. However, it requires enough manpower, time and money to make the process successful.

Secondary data, on the other hand, are the data already collected by an individual or an agency for a specific purpose and used afterwards for a number of other purposes. The data so obtained from that origin are then conveniently compiled up by an investigator to meet his or her own specific needs. Such data are usually collected by an authorised agency for one particular purpose and then it is officially published and again used by other individuals or agencies to serve their own purposes and in that sense these data are not original in nature.

For example, we often’ use Census (data collected every after ten years with the government effort) reports to accomplish, support and supple­ment our studies. These are, no doubt, secondary data used by the researchers of various fields.

The most important and remarkable advantage here is that it requires less manpower and time and as a result less costly to complete the entire procedure. But, in practice, it frequently contains a number of errors due to erroneous transcription, faulty rounding-off (up or down), etc., and, therefore, less dependable in nature for the researchers.

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The investigators and the scholars working with them should therefore be much careful while using them in their own fields. It is, therefore, quite clear that the data which are initially primary in nature at the origin for one use becomes secondary in qualities and character for other uses.

Therefore, the distinction between primary and secondary data is one of degree only. A parti­cular data may be primary in the hands of data collecting authority but may be secondary to other people using them afterwards. Prof. H. Secrist in this context says: “The distinction between primary and secondary data is largely one of degree. Data which are secondary in the hands of one party may be primary in the hands of another.”

However, the method of collection of primary data and secondary data must not be identical in nature because, in the former case data are collected originally while, in the latter case, data are to be taken up in the nature of compilation.

There exists various methods for the collection of the primary and secondary data. Choice of the exact method depends largely on the nature, object and scope of statistical investigation.

#### Advantages of Primary Data:

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It is usually preferable to use primary data because of the following reasons: First, it generally contains a detailed description and information of the definition for the terms used. Secondly, since secondary data are second-hand data or ‘finished products’, an element of error may creep in after­wards.

This may then give some misleading infor­mation. Primary data cannot have such errors. Thirdly, in the primary data precise definition of the terms used is given and the scope of the data is clearly mentioned. Finally, collecting primary data often include the method or procedure followed and any approximation used so that one can find its limitations. On the contrary, secondary data usually lack such information.

Despite these advantages of primary data, secondary data are extensively used particularly when a large number of items are required.

The secondary data seems to be of minor importance, specially when collection of primary data is much expensive and time-consuming.

Secondary data invariably give less meaning of the statistics and frequently present no expla­nation other than the captions and footnotes in the tables. In fact, some information are usually suppressed in secondary data.

#### Advantages of Secondary Data:

Practically, there are various advantages in using secondary data. First, cost of collection of data is less. That is why data produced by the Government, com­panies and various organisations are readily available. Secondly, one obtains a great variety of data on a wide range of subjects.

Thirdly, much of the secondary data available has been collected for many years and, therefore, it can be used to study the trends. Fourthly and most importantly, secondary data is of great value to the government, business world and industry and also for research organisations. Again, secondary data help the government in making present policy decisions and also planning for future economic policies.

#### Limitations of Secondary Data:

In spite of all these advantages of secondary data, one must use it with enough caution. First, the method employed for the collection of such data is often unsatis­factory. That is why, secondary data in most cases, is subject to transcribing errors (i.e., errors occurring due to wrong transcriptions of the primary data). Secondly, secondary data are really mere estimates and not the facts.

In view of this, secondary data suffer from estimating errors. Thirdly, scrutiny of the secondary data is obviously essential since errors may creep in due to unwanted bias. This is because of the fact that often fictitious figures are recorded unknowingly in secondary data. In this sense, secondary data are not only inaccurate but also incomplete and inadequate. Without detailed scrutiny of the secondary data one must not be advised to use them.

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## The main advantages of statistics are:

• they are familiar to library staff and managers
• they can be analysed relatively quickly
• information is collected in a standardised way
• they are usually straightforward to analyse
• they overcome the difficulties of encouraging participation by users
• they are often required and respected by decision-makers within the institution and beyond eg funders, government
• they support qualitative data obtained from questionnaires, interviews etc with ‘hard facts’
• they are useful for benchmarking purposes.

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## Advantages of Statistics in Performance

One role of statistics in business is informing a manager working on employee performance management. A manager collects data about employee productivity, such as the number of tasks completed or the number of units produced. He or she must analyze data to find ways in which an employee should improve to achieve maximum productivity. Many companies also collect data about employee engagement and happiness on the job, which can be tracked to not only keep workers motivated but ensure they don’t leave for other positions elsewhere.

For example, if a manager finds that an employee’s number of finished outputs drops by 20 percent every Friday, he or she should communicate with the employee, setting the expectation that his or her output will remain above a minimum level every day of the work week.

Many companies will also compile aggregate statistics about employee performance. If a company finds that employees overall are doing less work right before or after the weekend, its managers will want to consider ways to either motivate employees or, if it turns out to be due to external factors, provide them with alternative tasks they can do during downtimes. Companies may want to avoid collecting too much data about employee activities, however, since it may come off as creepy to workers.

## Evaluating Alternative Scenarios

Beyond managing the performance of her own workers, a manager participates in joint decision making with other managers. Statistics help the managers to compare alternative scenarios and choose the best option for the company. The team must decide which software to use for automating the customer ordering process.

They consider which software products have been successfully used by competitors and choose the most popular one, or they might find how many orders that an ordering system can process on average daily. The team collects performance data from software makers and independent sources, such as trade magazines, to inform their purchasing decisions.

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## The Importance of Data Collection

Collecting data to use in statistics, or summarizing the data, is only an advantage in business if a manager uses a logical approach and collects and reports data in an ethical manner. For example, he might use statistics to determine if sales levels the company achieved for the last few products launched were even close to projected sales levels. He might decide that the least-performing product needs extra investment or perhaps the company should shift resources from that product to a new product.

In some cases, it might be necessary to anonymize customer data or strip out unimportant confidential parts to reduce the risk of a data breach or abuses by employees or data consultants. Privacy laws also increasingly govern how companies can use or store personal data, so it’s important to make sure your business follows the rules in jurisdictions where it’s active.

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## Statistics in Research and Development

A company also uses statistics in market research and product development, using different surveys, such as random samples of consumers, to gauge the market for a proposed product. A manager conducts surveys to determine if there is sufficient demand among target consumers.

Survey results might justify spending on developing the product. A product launch decision might also include a break-even analysis, such as finding out what percentage of consumers must try a new product for it to be successful.

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## What are the advantages of statistics in economics?

Statistics for economics concerns itself with the collection, processing, and analysis of specific economic data. It helps us understand and analyze economic theories and denote correlations between variables such as demand, supply, price, output etc.

## How do we use statistics in everyday life?

Statistics are widely used in consumer goods products. The reason is consumer goods are daily used products. The business use statistics to calculate which consumer goods are available in the store or not. They also used stats to find out which store needs the consumer goods and when to ship the products.

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## What are the main advantages of statistics?

Statistical knowledge helps you use the proper methods to collect the data, employ the correct analyses, and effectively present the results. Statistics is a crucial process behind how we make discoveries in science, make decisions based on data, and make predictions.

## What are the advantages of statistical analysis?

The statistical analysis brings in numerous benefits to make the best usage of the vast data available, such as assisting in market research, product development, mapping out the company’s growth rate, improve the efficiency of the company, etc.