# Relationship between statistics and management

This paper also examines the relationship between statistical power, field- based empirical research in Production and Operations Management (POM) and. With the help of careful data cleaning and after removing the outliers, statistics can identify the link and association between two variables. For an example: The . This paper also examines the relationship between statistical power, analysis of 28 articles ( statistical tests) in the Journal of Operations Management and .

Statistical techniques and analysis are used for forecasting the future of the economy. Time series like moving averages, indicators like inflation index are statistical methods. We can consider statistics as the backbone of economics. Statistics is broadly categorized into two parts based on their functions a Descriptive Statistics and b Inferential Statistics Descriptive Statistics: Descriptive Statistics involves collecting, organizing, summarizing and presenting data.

It is useful in clinical research, while communicating the results with experiments. The methods used in this statistics is preparing tables, drawing graphs, measuring central tendency and the variation of the data from the central value.

Inferential Statistics involve making inference, hypothesis testing, relation determination and making predictions.

The data obtained in descriptive statistics is analyzed and a valid inference is made out of it for effective decision making for managers and professionals.

In this type deductions and conclusions are made regarding the population under study by collecting a sample from the population. Statistics are aggregate of facts: A single figure cannot be analyzed. Statistics are affected by great extent by a multiplicity of causes: A number of causes affect statistics in a particular field of enquiry, e. Statistics are numerically expressed: Statistics is concerned essentially with facts expressed in numerical form with their quantitative details but not qualitative descriptions.

Statistics do not trust such statement without proper numerical data to prove it. Statistics are enumerated or estimated with required degree of accuracy: In statistics the data is collected from field or estimated with proper degree of accuracy.

The degree of accuracy depends on the purpose of the study. The average height of students in a class is measured in centimeter where accuracy is not that important, but the length of screw used in automobile is measured in millimeter because accuracy is important in this case.

Statistics should be collected in a systematic manner for a predetermined purpose: The required fact should be collected with planning and with suitable scientific methods.

If it is not done scientifically and properly it may give wrong or misleading inferences. If there is no predetermined purpose, all the efforts in collecting the figures and collection of indiscriminate data may be waste of time and resources. Statistics should be capable of being placed in relation to each other: The collected figure should be comparable and well-connected so that analyzation of the collected data is possible. Thus in statistics similar related quantities should be compared.

To present facts in a definite form: Using statistics we can collect and organize data. Using organize data its analysis is carried out to verify the fact. To simplify unwieldy and complex mass data: Statistical methods reduce complexity of data by choosing proper sample.

Studying the sample and applying statistical method to this sample, the huge and complex mass data can be understood. To use it for comparisons: The purpose of data collection can be fulfilled only when they are compared with others of the same type.

## [Relationship of statistics and data management in clinical trials].

To bring out trends and tendencies in data: The data is collected and organized, then using techniques like moving averages, time series, interpolation and extrapolation the trend can be studied which is useful for forecasting. To provide guidance in the formulation of policies and take decision: Government and businesses used statistics to take decision by analyzing the data.

Managers can used statistical techniques to arrive at a decision and can support it with necessary statistical data. To enlarge individual experience: The knowledge collecting ability of human being is limited to its senses.

### "Statistical Power in Operations Management Research" by Rohit Verma and John C. Goodale

To quote a few of the many applications across functions, A Marketing manager needs to gather and analyze a large amount of data pertaining to market dynamics and target customers.

Ideally, marketing strategy depends up on the outcomes of a Market research, which involves statistical methods for collecting and analyzing data, application of sampling techniques and evaluating the effect of various marketing strategies.

• Introduction to Statistics
• The Importance of Statistics in Management Decision Making
• Importance of Statistics for Managers

A production manager would ideally use Statistical Process Control techniques to improve productivity and quality. Knowledge and application of Control Charts, Sampling techniques and Probability Distributions ensures better processes and products. This also leads to the reduction in production cost and higher profits. A HR manager would be interested in identifying the best approach to train employees and evaluate the impact of training.

There is a need to measure attrition and understand the underlying factors. For a Finance manager, crunching financial data and using financial techniques is an integral part of day-to-day job. Knowledge of Statistics enhances competency and proficiency of a manager as a researcher and therefore provides an edge.

Professionally trained and skilled graduates are encouraged to establish ventures, create jobs and create value. Quantitative analysis aids in providing an objective, factual underpinning of situations and responses.

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