what is statistics essay

what is statistics essay

The Importance and Applications of Statistics in Various Fields

1. Introduction to Statistics

Not only that, now in every basic field it is essential to learn statistics. After learning the concept of statistics, almost in case of all matters we are applying statistics. First, let’s understand here what is meant by statistics. What do you think when you hear the word statistics? Simply in a few words, listening to the name of statistics you think it is the study of examining the numerical data. But behind that, only in one word it is ‘scary’. Because statistics deals with large data samples but still it will be in exactness level and finally the result will be fine. Our economy is also a factor of our lives. So our needs also increase and the simple comforts of the people do not remain simple.

What is the importance of statistics in various fields? That’s the question we are looking forward to getting the answer. It is obviously seen that statistics is playing a major role in various fields like science, business, commerce, mathematics, agriculture, etc. With the help of statistics, exactness can be measured. We can say that today statistics is the most important subject with regard to research. Collecting data, conducting statistical calculations to deduce the desired result is the measurable branch.

2. Key Concepts and Methods in Statistics

2.1.4 Organization and display of data (ix) Organization of data: Frequency distribution, relative frequency distribution, and cumulative frequency distribution. (x) Display of data: Frequency (histograms, polygons, ogives), relative frequency (percent) histograms, polygons, ogives, bar charts, stem-and-leaf displays, pie charts, pictograms, and scatterplots.

2.1.3 Data collection techniques (vii) Data collection methods: Surveys, observational studies, and experiments. (viii) Sampling methods/designs: Simple random sampling, stratified random sampling, systematic random sampling, cluster sampling, judgment sampling, quota sampling, convenience sampling, etc.

2.1.2 Scales of measurements and levels of data (vi) Scales of measurements/types of data (a) Nominal (Quality) Data: Data that can be classified into categories and are distinguished only by differences in kind or quality. (b) Ordinal (Rank) Data: Nominal data that can be arranged in an ordered format. (c) Interval (Equal-unit spacing) Data: The data are ordinal, and that adjacent data values are equidistant. (d) Ratio Data: The difference between two data values is meaningful because there exists a true or natural zero or origin.

2.1.1 Concepts and definitions (i) Population: All items, objects, individuals, or subjects of which information or data will or can be collected. (ii) Sample: A representative subset of the population. (iii) Descriptive statistics: The graphical and numerical tools used to summarize and describe the main features of the data under analysis. (iv) Inferential statistics: The branch of statistics that uses sample data to make inferences or generalizations about the population. (v) Basic structure of a statistical study: Formulate a research question or statement, collect data, use descriptive statistics to explore the data, and ultimately achieve a conclusion.

2.1. Key concepts in statistics

3. Applications of Statistics in Business and Economics

The manager must be able to apply various business statistics tools or methods to determine what the data mean in order to analyze, summarize, and draw conclusions from the data and projections of the future. The key basic business statistics tools one would use include mean, standard deviation, single variable regression, multi-variable regression, analysis of variance (ANOVA), analysis of exception (ANOVA), coefficient, and inter-coefficient. Businesses use statistics in market research to measure customer satisfaction. Customer relationship management uses statistics to identify customer habits. Understanding business data will help managers create global strategies that can be analyzed and tested. Marketing also uses statistics to identify target markets, their size, and the buyers of their products. In addition to making you more marketable, field-specific knowledge can help you stand out by making you a unique candidate in your field.

Statistics provides numerous techniques, methods, and tools that are useful for various business decisions. Business statistics is the application of statistical techniques to the business and economics problems relating to, e.g., marketing, distribution, banking, insurance, industry, human resource management, and financial management. It is the study of these subjects using statistical tools and techniques. It only deals with the techniques used for estimation and prediction purposes in the field of business and economics. Statistics play an important role in business. It helps to guide the managerial process. Data and numbers are used all the time in business to plan and manage.

4. Impact of Statistics in Healthcare and Medicine

Physicians need diagnostic test results to diagnose and manage diseases. Diagnostic statistics can help the patient to determine their own level of appropriate care. Different topics have focused on symptom evaluation based on collected data. Physicians will prescribe a treatment based on the patients’ diagnosis, knowledge from past treatments of similar patients, and the estimation of risk. The statin decision support trial includes these data and applies to analyze the points. If a treatment is effective, the medical question is which combination is best. The topic for the practical evaluation of combined treatments using referred to data and statistical model has been added. Finally, given the rise in the number of incidence of certain diseases, the monitoring of disease counts is important. The disease monitoring case study concerns both the rates and intensity of the count time series modal components.

Statistics has been an important key discipline in every field of life science. This chapter of the Statistics Book contains the topics that are used to solve everyday problems in the field of healthcare and medicine: medical tests, prevention, treatment comparison, epidemic incidence, survival of patients, health care with costs or global measurement devices. The classical methods have been extended and improved reflecting the needs of statisticians, medical researchers, and doctors. Wearable devices can be used to collect data at a high frequency and used to monitor heart rate, blood pressure, or blood glucose level. To analyze the data, a preprocessing step is required to aggregate the raw data point to a meaningful measurement. These high-frequency measurements can be used, for instance, to estimate health status. A survival analysis methodology is also required to assess the survival of patients.

5. Ethical Considerations in Statistical Analysis

Five hundred years ago, our view of the universe was without any statistical references. The concepts of randomness, degrees of uncertainty, and estimates and predictions from data did not exist. Galileo, an earlier champion of the significance of the investigator’s role of observation, argued vigorously in calling for the use of probabilities; and he tried to persuade many interested parties to espouse this approach. But Galileo was rebuffed both by philosophers and even some of the scientists of his day because they were involved in either dogmatic theologies or incipient deterministic models of science. A similar kind of controversy applies in the quest to understand the consideration and application of present-day statistical methods. The infinite t lion of statistical ideas, inferences and consequences are present. It is important to appreciate those concepts which have been proven to be of substantial lasting importance. The present paper suggests a few concepts.

Dhan R. Kalwani and Eon S. Sinclair Statistical methodologies inform conclusions regarding happenings in both physical and social science areas. The hard sciences and technology areas, like business, medicine, the computer sciences, and the environmental and management sciences, are enjoying a plethora of new and challenging applications of statistical methods. It is as if the dam of new statistical applications has given way and we are now living in the deluge of new applications. Prominent examples of statistical applications include DNA fingerprinting in the criminal justice area, development of econometric hypotheses regarding the validity of the supply and demand model in the antitrust case, and an analysis of the FT-SE 100 stock returns in a study of statistical characteristics.