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INTRODUCTION TO STATISTICS.pptx

  1. INTRODUCTION TO STATISTICS DR. Manish Agarwal
  2. What is Statistics? Statistics is the science of conducting studies to collect, organize, summarize, analyze, and draw conclusions from data.
  3. What is Data? Definition: Facts or figures, which are numerical or otherwise, collected with a definite purpose are called data. Everyday we come across a lot of information in the form of facts, numerical figures, tables, graphs, etc. These are provided by newspapers, televisions, magazines and other means of communication. These may relate to cricket batting or bowling averages, profits of a company, temperatures of cities, expenditures in various sectors of a five year plan, polling results, and so on. These facts or figures, which are numerical or otherwise, collected with a definite purpose are called data.
  4. Characteristics of statistics 1. Statistics are the aggregates of facts: It means a single figure is not statistics. For example, national income of a country for a single year is not statistics but the same for two or more years is statistics. 2. Statistics are affected by a number of factors: For example, sale of a product depends on a number of factors such as its price, quality, competition, the income of the consumers, and so on. 3. Statistics must be reasonably accurate: Wrong figures, if analyzed, will lead to erroneous conclusions. Hence, it is necessary that conclusions must be based on accurate figures. 4. Statistics must be collected in a systematic manner: If data are collected in a haphazard manner, they will not be reliable and will lead to misleading conclusions. 5. Collected in a systematic manner for a pre-determined purpose 6. Lastly, Statistics should be placed in relation to each other: If one collects data unrelated to each other, then such data will be confusing and will not lead to any logical conclusions. Data should be comparable over time and over space.
  5. • Condensation: Explain huge mass of data with few observations. • Comparison: Helps in comparing two set of data for better decision making • Forecasting: With the help of past data we can predict the future outcomes e.g. regression and time series analysis. • Estimation: We can estimate about population characteristics with the help of sample study. • Hypothesis Testing: A statistical hypothesis is some statement about the probability distribution, characterizing a population on the basis of the information available from the sample observations. In the formulation and testing of hypothesis, statistical methods are extremely useful. Whether crop yield has increased because of the use of new fertilizer or whether the new medicine is effective in eliminating a particular disease are some examples of statements of hypothesis and these are tested by proper statistical tools. Functions of Statistics:
  6. Scope of Statistics • Statistics and Industry: Statistics is widely used in many industries. In industries, control charts are widely used to maintain a certain quality level. In production engineering, to find whether the product is conforming to specifications or not, statistical tools, namely inspection plans, control charts, etc., are of extreme importance. • Statistics and Commerce: Statistics are lifeblood of successful commerce. Any businessman cannot afford to either by under stocking or having overstock of his goods. In the beginning he estimates the demand for his goods and then takes steps to adjust with his output or purchases. Thus statistics is indispensable in business and commerce. • Statistics and Economics: statistical tools are immensely useful in solving many economic problems such as wages, prices, production, distribution of income and wealth and so on. Statistical tools like Index numbers, time series Analysis, Estimation theory, Testing Statistical Hypothesis are extensively used in economics.
  7. Scope of Statistics cont… • Statistics and Education: Statistics is widely used in education. Research has become a common feature in all branches of activities. Statistics is necessary for the formulation of policies to start new course, consideration of facilities available for new courses etc. There are many people engaged in research work to test the past knowledge and evolve new knowledge. These are possible only through statistics. • Statistics and Planning: The government are seeking the help of planning for efficient working, for the formulation of policy decisions and execution of the same. In order to achieve its goals, the statistical data relating to production, consumption, demand, supply, prices, investments, income expenditure etc and various advanced statistical techniques for processing, analyzing and interpreting such complex data are of importance. • Statistics and Medicine: In Medical sciences, statistical tools are widely used. In order to test the efficiency of a new drug or medicine, t - test is used. More and more applications of statistics are at present used in clinical investigation.
  8. LIMITATIONS OF STATISITICS • Statistics is not suitable to the study of qualitative phenomenon: Since statistics is basically a science and deals with a set of numerical data, it is applicable to the study of only these subjects of enquiry, which can be expressed in terms of quantitative measurements. As a matter of fact, qualitative phenomenon like honesty, poverty, beauty, intelligence etc, cannot be expressed numerically and any statistical analysis cannot be directly applied on these qualitative phenomenon's. Nevertheless, statistical techniques may be applied indirectly by first reducing the qualitative expressions to accurate quantitative terms. For example, the intelligence of a group of students can be studied on the basis of their marks in a particular examination. • Statistics does not study individuals: Statistics does not give any specific importance to the individual items, in fact it deals with an aggregate of objects. Individual items, when they are taken individually do not constitute any statistical data and do not serve any purpose for any statistical enquiry.
  9. LIMITATIONS OF STATISITICS cont.. • Statistical laws are not exact: It is well known that mathematical and physical sciences are exact. But statistical laws are not exact and statistical laws are only approximations. Statistical conclusions are not universally true. They are true only on an average. • Statistics table may be misused: Statistics must be used only by experts; otherwise, statistical methods are the most dangerous tools on the hands of the inexpert. The use of statistical tools by the inexperienced and un traced persons might lead to wrong conclusions. Statistics can be easily misused by quoting wrong figures of data. • Statistics is only, one of the methods of studying a problem: Statistical method do not provide complete solution of the problems because problems are to be studied taking the background of the countries culture, philosophy or religion into consideration. Thus the statistical study should be supplemented by other evidences.
  10. Primary Data Vs Secondary Data Primary Data Primary data is the data that is collected for the first time through personal experiences or evidence, particularly for research. It is also described as raw data or first-hand information. The mode of assembling the information is costly. The data is mostly collected through observations, physical testing, mailed questionnaires, surveys, personal interviews, telephonic interviews, case studies, and focus groups, etc.
  11. Primary Data Vs Secondary Data Secondary Data Secondary data is a second-hand data that is already collected and recorded by some researchers for their purpose, and not for the current research problem. It is accessible in the form of data collected from different sources such as government publications, censuses, internal records of the organisation, books, journal articles, websites and reports, etc. This method of gathering data is affordable, readily available, and saves cost and time. However, the one disadvantage is that the information assembled is for some other purpose and may not meet the present research purpose or may not be accurate.
  12. Discrete Vs continuous data • Discrete data (countable) is information that can only take certain values. These values don’t have to be whole numbers but they are fixed values – such as shoe size, number of teeth, number of kids, etc. • Discrete data includes discrete variables that are finite, numeric, countable, and non-negative integers (5, 10, 15, and so on). • Continuous data (measurable) is data that can take any value. Height, weight, temperature and length are all examples of continuous data. • Continuous data changes over time and can have different values at different time intervals like weight of a person.
  13. Types of statistics • Descriptive statistics – Methods of organizing, summarizing, and presenting data in an informative way • Inferential statistics – The methods used to determine something about a population on the basis of a sample • Population –The entire set of individuals or objects of interest or the measurements obtained from all individuals or objects of interest • Sample – A portion, or part, of the population of interest
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