B.Com 1st Year Introductory Long Question Answer Notes

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B.Com 1st Year Introductory Long Question Answer Notes
B.Com 1st Year Introductory Long Question Answer Notes

Q.1. ‘Statistics may be defined as the collection, presentation, analysis and interpretation of numerical data’. Examine this statement.

Or ‘Statistics are numerical statement of facts but all facts numerically stated are not statistics’. Discuss and point out briefly. (2015)

Or What do you mean by statistics? Give its characteristics.

Ans. In modern times, statistics is used in the form of statistical method and numerical data. In singular sense, it is defined as the science of the study of the principles and methods of collecting, presenting, analysing and interpreting the numerical data. Thus, statistics is the science dealing with principles and methods of estimating or enumerating the facts and figures. In the plural sense statistics is defined as the numerical facts or the numerical statement of facts in any department of enquiry placed in relation to each other.

‘Statistics means aggregate of facts affected to a market extent by multiplicity of causes, numerically expressed, enumerated or estimated according to reasonable standards of accuracy, collected in a systematic manner for a predetermined purpose and placed in relation to each other. —Prof. Horace Secrist

In actual, statistics are numerical statement of facts, but all facts numerically stated are not statistics. Horace Secrist has described some important characteristics in relation to statistics data. According to him, those can be data only in which the following characteristics exist:

1. Aggregates of Facts: Single facts and figures are not statistics. This is because they are incapable of comparison but aggregates of figures relating to age, number of students, births, deaths, purchases, etc. are statistics as they can be studied in relation to each other and are capable of comparison. Statistics must be studied in relation to time, place, frequency of occurrence, etc. so as to help in decision making.

2. Numerically Expressed: Qualitative expressions are not statistics. Qualities like good, bad, young, old, etc. cannot constitute statistics unless these attributes are quantitatively expressed.

3. Affected ten Marked sent by Multiplicity of Causes: Statistical facts are usually not affected by a single cause but a large variety of factors at the same time. Price statistics are affected by market conditions like supply, demands, import, export, circulation of currency and other factors.

Number of students coming from different strata of society will be affected by social conditions that are prevailing in the area like income of the household, national policy, social environmental

4. Enumerated or Estimated According to Reasonable Standards of Accuracy: Numerically expressed facts and figures are supposed to be accurate and precise. They are enumerated or estimated by experts. The degree of accuracy required in such enumeration depends upon the purpose on the statistics are collected. It also depends on the nature of the problem for which the data are requncu to be collected. Thus, types of the enquiries and nature of problem decide the degree of accuracy.

5. Collected in Systematic Manner: Data are collected in systematic manner so as to ensure fair degree of accuracy and to conform the reasonable standard. If the data is collected in hapnazard manner, the purpose of collecting the data gets disturbed.

6. Collected for a Pre-determined Purpose: Statistics are collected to serve a particular purpose which usually is pre-determined. If this is not like that, the usefulness of data would become negligible and efforts are put in to collect the data.

7. Placed in Relation to Each Other: An important characteristic of data is that data should be comparable. If the data is not comparable, they would lose a large part of their value and the efforts in collecting them may not prove to be as useful as the requirements may be. It is therefore necessary that the data should be homogeneous so as to make them comparable and more useful. All this help the users to place them in relation to each other and make use of them as per the requirement.

Thus, it can be clearly stated that Statistics are numerical statement of facts but all facts numerically stated are not statistics. This is because, all the above stated characteristics are not found in facts so they cannot be called as statistical data.

Q.2. Discuss the importance, limitations and scope of statistics. 

Or Define statistics and discuss its scope and limitations.

Or ‘Statistics is not science, it is a scientific method’. Discuss critically explaining the scope, utility and limitations of statistics.(2014) 

Ans. Statistics is not science but it is concerned with scientific methods for collecting organising summarising, presenting and analysing data, as well as drawing valid conclusions and making reasonable decision on the basis of such analysis. In a narrow sense, the term is used to denote that data themselves or number derived from the data as for example, averages.

Importance of Statistics: Refer to Section-A, Q.8.

The basic concepts of statistics are the same in all fields; however, these concepts are emphasised and utilised somewhat differently in each of the branches of knowledge. Despite the fact that statistics performs some very important functions in collecting and analysing facts regarding social and economic problems, it is not without limitations.

Limitations of Statistics: Its limitations are as follows:

1. Statistics does not Study Individuals: An individual figure, howsoever important it cannot become a part of a statistical study. For example, the marks secured by Deepanshu in an examination will not be studied in statistics, even if he has topped in the examination because it is an individual item. It is the marks secured by a group of students that would constitute statistics and be studied.

2. Statistics does not Study Qualitative Aspects: Statistics studies only those aspects of human or social behaviour that can be expressed in numbers.

3. Statistical Results are True only in General and on an Average: Statistical laws are not exact laws like mathematical, chemical or physical laws. They are derived by taking a majority of cases and are not true for every individual.

4. Statistics can be Misused by Ignorant or Wrongly Motivated Persons: The data placed in the hands of an inexpert may lead to fallacious results. The figures may be stated without their context and thus fallacious conclusions may be reached. The argument that ‘in a country 20,000 vaccinated persons died of small-pox, therefore vaccination is useless’ is statistically defective, since we are not told what percentage of the persons who were not vaccinated died. The argument may be applied to a phenomenon other than the one to which they really relate. Also figures relating to part of a group are taken as relating to the whole or figures favourable to an argument are stated omitting the other side. The data may be inaccurately compiled, deliberately manipulated and unscientifically interpreted and made to produce a false statistical argument. The number of road accidents in Delhi in 2004 may be more than in 2002. However, there may be no need for any alarm. The increase may be due to population increase and wider use of automobiles. Thus statistics are capable of being conveniently interpreted and generally there is distrust of statistics in the mind of the public..

Sometimes certain basic results are attributed to statistics, as making forecasts for sales on the basis of past statistics. The decision regarding future sales is not statistical as it cannot be entirely based on datą, It may be true on the average but not always. There are many allied factors influencing the forecast. Circumstances can also change. Thus statistics is only a helping tool and it is a means to achieve some end.

5. Statistics cannot Prove Anything: Statistics only describe a phenomenon quantitatively, classify it into parts, summarise a fact relating to each part and prepare the ground for logical inference. But the inference must be drawn to the appropriate surroundings which may be personal, political or social otherwise would not be valid. Statistics cannot give a result that can be an end in itself as is possible in many physical sciences. A drug to cure a disease is discovered by a biochemist. A statistician is in a position to tell whether the tests carried out by him as to the efficiency of a drug are adequate or not. It is obvious that statistics plays an auxiliary role and not a basic one.

Scope of Statistics: Refer to Section-A, Q.10.

Q.3. Write a note on misuse and distrust of statistics.

Or What do you mean by distrust of statistics?(2016)

Ans. Misuse and Distrust of Statistics: As we know that statistical data and statistical techniques have emerged as most important tools of mankind in its social, political, economic and business life but even then, there exists a great prejudice or personal feeling against statistics.

Distrust of statistics means that there exists a lack of confidence in statistical data and statistical methods. There are many damaging statements that are levelled against statistics. The opinions regarding the distrust of statistics are:

1. First Opinion: Under it, statisticians fully trust on the statistical conclusions. In statistics, data is collected, edited, analysed and interpreted on the basis of scientific statistical Methods which are absolute and justified. In this it is said that, ‘Figures do not lie or the conclusions drawn on the basis of are true!

2 . Second Opinion: According to this, statistical conclusions are considered to be doubtful and hence, figures are tissues falsehood. According to Diseraeli, ‘There are three kinds of lies-lies, damned lies and statistics. secret language of statistics is employed to sensationalist, inflate, confuse and over simplify.

Thus, it can be said that:

(a) Statistics can prove or disprove anything.

(b) Statistics is another form of lying.

(c) There are three kinds of lies-lies damned lies and statistics.

There are various reasons for distrust in statistics: 

(a) Since, the figures carry no weight, the people believe them easily. 

(b) They can be used to support false as well as true statement. 

(C) They are just tools which can be used or abused. 

(d) Data can be collected in a false way then one cannot differentiate between real data and fictitious data. 

(e) Data is a group of numbers and numbers stand for perfection and accuracy. So, accurate numbers attract the attention of audience or everybody. 

(F) Blind trust on figures results in wrong conclusions and thus creates distrust. check the suitability of data to the problem and the situation under study. 

(g) Sometimes, investigator himself twists the data so as to obtain the desired results.

Thus, it is easy to say that ‘statistics can prove anything’. In fact, figures do not lie but liars ligure. This is a testimonial to the misuse of statistics. The misuse of statistical data can be explained as:

1. Inappropriate Comparison: Wrong results will be obtained by comparing statistics which are essentially not comparable.

2. Misuse of Statistical Methods: Wrong handling of statistical methods produce a wrong and misleading picture.

3. Ambiguous and Variable Definitions: The concept and the definitions for the collection of data should be clear and definite over a period of time otherwise the results obtained may be doubtful, misleading and wrong.

4. Bias: The main cause of misuse of statistics is bias. If the investigator is prejudiced, then the conclusion produced by him may not be fair.

5. One Sided Argument or Misinterpretation: Sometimes an investigator collects data according to his argument and draw conclusion accordingly which is one sided and wrong.

6. Unrepresentative and inadequate Material: The conclusion drawn on the basis of unrepresentative and inadequate material may be doubtful. Such statistics do not represent the entire area of investigation that may lead to insufficient and the misleading results.

Thus, statistics are the live tools which could either be used or misused. So, statistical tools are delicate instruments that are to be handled carefully and utilised with commonsense. So, statistics are like clay of which one can make a God or Devil as one wishes.

Q.4. Discuss various statistical tools used in economic analysis.

Ans. Statistics play an important role in every segment of life. In statistics, we have a number of tools that are used to solve different types of problems. The following are the statistical tools used in economic analysis:

1. Measures of Central Value: Data are assembled mostly for the sake of comparison and so they are placed in relation to each other. It is necessary for comparison to find a representative value for each group. Various types of averages are studied in measure of central value. These measures are Arithmetic mean, Mode, Median, Geometric mean, Harmonic mean, etc.

2. Measures of Dispersion or Variation: Dispersion means the differences in the individual items. Averages do not give this information. So, in order to give a proper idea of the overall nature of the given series, it is not sufficient to calculate only averages but also the variability of the series, i.e. the extent to which the given values are scattered about the average.

3. Correlation and Regression Analysis: It is possible that data may be bivariate. Bivariate analysis is of two types-one is called correlation and the other is called regression analysis. Correlation analysis investigates the nature and extent of the relationship between the two related variables while regression analysis describes the dependence of a variable on an independent variable. Here one variable is regarded as dependent while the other is called independent variable.

4. Association of Attributes: It is possible that the data are of qualitative nature instead of quantitative nature in which some numerical measurements are taken. Here, the data are classified according to some attribute or qualities. Relationship between non-quantitative characteristics cannot be studied by ordinary methods but the method of association of attributes is suitable for it.

5. Analysis of Time Series: It is an important problem in economic analysis. Time series means that the numerical data are collected and recorded at successive interval of time. Time series help to study the future with the help of the past. Profit and loss in businesses depend upon the failure or success of the forecast made by the executives. Time series can be classified into long-term component (secular trend) and short-term component (seasonal variation, cyclical variation and irregular variation).

6. Index Numbers: It is defined as a measure of the average change in a group of related variables over two different situations which may be either two different times or two different places. Index numbers play an important role in economic analysis. They are used for measuring price changes and other factors like wages, employment, trade, demand, export, import, cost of living, etc. are studied. 

7 . Interpolation: It is the art of estimating the unknown value of the function for any given value of the independent variable within an interval. If it is outside the interval, it is called extrapolation. We have to use interpolation if intercensal figures of population are required for investigation. The future probable value of a given phenomenon is estimated by extrapolation. 

8. Sampling: In sample method, information on a part of the population is collected and it throws light on the entire population. In our normal life, sampling is used for purchase of food grains in the market by examining a handful of them. Thus, sampling saves the time and money and gives rapid results. It is frequently used in various segments of economic analysis.

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