Merits and Demerits of Statistics. ( In points please)

Cyrus as much as i know i am writing it but there may be lot many more.. Hope you like it.

Merits :

1.Comprehensive : Statistics makes data short,comprehensive and easy.

2.Saves Time : Long unarranged data may result in consumption of ample of time, through statistics is
becomes lot more easy to handle the data.

3. Quick Conclusions & Results : Through Statistics one can make very quick conclusions & results can be easily made out of a complex long Raw Data.

Demerits :

1.Statistics omitts or neglets an individuals importance.. so Loss of Imformation is there..

Cyrus hope u lyk .. Thumps up if u .. :)

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merits:

1. quantitaive expression of economic problems

2. inter sectoral and inter temporal comparisons

3. formulation of policies

4. economic equilibrium

demerits:-

1. study of numerical facts only

2.study of aggregates only

3. results are true only on a average

4.can be used only by the experts

5. prone to misuse

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Merits :  

1.Comprehensive : Statistics makes data short,comprehensive and easy.

2.Saves Time : Long unarranged data may result in consumption of ample of time, through statistics is 
becomes lot more easy to handle the data.

3. Quick Conclusions & Results : Through Statistics one can make very quick conclusions & results can be easily made out of a complex long Raw Data.

Demerits :

1.Statistics omitts or neglets an individuals importance.. so Loss of Imformation is there..
 

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merits:

1. quantitaive expression of economic problems

2. inter sectoral and inter temporal comparisons

3. formulation of policies

4. economic equilibrium

demerits:-

1. study of numerical facts only

2.study of aggregates only

3. results are true only on a average

4.can be used only by the experts

5. prone to misuse 

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1. quantitaive expression of economic problems

2. inter sectoral and inter temporal comparisons3. formulation of policies4. economic equilibriumdemerits:-1. study of numerical facts only2.study of aggregates only3. results are true only on a average4.can be used only by the experts5. prone to misuse

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Statistical analysis is used to determine if a scientific experiment produced a result that supported a hypothesis or not. While calculating the probability of an outcome, or "p-value," is the most common technique, one technique that is becoming more popular is Bayesian analysis, in which a statistician starts with a hypothesized model that is continuously updated over the course of an experiment. Statistical analysis helps experts determine if particular medical treatments are effective.
However, it is easy to misinterpret statistics and present deceptive analysis. One outlier in an experiment, for example, can skew results away from the true central mean. In addition, bias can be introduced into public surveys by asking questions in an inappropriate manner. So-called "push polls" can mislead the media and the public to believe something that is not supported by fair polls.
In addition, scientists are often accused of misinterpreting data. For example, a large sample is likely to contain one or more anomalous results. Scientists who do not state a clear hypothesis before running tests and conducting statistical analysis may conclude that one such small anomaly is evidence for a particular hypothesis even though the result is merely noise in the data
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Merits :
# Statistics is used by workers, labour unions, traders, auditors, etc. The politicians & their supports  are immensely interested in knowing their prospects of winning election by sampling few voters prior to election.
# Useful to economists; satistics serves as a raw material to the economists in making certain laws.
# Useful to finance minister; for making sound and balanced annual budget of the country, statistics plays an very important role.
# Statistics is very useful for an individual ;It provides him factual knowledge of prices of commodities in different markets.
Limitations :
# Does not study individuals.
# Without reference, the results may prove to be wrong.
# Statistics deals with numerical facts only.
# They are true only on an average.
# Needs special expertise.
# Homogeneity of data is essential.
# Prone to misuse.
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I think the answers are right
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demerits:-

1. study of numerical facts only

2.study of aggregates only

3. results are true only on a average

4.can be used only by the experts

5. prone to misuse?
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