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FINANCIAL MATHS GROUP PROJECT
Page 2


    
  
FINANCIAL MATHS GROUP PROJECT
    
“
“
Mathematics is the only science 
Mathematics is the only science 
where one never knows what one 
where one never knows what one 
is talking about nor whether what 
is talking about nor whether what 
is said is true” - Bertrand Russell
is said is true” - Bertrand Russell
LET US GIVE A TRY !!!!!
LET US GIVE A TRY !!!!!
Page 3


    
  
FINANCIAL MATHS GROUP PROJECT
    
“
“
Mathematics is the only science 
Mathematics is the only science 
where one never knows what one 
where one never knows what one 
is talking about nor whether what 
is talking about nor whether what 
is said is true” - Bertrand Russell
is said is true” - Bertrand Russell
LET US GIVE A TRY !!!!!
LET US GIVE A TRY !!!!!
    
SKEWNESS 
SKEWNESS 
AND 
AND 
 KURTOSIS
 KURTOSIS
Page 4


    
  
FINANCIAL MATHS GROUP PROJECT
    
“
“
Mathematics is the only science 
Mathematics is the only science 
where one never knows what one 
where one never knows what one 
is talking about nor whether what 
is talking about nor whether what 
is said is true” - Bertrand Russell
is said is true” - Bertrand Russell
LET US GIVE A TRY !!!!!
LET US GIVE A TRY !!!!!
    
SKEWNESS 
SKEWNESS 
AND 
AND 
 KURTOSIS
 KURTOSIS
    
Defining Skewness
Skewness is the measure of asymmetry of the  
distribution of a real valued random 
variable. It is the standardized 3rd central 
moment of a distribution
?
Positive Skewness indicates a long right tail
?
Negative Skewness indicates a long left tail
?
Zero Skewness indicates a symmetry around the mean
Page 5


    
  
FINANCIAL MATHS GROUP PROJECT
    
“
“
Mathematics is the only science 
Mathematics is the only science 
where one never knows what one 
where one never knows what one 
is talking about nor whether what 
is talking about nor whether what 
is said is true” - Bertrand Russell
is said is true” - Bertrand Russell
LET US GIVE A TRY !!!!!
LET US GIVE A TRY !!!!!
    
SKEWNESS 
SKEWNESS 
AND 
AND 
 KURTOSIS
 KURTOSIS
    
Defining Skewness
Skewness is the measure of asymmetry of the  
distribution of a real valued random 
variable. It is the standardized 3rd central 
moment of a distribution
?
Positive Skewness indicates a long right tail
?
Negative Skewness indicates a long left tail
?
Zero Skewness indicates a symmetry around the mean
    
NORMAL DISTRIBUTION
NORMAL DISTRIBUTION
SKEWNESS
NEGATIVE POSITIVE
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FAQs on PPT - Concept of Kurtosis - Business Mathematics and Statistics - B Com

1. What is kurtosis and how is it related to probability distributions?
Ans. Kurtosis is a statistical measure that describes the shape of a probability distribution. It measures the peakedness or flatness of a distribution compared to the normal distribution. Higher kurtosis values indicate a sharper peak and heavier tails, while lower kurtosis values indicate a flatter peak and lighter tails. In other words, kurtosis measures the amount of data that is in the tails of the distribution.
2. How is kurtosis different from skewness?
Ans. Kurtosis and skewness are both measures of the shape of a probability distribution, but they capture different aspects. Skewness measures the asymmetry of the distribution, while kurtosis measures the tails of the distribution. Skewness tells us whether the distribution is skewed to the left or right, while kurtosis tells us whether the distribution has heavier or lighter tails compared to the normal distribution.
3. What are the implications of high kurtosis in a probability distribution?
Ans. High kurtosis in a probability distribution indicates that the distribution has heavier tails and a sharper peak compared to the normal distribution. This means that there is a higher probability of extreme values occurring in the data. It also suggests that the distribution may have more outliers or extreme observations. High kurtosis can indicate a more volatile or risky dataset.
4. Can kurtosis be negative?
Ans. Yes, kurtosis can be negative. Negative kurtosis indicates that the distribution has lighter tails and a flatter peak compared to the normal distribution. It suggests that the data has fewer outliers or extreme observations. Negative kurtosis is less common in practice and often indicates a more regular or uniform dataset.
5. How can kurtosis be used in data analysis?
Ans. Kurtosis can be used in data analysis to understand the shape and characteristics of a probability distribution. It helps in identifying outliers or extreme values in the data. For example, in finance, kurtosis is used to measure the risk of an investment portfolio. It is also used in fields such as economics, biology, and engineering to analyze various types of data and make informed decisions based on the shape of the distribution.
115 videos|142 docs
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