Podcast
Questions and Answers
What is the primary purpose of fixing the boundary in handling outliers?
What is the primary purpose of fixing the boundary in handling outliers?
Which measure of position is used to detect outliers?
Which measure of position is used to detect outliers?
What does Q2 represent in the calculation of quartiles?
What does Q2 represent in the calculation of quartiles?
What is the formula to calculate the Inter Quartile Range (IQR)?
What is the formula to calculate the Inter Quartile Range (IQR)?
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What is the criteria to detect outliers in a frequency table?
What is the criteria to detect outliers in a frequency table?
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What is the purpose of Step-4 in handling outliers?
What is the purpose of Step-4 in handling outliers?
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How can you create a new variable 'total' in a DataFrame 'df' using Python?
How can you create a new variable 'total' in a DataFrame 'df' using Python?
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What is the purpose of dividing the data into four equal parts in the calculation of quartiles?
What is the purpose of dividing the data into four equal parts in the calculation of quartiles?
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How do you calculate the first quartile (Q1) in a dataset?
How do you calculate the first quartile (Q1) in a dataset?
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What is the role of the Inter Quartile Range (IQR) in detecting outliers?
What is the role of the Inter Quartile Range (IQR) in detecting outliers?
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How do you determine if a value is an outlier using the first criterion?
How do you determine if a value is an outlier using the first criterion?
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What is the purpose of creating a box plot in handling outliers?
What is the purpose of creating a box plot in handling outliers?
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How do you find the number of outliers in a dataset?
How do you find the number of outliers in a dataset?
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Why is it important to detect and report outliers in a dataset?
Why is it important to detect and report outliers in a dataset?
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Study Notes
Handling Outliers
- Extreme values are reported as outliers, and the boundary for detection needs to be fixed.
Steps to Detect Outliers
- Measure of position to be used for detection of outliers includes decile, percentile, and quartile.
Quartile
- Division of data into 4 equal parts.
- Q1: 25% of students are below the value of Q1.
- Q2 (Median): 50% of students are below the value of Q2.
- Q3: 75% of students are below the value of Q3.
Calculation of Inter Quartile Range (IQR)
- IQR = Q3 - Q1.
Criteria for Outliers
- Criteria 1: Values less than Q1 - 1.5*IQR are treated as outliers.
- Criteria 2: Values more than Q3 + 1.5*IQR are treated as outliers.
Steps to Find and Report Outliers
- Calculate the number of outliers from both criteria.
- Report the total number of outliers detected for each variable in the data set.
Reporting Outliers Visually via Box Plot
- Use Python library to create a new variable, such as
Df["total"] = df["read"] + df['write'].
Handling Outliers
- Extreme values are reported as outliers, and the boundary for detection needs to be fixed.
Steps to Detect Outliers
- Measure of position to be used for detection of outliers includes decile, percentile, and quartile.
Quartile
- Division of data into 4 equal parts.
- Q1: 25% of students are below the value of Q1.
- Q2 (Median): 50% of students are below the value of Q2.
- Q3: 75% of students are below the value of Q3.
Calculation of Inter Quartile Range (IQR)
- IQR = Q3 - Q1.
Criteria for Outliers
- Criteria 1: Values less than Q1 - 1.5*IQR are treated as outliers.
- Criteria 2: Values more than Q3 + 1.5*IQR are treated as outliers.
Steps to Find and Report Outliers
- Calculate the number of outliers from both criteria.
- Report the total number of outliers detected for each variable in the data set.
Reporting Outliers Visually via Box Plot
- Use Python library to create a new variable, such as
Df["total"] = df["read"] + df['write'].
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Description
Learn how to detect outliers in a dataset using deciles, percentiles, and quartiles. Understand the calculation of Q1, Q2, and Q3, and how to find the Interquartile Range (IQR).
