Identifying Outliers in Statistics
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Questions and Answers

What is the primary purpose of fixing the boundary in handling outliers?

  • To detect the median of the data
  • To divide the data into 4 equal parts
  • To calculate the interquartile range
  • To report all extreme values as outliers (correct)

Which measure of position is used to detect outliers?

  • Decile
  • Mean
  • Mode
  • Percentile (correct)

What does Q2 represent in the calculation of quartiles?

  • 50% of students are below the value of Q2 (correct)
  • 25% of students are below the value of Q2
  • 75% of students are below the value of Q2
  • 100% of students are below the value of Q2

What is the formula to calculate the Inter Quartile Range (IQR)?

<p>Q3 - Q1 (B)</p> Signup and view all the answers

What is the criteria to detect outliers in a frequency table?

<p>If any value is less than Q1-1.5<em>IQR or more than Q3 +1.5</em>IQR (A)</p> Signup and view all the answers

What is the purpose of Step-4 in handling outliers?

<p>To report outliers visually via box plot (A)</p> Signup and view all the answers

How can you create a new variable 'total' in a DataFrame 'df' using Python?

<p>Df[“total”]=df[“read”] + df[‘write’] (B)</p> Signup and view all the answers

What is the purpose of dividing the data into four equal parts in the calculation of quartiles?

<p>To find the quartiles (Q1, Q2, and Q3) that help in detecting outliers.</p> Signup and view all the answers

How do you calculate the first quartile (Q1) in a dataset?

<p>Q1 is the value below which 25% of the data points fall.</p> Signup and view all the answers

What is the role of the Inter Quartile Range (IQR) in detecting outliers?

<p>The IQR is used to set the boundaries for detecting outliers, specifically 1.5*IQR below Q1 and above Q3.</p> Signup and view all the answers

How do you determine if a value is an outlier using the first criterion?

<p>If the value is less than Q1-1.5*IQR, it is considered an outlier.</p> Signup and view all the answers

What is the purpose of creating a box plot in handling outliers?

<p>To visually represent the outliers and the distribution of the data.</p> Signup and view all the answers

How do you find the number of outliers in a dataset?

<p>By counting the number of values that meet the criteria for outliers (either below Q1-1.5<em>IQR or above Q3+1.5</em>IQR).</p> Signup and view all the answers

Why is it important to detect and report outliers in a dataset?

<p>To identify unusual or abnormal values that may affect the analysis or results.</p> Signup and view all the answers

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).

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