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Quartiles and Percentiles - Measures of Central Tendency, Business Mathematics & Statistics Video Lecture | SSC CGL Tier 2 - Study Material, Online Tests, Previous Year

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FAQs on Quartiles and Percentiles - Measures of Central Tendency, Business Mathematics & Statistics Video Lecture - SSC CGL Tier 2 - Study Material, Online Tests, Previous Year

1. What are quartiles and percentiles?
Quartiles and percentiles are statistical measures used to divide a dataset into equal parts. Quartiles divide a dataset into four equal parts, while percentiles divide it into 100 equal parts. Quartiles and percentiles can help understand the distribution and central tendency of a dataset.
2. How do you calculate quartiles?
To calculate quartiles, first arrange the dataset in ascending order. The first quartile (Q1) is the median of the lower half of the dataset, the second quartile (Q2) is the overall median, and the third quartile (Q3) is the median of the upper half of the dataset. If the number of data points is odd, the median is included in both halves. If it is even, the median is excluded from both halves.
3. What is the purpose of quartiles in statistics?
Quartiles are used in statistics to understand the distribution of a dataset and identify the spread of values. They provide valuable information about the range, variability, and central tendency of the data. Quartiles also help in analyzing skewness and outliers in a dataset.
4. How are percentiles useful in business mathematics and statistics?
Percentiles are useful in business mathematics and statistics to analyze the relative position of data points within a dataset. They can help understand how a particular data point compares to the rest of the data. For example, if a student's score is in the 90th percentile, it means they scored better than 90% of the students in the group. Percentiles are commonly used in areas such as market research, employee performance evaluation, and analyzing income distributions.
5. How can quartiles and percentiles be used in decision-making and analysis?
Quartiles and percentiles can be used in decision-making and analysis by providing insights into the distribution and central tendency of data. They help identify potential outliers, understand the spread of values, and compare data points to the rest of the dataset. This information can aid in making informed decisions, such as setting performance benchmarks, determining pricing strategies, or evaluating market trends. Additionally, quartiles and percentiles can be used to identify potential patterns or trends within a dataset, leading to data-driven insights for business strategies.
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