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Step Deviation Method-Shift of Origin Method Video Lecture - Class 10

FAQs on Step Deviation Method-Shift of Origin Method Video Lecture - Class 10

1. What is the Step Deviation Method?

Ans. The Step Deviation Method is a statistical technique used to find the mean deviation of a given set of data. It involves finding the difference between each data point and a chosen reference point, known as the origin. These differences, or deviations, are then grouped into intervals or steps, and the mean deviation is calculated based on these intervals.

2. How is the Shift of Origin Method different from the Step Deviation Method?

Ans. The Shift of Origin Method is a variation of the Step Deviation Method where the reference point or origin is shifted from the original dataset. In the Shift of Origin Method, a new origin is chosen, and the differences between the data points and this new origin are calculated. This technique is useful when there is a need to compare datasets with different reference points.

3. What is the purpose of using the Step Deviation Method?

Ans. The Step Deviation Method is used to calculate the mean deviation of a dataset. Mean deviation is a measure of the dispersion or spread of data points around the mean. By using this method, we can simplify the calculations by grouping the deviations into intervals or steps, making it easier to analyze and interpret the data.

4. How do you calculate the mean deviation using the Step Deviation Method?

Ans. To calculate the mean deviation using the Step Deviation Method, you first need to determine the origin or reference point. Then, find the difference between each data point and the origin, known as the deviation. Next, group these deviations into intervals or steps. Finally, calculate the mean deviation by taking the average of the absolute values of the deviations within each interval, multiplied by the corresponding frequency, and divide it by the total frequency.

5. When is it appropriate to use the Step Deviation Method for calculating mean deviation?

Ans. The Step Deviation Method is particularly useful when dealing with large datasets or continuous data. It simplifies the calculation process by grouping the deviations into intervals or steps, reducing the number of individual calculations required. This method is especially effective when the data points are already grouped or when the data follows a specific pattern or distribution.

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Class 10 SSS 1

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Feb 07, 2025 Last updated

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