Explanation Definition: Mean: It is the ratio of sum of all the data values in a dataset to the total number of data values. The mean is usually denoted by x ¯ . If x is set of data values and n is the total number of data values, then mean is calculated by the formula, x ¯ = ∑ x n Variance: It is defined as ratio of, the sum of the deviation from the mean to one less than the number of samples in frequency distribution or dataset. It is denoted by s 2 , if x is the random sample and x ¯ is the mean then variance for a random sample is found by, s 2 = ∑ ( x − x ¯ ) 2 n − 1 Standard deviation: Standard deviation is the square root of the variance and is denoted by, s = s 2 Calculation: The given dataset is, Year 2012 2011 2010 2009 2008 2007 Attendance(x) 366 391 358 373 346 364 Total number of data values is n = 6 . Steps to calculate variance and Standard deviation: Step 1: Calculate mean of the dataset. Mean is calculated as shown below, x ¯ = ∑ x n x ¯ = ( 366 + 391 + 358 + 373 + 346 + 364 ) 6 x ¯ = 2198 6 mean = 366.34 ≃ 366 Mean of the given dataset is 366. Step 2: Calculate Square of the deviation from the mean. Scores Square of the deviation from mean x

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Author: SMITH

Publisher: CENGAGE L

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Chapter 14.2, Problem 52PS

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The Standard deviation for the given data of total attendance.

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Chapter 14 Solutions

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The Standard deviation for the given data of total attendance.

Solution Summary: The author explains the definition of mean, which is the ratio of sum of all the data values in a dataset to the total number of data.

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To find: The Standard deviation for the given data of total attendance.

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Chapter 14 Solutions

To find:

The Standard deviation for the given data of total attendance.