Let x be the mean of x1, and x2,. The sumof the squared deviations of xi, from themean is 5. (Hint: recall your statistics)​

In statistics, the sum of the squared deviations from the mean is a measure of how spread out the values are around the mean. This is often denoted as \( S_xx \) and is calculated using the formula:\[ S_xx = \sum (x_i - \bar{x})^2 \]where \( x_i \) are the individual data points and \( \bar{x} \) is the mean of these data points.Given that the sum of the squared deviations is 5, we have:\[ \sum (x_i - \bar{x})^2 = 5 \]This means that the total of the squared differences between each data point and the mean is 5. This value is useful in various statistical analyses, including calculating variance and standard deviation.

Answered by jumongverano | 2024-09-02

Step-by-step explanation:[tex]51.4 \div 6.275[/tex]

Answered by deseoedralyn77 | 2024-09-02