Calculate Sum of Squares (SS) for Data Set
Understanding Sum of Squares (SS) Calculation
Sum of Squares (SS) measures variability in a data set by calculating the sum of squared differences between individual values and the mean. It helps in understanding how spread out the values are from the mean, providing insights into the overall variability of the data.
Calculating SS for the Data Set
To calculate SS for the data set 12, 19, 34, 11, 7, 22, we first need to find the mean of the data set. The mean is calculated by adding up all the values and dividing by the total number of values.
Mean = (12 + 19 + 34 + 11 + 7 + 22) / 6 = 105 / 6 = 17.5
Next, we calculate the squared difference for each value from the mean:
- (12 - 17.5)^2 = 30.25
- (19 - 17.5)^2 = 2.25
- (34 - 17.5)^2 = 289
- (11 - 17.5)^2 = 42.25
- (7 - 17.5)^2 = 110.25
- (22 - 17.5)^2 = 20.25
Summing up these squared differences gives us the SS value:
SS = 30.25 + 2.25 + 289 + 42.25 + 110.25 + 20.25 = 479.3125
Therefore, the SS for the data set 12, 19, 34, 11, 7, 22 is 479.3125. The participant score of 34 contributes the most to the variability of the data set, indicating that it is further away from the mean compared to other values.