Asked by Tristan Fetro on Jun 07, 2024
Verified
Which of the following statements is false?
A) The sum of squares for treatments (SST) explains some of the variation.
B) The sum of squares for error (SSE) measures the amount of variation that is unexplained.
C) The total sum of squares Total SS = SST + SSE.
D) The total sum of squares Total SS measures the amount of variation within the samples.
E) The sum of squares for treatments (SST) explains some of the variation and the total sum of squares Total SS = SST + SSE.
Sum of Squares
A statistical measure that quantifies the total variation within a set of observations, used in various analyses and calculations.
Total SS
The total sum of squares, a measure used in statistical analysis to represent the total variation in a dataset.
Variation
A measure of how much values in a dataset differ from the mean of the population or from each other.
- Clarify the importance of treatment and error sum of squares in one-way ANOVA methodology.
Verified Answer
LP
Lindsey PerryJun 12, 2024
Final Answer :
D
Explanation :
The total sum of squares (Total SS) measures the total amount of variation in the data, including both the variation within the samples (captured by the sum of squares for error, SSE) and the variation between the treatment groups (captured by the sum of squares for treatments, SST). Therefore, option D is false because it states that the total sum of squares only measures the amount of variation within the samples, which is incorrect.
Learning Objectives
- Clarify the importance of treatment and error sum of squares in one-way ANOVA methodology.