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Apply the techniques of two-way ANOVA to a data sample split into eight treatments with total degrees of freedom, df = 47, esting at the 2.5% level of significance. The Sum of Squares for Treatments is 42; the Mean Square for Blocks is 9, and the Mean Square for Error is 3. SS df MS F test stats Treatments # 1 #5 #9 #12 Blocks #2 #6 #10 #13 Error # 3 #7 #11 XXXXXXX XXXXXXX Total #4 #8 XXXXXXX #21: What is the number of blocks? Record your response to item #21 here.

Apply the techniques of two-way ANOVA to a data sample split into eight treatments with total degrees of freedom, df = 47, esting at the 2.5% level of significance. The Sum of Squares for Treatments is 42; the Mean Square for Blocks is 9, and the Mean Square for Error is 3. SS df MS F test stats Treatments # 1 #5 #9 #12 Blocks #2 #6 #10 #13 Error # 3 #7 #11 XXXXXXX XXXXXXX Total #4 #8 XXXXXXX #21: What is the number of blocks? Record your response to item #21 here.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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(3) Directions: Solve the following problems and answer the following questions.  [COMMENTS & HINTS:  Use technology to your advantage.  Record your responses according to the coded cells in the organizer and the additional questions. Be precise; do not enter any insignificant or extraneous digits: enter 2 not 2.0 if the answer is two.  Please round off precisely if and when necessary and as requested.]

 

Apply the techniques of **two-way ANOVA** to a data sample split into **eight treatments** with total degrees of freedom, \( df = 47 \), testing at the 2.5% level of significance. The Sum of Squares for Treatments is 42; the Mean Square for Blocks is 9, and the Mean Square for Error is 3. ### Table Explanation | | SS | df | MS | F test stats | |---|---|---|---|---| | **Treatments** | #1 | #5 | #9 | #12 | | **Blocks** | #2 | #6 | #10 | #13 | | **Error** | #3 | #7 | #11 | XXXXXXX | | **Total** | #4 | #8 | XXXXXXX | XXXXXXX | - **SS (Sum of Squares):** This is used to measure the variability in the data. - **df (degrees of freedom):** Indicates the number of independent values or quantities which can be assigned to a statistical distribution. - **MS (Mean Square):** Calculated by dividing the sum of squares (SS) by the corresponding degrees of freedom (df). - **F test stats:** Used to determine if the variability between group means is greater than within-group variability, indicating a significant effect. ### Question **#21:** What is the number of blocks? Record your response to item #21 here. [Textbox for student response]
Transcribed Image Text:Apply the techniques of **two-way ANOVA** to a data sample split into **eight treatments** with total degrees of freedom, \( df = 47 \), testing at the 2.5% level of significance. The Sum of Squares for Treatments is 42; the Mean Square for Blocks is 9, and the Mean Square for Error is 3. ### Table Explanation | | SS | df | MS | F test stats | |---|---|---|---|---| | **Treatments** | #1 | #5 | #9 | #12 | | **Blocks** | #2 | #6 | #10 | #13 | | **Error** | #3 | #7 | #11 | XXXXXXX | | **Total** | #4 | #8 | XXXXXXX | XXXXXXX | - **SS (Sum of Squares):** This is used to measure the variability in the data. - **df (degrees of freedom):** Indicates the number of independent values or quantities which can be assigned to a statistical distribution. - **MS (Mean Square):** Calculated by dividing the sum of squares (SS) by the corresponding degrees of freedom (df). - **F test stats:** Used to determine if the variability between group means is greater than within-group variability, indicating a significant effect. ### Question **#21:** What is the number of blocks? Record your response to item #21 here. [Textbox for student response]
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