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
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
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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]](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F622bb469-b9c7-46a9-a831-40710d9ebd70%2Fc89bd6d2-7560-488d-9466-6b928fb3324f%2Ffc391w_processed.png&w=3840&q=75)
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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