Linear Correlation - Chapter 11 Section 11.2 The sample linear correlation coefficient, r, (a.k.a. the simple correlation, the total correlation and the product-moment correlation) is calculated as.
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CPSC 440, Linear Correlation. Chapter 11. Steel, T
Chapter 16 - Crossover Designs Sequence Period I II III 1 A B C 2 B C A 3 C A B 4 A C B 5 B A C 6 C B A
washout period washout period
yijklm = : + Si + A(i)j + Pk + Tl + Cm + e(ijk)l
where : is the general mean Si is the fixed effect of the ith treatment
Incomplete Blocks of Treatments to Reduce Block Size Section 9.1-9.3 pp 310-315
These are used when you dont have enough experimental units to run a complete replication in a block. They are also useful in that they reduce the estimate of the experimental
RCBD Using One Blocking Criterion Section 8.1 pp 263-264
In the designs we have looked at so far we have assumed that we have enough homogeneous experimental units to complete an experiment. What if we dont have that many? One approach is to use some type
Random Effects for Factorial Treatment Designs Section 7.1 pp 232-237
This is really an RCBD with days as blocks. When we have random variables our interest is in the variance components rather than the means. In this example days and machines are both ra
Factorial Treatment Designs Factorial Treatment Designs all us to look at how multiple treatment factors affect our response variable AND how the treatments interact to affect our response variable. This is all about interactions. T able of means for a 2
Random Effects Models for Variances Section 5.1 pp 148-151 Traditional definitions Fixed - treatment level is reproducible, our interest is the means and our inference is to just the levels tested. Examples.
Random - treatment level is a random draw from
Valid Analysis Depends on Valid Assumptions Section 4.1 p 123 & Cochran 1947 Biometrics 3(1):22-36
The purposes of the ANOVA are. 1) To estimate certain treatment differences that are of interest to us. We want such estimates to be efficient which is to s
Treatment Comparisons Answer Research Questions Section 3.1 pp 73-74 There are implicit questions in most experiments. For the meat example we might have. Is the creation of an artificial atmosphere more effective in reducing bacterial growth than ambient
Assembling the Research Design Section 2.1pp 37-38
The Bacterial Growth on Stored Meat Problem (Example 2.1) Packaging Log Total Mean 2 Condition (count/cm ) Commercial Vacuum Mixed Gas 100% CO2 7.66, 6.98, 7.80 5.26, 5.44, 5.80 7.41, 7.33, 7.04 3.51, 2.9
The Legacy of Ronald A. Fisher Section 1.1- 1.3 pp 1-5
Fairly large print is a real antidote to stiff reading. 31 May 1929, in a letter to K.Sisam, Oxford University Press. Printed in Natural Selection, Heredity, and Eugenics, p.20, J.H.Bennett, Oxford: C
Crop Sciences 540 Applied Statistical Methods II Spring 2006 Professor Don Bullock Office: W201E Turner Hall Phone: 244-8221 e-mail: dbullock@uiuc.edu Office Hours: Friday 3-5 or by appointment Teaching Assistants Sushma Jossey sjossey2@uiuc.edu Fernando
Linear Regression in Matrix Notation - Chapter 13 Section 13.2
CPSC 540, Linear Regression in Matrix Notation. Chapter 13. Steel, Torrie, and Dickey
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* This is the leghorn data on Table 10.1, p age 254 from STD.; OPTIONS pageno=1; data Leghorn; input bod
Matrix Notation - Chapter 12 Section 12.2 A matrix is a rectangular array of numbers such as A and B
B is the transpose of A . A N=B. A transpose of a matrix is one in which the first row is the first column or the original, the second row is the second c
Analysis of Covariance Analysis of covariance can be summarized as a technique to reduce experimental error by utilizing additional factor(s) which are not part of the treatments but were in place prior to imposing treatments and are affecting the measure