Aziz College of Education, Yar Hussain, Swabi
Aziz College of Education, Yar Hussain, Swabi * We aren't endorsed by this school

Aziz College of Education, Yar Hussain, Swabi (ACE) ** School Info Aziz College of Education, Yar Hussain, Swabi (ACE) has 4 departments in Course Hero with 55 documents.

* We aren't endorsed by this school

Find your department

All Departments (4)

'{[deptFilter.toUpperCase()]}' Departments ({[filteredDepartments.length]})

All A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 0-9

{[ filteredDepartmentsMessage ]}

Aziz College of Education, Yar Hussain, Swabi Documents (55)

Master your classes with homework help, exam study guides, past papers, and more for ACE.

Most Recent Documents for ACE

View all
  • 1 pages Actual_1267.docx
    • Actual_1267.docx
    • Aziz College of Education, Yar Hussain, Swabi
    • fsdzx
    • EFS 127 - Fall 2016
    • MS F = MS If the impact of lack of fit is significant, the model of simple linear regression is not correct. These results are shown in an ANOVA table: Source SS df MS F SSREG 1 MSREG = SSREG / 1 F = MSREG / MSRES Error SSRES n-2 MSRES = SSRES / (n-2) Lac
    • Register Now

    Actual_1267.docx

  • 1 pages Actual_1269.docx
    • Actual_1269.docx
    • Aziz College of Education, Yar Hussain, Swabi
    • fsdzx
    • EFS 127 - Fall 2016
    • not adequate in describing the relationship. The change in feed conversion as protein level increases is not linear. The next step is to try a quadratic model and test the correctness of fit of that model. 21.1.1 SAS Example for Lack of Fit The example co
    • Register Now

    Actual_1269.docx

  • 1 pages Actual_1265.docx
    • Actual_1265.docx
    • Aziz College of Education, Yar Hussain, Swabi
    • fsdzx
    • EFS 127 - Fall 2016
    • if y y (for some i) then the model is not correct. The test is based on the fact that the residual sum of squares can be partitioned to a pure error sum of squares and a lack of fit sum of squares: SSRES = SSPE + SSLOF with appropriate degrees of freedom:
    • Register Now

    Actual_1265.docx

  • 1 pages Actual_1272.docx
    • Actual_1272.docx
    • Aziz College of Education, Yar Hussain, Swabi
    • fsdzx
    • EFS 127 - Fall 2016
    • variability are Model, Error and Corrected Total. In the table are presented degrees of freedom (DF), Sum of Squares, Mean Square, calculated F (F value) and P value (Pr > F). In the next table the sum of squares for MODEL from the first table is partitio
    • Register Now

    Actual_1272.docx

  • 1 pages Actual_1275.docx
    • Actual_1275.docx
    • Aziz College of Education, Yar Hussain, Swabi
    • fsdzx
    • EFS 127 - Fall 2016
    • treatment sum of squares is equal to the sum of contrasts sums of squares: 1.2733 = 0.7565+0.4528+0.0512+0.0128. In addition, the error term here is equal to the pure error from the lack of fit analysis. The coefficients of the quadratic function are esti
    • Register Now

    Actual_1275.docx

  • 1 pages Actual_1254.docx
    • Actual_1254.docx
    • Aziz College of Education, Yar Hussain, Swabi
    • fsdzx
    • EFS 127 - Fall 2016
    • Defining separate variance-covariance parameters for each treatment and also separate error variance for each treatment, the SAS program is: PROC MIXED DATA=reps; CLASS kid treatment; MODEL gain = treatment week treatment*week; RANDOM int week / TYPE=UN S
    • Register Now

    Actual_1254.docx

  • 1 pages Actual_1288.docx
    • Actual_1288.docx
    • Aziz College of Education, Yar Hussain, Swabi
    • fsdzx
    • EFS 127 - Fall 2016
    • 2 i = 1, number of observations where: yi = number of successes from a total of ni trials for observation i pi = the estimated probability of success for observation i The difference between the full and reduced model deviances is distributed with an appr
    • Register Now

    Actual_1288.docx

  • 1 pages Actual_1273.docx
    • Actual_1273.docx
    • Aziz College of Education, Yar Hussain, Swabi
    • fsdzx
    • EFS 127 - Fall 2016
    • Degree of polynom Coefficient (c) c i i 2 2 linear -1 +1 2 3 linear quadratic -1 0 +1 +1 -2 +1 2 6 4 linear quadratic cubic -3 -1 +1 +3 +1 -1 -1 +1 -1 +3 -3 +1 20 4 20 5 linear quadratic cubic quartic -2 -1 0 +1 +2 +2 -1 -2 -1 +2 -1 +2 0 -2 +1 +1 -4 +6 -4
    • Register Now

    Actual_1273.docx

  • 1 pages Actual_1278.docx
    • Actual_1278.docx
    • Aziz College of Education, Yar Hussain, Swabi
    • fsdzx
    • EFS 127 - Fall 2016
    • Up to now we have emphasized analysis of continuous dependent variables; however, dependent variables can be discrete or categorical as well. For example, the effect of different housing systems on calf survival with survival coded as living = 1 or dead =
    • Register Now

    Actual_1278.docx

  • 1 pages Actual_1270.docx
    • Actual_1270.docx
    • Aziz College of Education, Yar Hussain, Swabi
    • fsdzx
    • EFS 127 - Fall 2016
    • DATALINES; I 10 4.61 I 12 4.35 I 14 4.21 I 16 4.02 I 18 4.16 II 10 4.12 II 12 3.84 II 14 3.54 II 16 3.45 II 18 3.28 III 10 4.25 III 12 3.93 III 14 3.47 III 16 3.24 III 18 3.59 IV 10 3.67 IV 12 3.37 IV 14 3.19 IV 16 3.55 IV 18 3.92 V 10 4.01 V 12 3.98 V 14
    • Register Now

    Actual_1270.docx

  • 1 pages Actual_1262.docx
    • Actual_1262.docx
    • Aziz College of Education, Yar Hussain, Swabi
    • fsdzx
    • EFS 127 - Fall 2016
    • 0.402300 0.039190 1 12 1 11 1 10 19 R 384 Chapter 21 Analysis of Numerical Treatment Levels In biological research there is often more than one measurement of the dependent variable for each level of the independent variable (Figure 21.1). For example, th
    • Register Now

    Actual_1262.docx

  • 1 pages Actual_1268.docx
    • Actual_1268.docx
    • Aziz College of Education, Yar Hussain, Swabi
    • fsdzx
    • EFS 127 - Fall 2016
    • = overall mean Lj = the effect of litter j 1 = regression parameter xi = protein level i ij = random error The number of protein levels is m = 5, the total number of pigs is n = 25, and the number of litters (blocks) is b = 5. Results are presented in the
    • Register Now

    Actual_1268.docx

  • 1 pages Actual_1264.docx
    • Actual_1264.docx
    • Aziz College of Education, Yar Hussain, Swabi
    • fsdzx
    • EFS 127 - Fall 2016
    • * * x1 Figure 21.1 Several measurements per level of independent variable 21.1 Lack of Fit Consider more than one measurement of the dependent variable y on each level of independent variable x. Let yij depict the jth measurement in level i of x. There ar
    • Register Now

    Actual_1264.docx

  • 1 pages Actual_1291.docx
    • Actual_1291.docx
    • Aziz College of Education, Yar Hussain, Swabi
    • fsdzx
    • EFS 127 - Fall 2016
    • 0 D = ( ) ( ) 5.2229 001 2 = D D + x = The critical value is 2 0.05,1 = 3.841. Since the calculated difference is greater than the critical value, H0 is rejected, and we can conclude that age at first calving influences incidence of mastitis. The estimate
    • Register Now

    Actual_1291.docx

  • 1 pages Actual_1294.docx
    • Actual_1294.docx
    • Aziz College of Education, Yar Hussain, Swabi
    • fsdzx
    • EFS 127 - Fall 2016
    • i = log[pi /(1-pi)] = m + i i = A, B, C where: pi = the proportion with mastitis on farm i m = the overall mean of the proportion on the logarithmic scale i = the effect of farm i As shown for linear models with categorical independent variables, there ar
    • Register Now

    Actual_1294.docx

  • 1 pages Actual_1285.docx
    • Actual_1285.docx
    • Aziz College of Education, Yar Hussain, Swabi
    • fsdzx
    • EFS 127 - Fall 2016
    • binomial distribution divided by n. A variance function is also defined: V() = V(p) = pq = p (1-p) where q = 1 - p Thus, the variance of binomial proportions y/n is: Var( y / n) pq / n 1V ( p) 2 n = = Chapter 22 Discrete Dependent Variables 397 The varian
    • Register Now

    Actual_1285.docx

  • 1 pages Actual_1274.docx
    • Actual_1274.docx
    • Aziz College of Education, Yar Hussain, Swabi
    • fsdzx
    • EFS 127 - Fall 2016
    • we can conclude that the changes in values of the dependent variable are linear with respect to the independent variable. If the quadratic component is significant, we can conclude that the changes are not linear but parabolic. Using similar reasoning pol
    • Register Now

    Actual_1274.docx

  • 1 pages Actual_1283.docx
    • Actual_1283.docx
    • Aziz College of Education, Yar Hussain, Swabi
    • fsdzx
    • EFS 127 - Fall 2016
    • It is often more practical to express data as binomial proportions. A binomial proportion is the value of a binomial variable y divided by the total number of trials n. The mean and variance of binomial proportions are: E(y/n) = = p and Var(y/n) = 2 = pq/
    • Register Now

    Actual_1283.docx

  • 1 pages Actual_1271.docx
    • Actual_1271.docx
    • Aziz College of Education, Yar Hussain, Swabi
    • fsdzx
    • EFS 127 - Fall 2016
    • variables prot1 and prot are numerically identical (See DATA step), but the program treats them differently. The variable prot1 is not in the CLASS statement and the program uses it as a continuous (regressor) variable. Defining the same variable as both
    • Register Now

    Actual_1271.docx

  • 1 pages Actual_1309.docx
    • Actual_1309.docx
    • Aziz College of Education, Yar Hussain, Swabi
    • fsdzx
    • EFS 127 - Fall 2016
    • The SAS program for the example examining differences in the incidence of mastitis in cows on three farms, which uses a logit model with categorical independent variables, is as follows. Recall the data: Farm Total no. of cows No. of cows with mastitis A
    • Register Now

    Actual_1309.docx

  • 1 pages Actual_1266.docx
    • Actual_1266.docx
    • Aziz College of Education, Yar Hussain, Swabi
    • fsdzx
    • EFS 127 - Fall 2016
    • PE PE n MS SS 1 The expectation of the MSPE is E(MSPE) = 2, which means that MSPE estimates the variance regardless if model is correct or not. The mean square for lack of fit is: mp MS SSLOF LOF = If the model is correct then E(MSLOF) = 2, which means t
    • Register Now

    Actual_1266.docx

  • 1 pages Actual_1277.docx
    • Actual_1277.docx
    • Aziz College of Education, Yar Hussain, Swabi
    • fsdzx
    • EFS 127 - Fall 2016
    • Dependent Variable: conv Sum of Source DF Squares Mean Square F Value Pr > F Model 2 1.20926286 0.60463143 5.43 0.0121 Error 22 2.44828114 0.11128551 Corrected Total 24 3.65754400 Source DF Type I SS Mean Square F Value Pr > F prot1 1 0.75645000 0.7564500
    • Register Now

    Actual_1277.docx

  • 1 pages Actual_1281.docx
    • Actual_1281.docx
    • Aziz College of Education, Yar Hussain, Swabi
    • fsdzx
    • EFS 127 - Fall 2016
    • = g-1() Chapter 22 Discrete Dependent Variables 395 where g-1 = an inverse 'link' function, that is, a function that transforms x back to the mean. Observations of variable y can be expressed as: y=+ where is an error that can have a distribution other t
    • Register Now

    Actual_1281.docx

  • 1 pages Actual_1276.docx
    • Actual_1276.docx
    • Aziz College of Education, Yar Hussain, Swabi
    • fsdzx
    • EFS 127 - Fall 2016
    • CONTRAST 'quart' prot +1 -4 +6 -4 +1; LSMEANS prot / stderr; RUN; *the following procedure computes regression coefficients; PROC GLM; MODEL conv= prot prot*prot /SOLUTION; RUN; The first GLM procedure tests the significance of litters and protein. The CL
    • Register Now

    Actual_1276.docx

  • 1 pages Actual_1286.docx
    • Actual_1286.docx
    • Aziz College of Education, Yar Hussain, Swabi
    • fsdzx
    • EFS 127 - Fall 2016
    • [ ] 2 (_)(_) () 2 2 ( _ ) logL reduced model logL full model L full_model = log L reduced model = + where L and logL are values of the likelihood function and log likelihood function. This expression has a chi-square distribution with degrees of freedom e
    • Register Now

    Actual_1286.docx

  • 1 pages Actual_1290.docx
    • Actual_1290.docx
    • Aziz College of Education, Yar Hussain, Swabi
    • fsdzx
    • EFS 127 - Fall 2016
    • is different than 1, the test must be adjusted by dividing the deviances by 2/n. The estimates do not depend on the parameter 2 and they need not be adjusted. Example: Is there an effect of age at first calving on incidence of mastitis in cows? On a sampl
    • Register Now

    Actual_1290.docx

  • 1 pages Actual_1293.docx
    • Actual_1293.docx
    • Aziz College of Education, Yar Hussain, Swabi
    • fsdzx
    • EFS 127 - Fall 2016
    • 0.6 0.7 0.8 0.9 18 20 22 24 26 28 30 32 Age (months) Proportion Figure 22.1 Logistic curve of changes in proportion with mastitis as affected by changes in age at first calving Logistic regression is also applicable when the independent variables are cate
    • Register Now

    Actual_1293.docx

  • 1 pages Actual_1282.docx
    • Actual_1282.docx
    • Aziz College of Education, Yar Hussain, Swabi
    • fsdzx
    • EFS 127 - Fall 2016
    • and No, or 0 and 1. The probability distribution of the binary variable y has the Bernoulli distribution: p( y) = p yq1y y = 0,1 The probabilities of outcomes are: P(yi = 1) = p P(yi = 0) = q = 1-p The expectation and variance of the binary variable are:
    • Register Now

    Actual_1282.docx

  • 1 pages Actual_1307.docx
    • Actual_1307.docx
    • Aziz College of Education, Yar Hussain, Swabi
    • fsdzx
    • EFS 127 - Fall 2016
    • fixed (=1) for every value of the x variable (NOTE: The scale parameter was held fixed). At the end of the output the Type1 and Type3 tests of significance of regression are shown: Source of variability, Deviance, degrees of freedom (DF), ChiSquare and P
    • Register Now

    Actual_1307.docx

  • 1 pages Actual_1289.docx
    • Actual_1289.docx
    • Aziz College of Education, Yar Hussain, Swabi
    • fsdzx
    • EFS 127 - Fall 2016
    • D( 0 ) D( 0 1x) 2 = + has an approximate chi-square distribution with (2-1) = 1 degree of freedom. If the calculated difference is greater than the critical value 2 , H0 is rejected. Sometimes binomial proportion data show variance that differs from the
    • Register Now

    Actual_1289.docx

Aziz College of Education, Yar Hussain, Swabi Questions & Answers

Showing 1 to 0 of 0

View all

Aziz College of Education, Yar Hussain, Swabi Flashcards

Showing 1 to 0 of 0

View all

Aziz College of Education, Yar Hussain, Swabi Courses with Advice

Showing 1 to {[ numOfCoursesWithAdviceToShow ]} of {[ totalNumCoursesWithAdvice ]}

View all
Sort by:
{[$select.selected.label]}

Be the first to share words of wisdom!

You'll get $10 in tutor credits for sharing advice on 3 courses.

Give Advice

Aziz College of Education, Yar Hussain, Swabi Top Courses

Browse Schools
Ask a homework question - tutors are online