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Experimental design is a method for planning experiments so that the data obtained can be analyzed objectively. There are several key principles of experimental design, including replication, randomization, and controlling local sources of variation through techniques like blocking, balancing, and using proper plot sizes and techniques. When applied correctly, these principles help reduce experimental error and allow researchers to more accurately determine the effects of different treatments or variables.

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Experimental design.pptx

Assumption involving in ANOVA,Uses of CRD,RBD,LSD in agriculture, Principle of Design of Experiment,Uniformity trial,Level of Significance

02 designing of experiments and analysis of data in plant genetic resource ma...

02 designing of experiments and analysis of data in plant genetic resource ma...Indranil Bhattacharjee

This document discusses experimental design considerations for plant genetic resource evaluation trials. Such trials aim to identify promising new germplasm by comparing test treatments (new selections) to control treatments (existing varieties). Key challenges include limited seed availability and a large number of accessions to test. Augmented designs are commonly used, with test treatments unreplicated and controls replicated in blocks. Indices are developed to objectively compare test and control yields while accounting for spatial heterogeneity. Multivariate analysis and genetic distance measures can further characterize genetic diversity among accessions. Combined analysis of multi-location trials tests for genotype by environment interaction and identifies broadly adaptable lines.Experimental design in Plant Breeding

Introduction of Experimental Design , types , features, advantage and disadvantage of experimental designs and its comparison.

Completely randomized design

The document summarizes the key aspects of a Completely Randomized Design (CRD) experiment. It defines a CRD as an experimental design where treatments are randomly assigned to experimental units, giving each unit an equal chance of receiving each treatment. The summary describes some advantages as easy implementation and flexibility, and a disadvantage as not controlling for variation among units. It also outlines the statistical analysis of a CRD using an ANOVA table to partition total variation into treatment and error components.

Layout of Agricultural field experiments

1. The document outlines different experimental designs including single factor and double factor designs. It discusses completely randomized design (CRD) and randomized complete block design (RCBD) for single factor experiments.
2. For CRD, treatments are assigned completely at random to experimental units. For RCBD, the experimental area is divided into blocks of equal size with all treatments represented in each block to account for soil variability.
3. A two factor design involves all possible combinations of selected levels for two or more factors as treatments. For a two factor RCBD, all possible combinations of treatment levels for the two factors are used.

Latin square design

This document discusses Latin square designs, which are experimental designs used to study the effects of multiple factors. A Latin square design has the same number of treatments, rows, and columns, with each treatment occurring once in each row and column. This allows researchers to study the effects of treatments, rows, and columns while controlling for interactions between them. The document provides examples of 3x3 and 4x4 Latin squares and explains how to analyze the results using ANOVA.

Basic Concepts of Split-Plot Design,Analysis Of Covariance(ANCOVA)& Response ...

This gives the basic description of Analysis of Experiment . This is one of the most important topic in Statistics and also for Mathematics and for Researchers-Scientists .

Basic Concepts of Experimental Design & Standard Design ( Statistics )

This gives the basic description of Design and Analysis of Experiment . This is one of the most important topic in Statistics and also for Mathematics and for Researchers-Scientists

Experimental design.pptx

Assumption involving in ANOVA,Uses of CRD,RBD,LSD in agriculture, Principle of Design of Experiment,Uniformity trial,Level of Significance

02 designing of experiments and analysis of data in plant genetic resource ma...

02 designing of experiments and analysis of data in plant genetic resource ma...Indranil Bhattacharjee

This document discusses experimental design considerations for plant genetic resource evaluation trials. Such trials aim to identify promising new germplasm by comparing test treatments (new selections) to control treatments (existing varieties). Key challenges include limited seed availability and a large number of accessions to test. Augmented designs are commonly used, with test treatments unreplicated and controls replicated in blocks. Indices are developed to objectively compare test and control yields while accounting for spatial heterogeneity. Multivariate analysis and genetic distance measures can further characterize genetic diversity among accessions. Combined analysis of multi-location trials tests for genotype by environment interaction and identifies broadly adaptable lines.Experimental design in Plant Breeding

Introduction of Experimental Design , types , features, advantage and disadvantage of experimental designs and its comparison.

Completely randomized design

The document summarizes the key aspects of a Completely Randomized Design (CRD) experiment. It defines a CRD as an experimental design where treatments are randomly assigned to experimental units, giving each unit an equal chance of receiving each treatment. The summary describes some advantages as easy implementation and flexibility, and a disadvantage as not controlling for variation among units. It also outlines the statistical analysis of a CRD using an ANOVA table to partition total variation into treatment and error components.

Layout of Agricultural field experiments

1. The document outlines different experimental designs including single factor and double factor designs. It discusses completely randomized design (CRD) and randomized complete block design (RCBD) for single factor experiments.
2. For CRD, treatments are assigned completely at random to experimental units. For RCBD, the experimental area is divided into blocks of equal size with all treatments represented in each block to account for soil variability.
3. A two factor design involves all possible combinations of selected levels for two or more factors as treatments. For a two factor RCBD, all possible combinations of treatment levels for the two factors are used.

Latin square design

This document discusses Latin square designs, which are experimental designs used to study the effects of multiple factors. A Latin square design has the same number of treatments, rows, and columns, with each treatment occurring once in each row and column. This allows researchers to study the effects of treatments, rows, and columns while controlling for interactions between them. The document provides examples of 3x3 and 4x4 Latin squares and explains how to analyze the results using ANOVA.

Basic Concepts of Split-Plot Design,Analysis Of Covariance(ANCOVA)& Response ...

This gives the basic description of Analysis of Experiment . This is one of the most important topic in Statistics and also for Mathematics and for Researchers-Scientists .

Basic Concepts of Experimental Design & Standard Design ( Statistics )

This gives the basic description of Design and Analysis of Experiment . This is one of the most important topic in Statistics and also for Mathematics and for Researchers-Scientists

Experimental Design | Statistics

Experimental design is inferential procedure or scientific method in Statistics wherein cause and effect relationship is studied by planning an experiment. In Experimental Design methodology, proper experiments are planned in order to achieve desired objective. Copy the link given below and paste it in new browser window to get more information on Experimental Design:- www.transtutors.com/homework-help/statistics/experimental-design.aspx

Ducan’s multiple range test - - Dr. Manu Melwin Joy - School of Management St...

This document provides an overview of Duncan's multiple range test, a statistical method used to compare all pairs of means and group means that are not significantly different. It explains the steps to perform Duncan's test, including calculating ranked means, finding critical values using tables, and comparing means to determine grouping. An example using data from a plant study demonstrates how to apply Duncan's test to analyze differences between varietal means.

Mating designs..

It comprises on mating designs used in plant breeding programs. 6 basic mating designs are briefly explained in it with their requirements as well limiting factors...

Gene introgression from wild relatives to cultivated plants

This document summarizes a seminar on using crop wild relatives to introduce beneficial genes into cultivated crops. It discusses how crop wild relatives contain genetic diversity that can provide traits like pest and disease resistance, abiotic stress tolerance, and improved yields. Specific examples are given of introducing disease resistance genes from wild relatives into tomatoes and rust resistance genes into wheat. The use of wild rice species to develop rice varieties with improved resistance to various diseases and insects is also described.

Mutation breeding ppt

Mutation breeding involves deliberately inducing mutations in plant varieties to generate genetic diversity for crop improvement. The document discusses the history, techniques, and achievements of mutation breeding. It describes how mutations can be induced using physical or chemical mutagens and the procedures for handling segregating populations. Mutation breeding has been used to develop improved varieties with traits like increased yield, abiotic/biotic stress resistance, and quality. India has released many successful mutant crop varieties, especially in rice and chickpeas, through research centers like IARI. While mutation breeding can lead to quick gains, it also has limitations like unpredictability and costs of screening large populations.

Heritability , genetic advance

1. The document discusses components of variation, heritability, types of heritability, genetic advance, environment, and genotype-environment interaction. It defines key terms like phenotypic variation, genotypic variation, broad sense heritability, narrow sense heritability, genetic advance, and genotype-environment interaction.
2. Heritability is the ratio of genotypic variance to phenotypic variance and indicates the proportion of a phenotypic trait caused by genetic factors. Broad sense heritability includes all genetic effects while narrow sense only includes additive genetic effects.
3. Genetic advance measures the expected genetic improvement from selection and depends on genetic variability, heritability, and selection intensity. High genetic advance indicates a trait is

Biotic and abiotic stress

i) Breeding crops for resistance to insects, diseases, and abiotic stresses like drought is important to reduce yield losses and costs of control measures.
ii) Mechanisms of resistance include non-preference, antibiosis, tolerance, avoidance, and physiological or biochemical traits like hairiness, toxins, or proline accumulation.
iii) Sources of resistance come from cultivated varieties, germplasm collections, and related wild species, and screening is done under field or controlled conditions.

LATIN SQUARE DESIGN - RESEARCH DESIGN

A Latin square design assigns treatments to rows and columns so that each treatment appears once in each row and column. This allows controlling for two sources of variation: rows and columns. An example describes using a Latin square to study the effects of different protein sources and levels on rat weight gain. Treatments are assigned to letters in the square. Advantages are controlling two variables, but disadvantages are experiments become large with many treatments and statistical analysis is complicated.

Genetic diversity analysis

The presentation was done as part of the course STAT 504 titled Quantitative Genetics in Second Semester of MSc. Agricultural Statistics at Agricultural College, Bapatla under ANGRAU, Andhra Pradesh

Principles of experimental design

This document discusses principles of experimental design. It covers the aims of experiments including developing new products or processes or improving existing ones. It discusses types of experiments and defines DOE (design of experiments). It outlines the phases of experimental design including treatment design, experiment design, and analysis design. It provides examples of treatment design objectives like screening, quantifying, optimization, and theory. It also discusses concepts like one-variable and two-way factorial experiments, experimental units, replicates, randomization, and analysis of variance.

Genetics and plant breeding seminar

This document summarizes a seminar on breeding concepts and crop improvement in chickpea. It discusses the floral biology of chickpea, including emasculation and pollination techniques. Breeding objectives for chickpea include increasing yield, biotic and abiotic stress resistance, and quality traits. Key breeding techniques used are mass selection, pure line selection, and hybridization methods like bulk hybridization and pedigree breeding. Varieties developed through these techniques with important traits are mentioned. The document provides information on the present uses of chickpea and production constraints.

Managing plant population and competition in Field Crops

Plant population is defined as the total number of plants present at unit area of land (Baker, 1964). The number of plants per unit area that would give maximum yield is termed as optimum plant population (Willey & Heath, 1969). Competition is generally refer to the negative effects on plant growth caused by the presence of neighbors, usually by reducing the availability of resources (Paul & James, 2019).

Vr wr graph

This document discusses the Wr-Vr graph, a graphical approach developed by Hayman for diallel cross analysis. The Wr-Vr graph plots the covariance between parents (Wr) against the variance of arrays (Vr). A regression line is fitted and its intercept with the Wr axis indicates the average degree of dominance. The position of parent points relative to the regression line and parabola limits provides information about gene effects and interactions among the parents.

oneway ANOVA.ppt

The document provides an overview of one-way analysis of variance (ANOVA). It explains that one-way ANOVA tests whether the means of three or more populations are equal. Key aspects summarized include: assumptions of one-way ANOVA; calculating between-group, within-group, and total sums of squares and degrees of freedom; determining the F-statistic; and interpreting the p-value to determine whether to reject or fail to reject the null hypothesis of equal population means. An example comparing exam scores of students in different rows is presented to demonstrate a one-way ANOVA calculation.

Diallele selective mating system

This document discusses the diallel selective mating approach (DSM) for genetic improvement of autogamous crops. DSM involves three steps: 1) a parental diallel series of crosses between multiple parents, 2) F1 diallel series of crosses between F1 plants, and 3) selective mating series where selected F2 plants are intercrossed and selfed in successive generations. The goal is to accumulate desirable genes and increase recombination through restoring heterozygosity via intermating selected plants over multiple cycles. While it broadens the genetic base, DSM is more complex than pedigree methods and success depends on identifying desirable plants in segregating generations.

MARKER ASSISTED BACKCROSS BREEDING

This document summarizes three case studies on using marker-assisted breeding techniques:
1) Introgressing rice QTLs controlling root traits from donor Azucena into recipient Kalinga III. Five target QTLs were introgressed over three backcrosses using foreground, background, and recombinant selection with RFLPs and SSRs.
2) Introgressing the submergence tolerance Sub1 QTL from donor IR49830 into popular rice variety Swarna. The QTL was introgressed over three backcrosses and a BC3F2 line identified with minimal donor DNA.
3) Introgressing drought tolerance QTLs from donor CML247 into

Breeding methods in cross pollinated crops

This document discusses methods of breeding in cross-pollinated crops. It describes mass selection, progeny selection (ear-to-row method), modified ear-to-row method, and recurrent selection. It also discusses hybrid varieties, synthetic varieties, and the operations involved in producing hybrids and synthetics. The key methods discussed are mass selection, ear-to-row selection, and recurrent selection.

Central seed committee

The Presentation is prepared by the N.S Institution of science, Markapur.
It consists of a basic introduction related to Central seed committee.

Basic terminology of experimental design in Agriculture

This presentation provides an overview of basic terminology used in the design of agricultural experiments. It defines key terms like experimental units, experimental error, factors, treatments, blocking, randomization, and replication. It also defines concepts like local control, field layouts, yield, and tools. The presentation was delivered by Gurkirat Singh Sidhu to introduce students to foundational concepts in experimental design and data collection in agriculture.

global agriculture research system.ppt

This document discusses the global agricultural research system, which is divided into two sections: national agricultural research systems (NARS) and international agricultural research centers (IARCs). It provides examples of specific research centers for various crops like wheat, maize, rice, cotton, dryland systems, and others. National research is conducted by institutes like the Indian Council of Agricultural Research (ICAR) and state agricultural universities, while international research is led by centers like CIMMYT for wheat and maize, the International Rice Research Institute, and ICRISAT for grain legumes.

Randomized complete block_design_rcbd_

The document describes a randomized complete block design (RCBD) experimental method. RCBD involves comparing treatments (e.g. fertilizers) applied to experimental units (e.g. corn crops) grouped into blocks (e.g. fields). Treatments are randomly assigned to experimental units within each block. RCBD controls for variability between blocks (e.g. differences in soil between fields) to isolate the effect of treatments. It provides more precise results than a completely randomized design when blocks are homogeneous within and heterogeneous between.

Design of experiments(

The document provides information on the basic principles of experimental design, including replication, randomization, and local control. It then discusses the completely randomized design (CRD) in detail. The CRD allocates treatments randomly across experimental units. It has advantages like maximum use of units and simple analysis, but disadvantages like more experimental error. The document also introduces the randomized block design (RBD) which controls for variation among blocks. The RBD stratifies the experimental area into blocks and allocates treatments randomly within each block.

Experimental Design | Statistics

Experimental design is inferential procedure or scientific method in Statistics wherein cause and effect relationship is studied by planning an experiment. In Experimental Design methodology, proper experiments are planned in order to achieve desired objective. Copy the link given below and paste it in new browser window to get more information on Experimental Design:- www.transtutors.com/homework-help/statistics/experimental-design.aspx

Ducan’s multiple range test - - Dr. Manu Melwin Joy - School of Management St...

This document provides an overview of Duncan's multiple range test, a statistical method used to compare all pairs of means and group means that are not significantly different. It explains the steps to perform Duncan's test, including calculating ranked means, finding critical values using tables, and comparing means to determine grouping. An example using data from a plant study demonstrates how to apply Duncan's test to analyze differences between varietal means.

Mating designs..

It comprises on mating designs used in plant breeding programs. 6 basic mating designs are briefly explained in it with their requirements as well limiting factors...

Gene introgression from wild relatives to cultivated plants

This document summarizes a seminar on using crop wild relatives to introduce beneficial genes into cultivated crops. It discusses how crop wild relatives contain genetic diversity that can provide traits like pest and disease resistance, abiotic stress tolerance, and improved yields. Specific examples are given of introducing disease resistance genes from wild relatives into tomatoes and rust resistance genes into wheat. The use of wild rice species to develop rice varieties with improved resistance to various diseases and insects is also described.

Mutation breeding ppt

Mutation breeding involves deliberately inducing mutations in plant varieties to generate genetic diversity for crop improvement. The document discusses the history, techniques, and achievements of mutation breeding. It describes how mutations can be induced using physical or chemical mutagens and the procedures for handling segregating populations. Mutation breeding has been used to develop improved varieties with traits like increased yield, abiotic/biotic stress resistance, and quality. India has released many successful mutant crop varieties, especially in rice and chickpeas, through research centers like IARI. While mutation breeding can lead to quick gains, it also has limitations like unpredictability and costs of screening large populations.

Heritability , genetic advance

1. The document discusses components of variation, heritability, types of heritability, genetic advance, environment, and genotype-environment interaction. It defines key terms like phenotypic variation, genotypic variation, broad sense heritability, narrow sense heritability, genetic advance, and genotype-environment interaction.
2. Heritability is the ratio of genotypic variance to phenotypic variance and indicates the proportion of a phenotypic trait caused by genetic factors. Broad sense heritability includes all genetic effects while narrow sense only includes additive genetic effects.
3. Genetic advance measures the expected genetic improvement from selection and depends on genetic variability, heritability, and selection intensity. High genetic advance indicates a trait is

Biotic and abiotic stress

i) Breeding crops for resistance to insects, diseases, and abiotic stresses like drought is important to reduce yield losses and costs of control measures.
ii) Mechanisms of resistance include non-preference, antibiosis, tolerance, avoidance, and physiological or biochemical traits like hairiness, toxins, or proline accumulation.
iii) Sources of resistance come from cultivated varieties, germplasm collections, and related wild species, and screening is done under field or controlled conditions.

LATIN SQUARE DESIGN - RESEARCH DESIGN

A Latin square design assigns treatments to rows and columns so that each treatment appears once in each row and column. This allows controlling for two sources of variation: rows and columns. An example describes using a Latin square to study the effects of different protein sources and levels on rat weight gain. Treatments are assigned to letters in the square. Advantages are controlling two variables, but disadvantages are experiments become large with many treatments and statistical analysis is complicated.

Genetic diversity analysis

The presentation was done as part of the course STAT 504 titled Quantitative Genetics in Second Semester of MSc. Agricultural Statistics at Agricultural College, Bapatla under ANGRAU, Andhra Pradesh

Principles of experimental design

This document discusses principles of experimental design. It covers the aims of experiments including developing new products or processes or improving existing ones. It discusses types of experiments and defines DOE (design of experiments). It outlines the phases of experimental design including treatment design, experiment design, and analysis design. It provides examples of treatment design objectives like screening, quantifying, optimization, and theory. It also discusses concepts like one-variable and two-way factorial experiments, experimental units, replicates, randomization, and analysis of variance.

Genetics and plant breeding seminar

This document summarizes a seminar on breeding concepts and crop improvement in chickpea. It discusses the floral biology of chickpea, including emasculation and pollination techniques. Breeding objectives for chickpea include increasing yield, biotic and abiotic stress resistance, and quality traits. Key breeding techniques used are mass selection, pure line selection, and hybridization methods like bulk hybridization and pedigree breeding. Varieties developed through these techniques with important traits are mentioned. The document provides information on the present uses of chickpea and production constraints.

Managing plant population and competition in Field Crops

Plant population is defined as the total number of plants present at unit area of land (Baker, 1964). The number of plants per unit area that would give maximum yield is termed as optimum plant population (Willey & Heath, 1969). Competition is generally refer to the negative effects on plant growth caused by the presence of neighbors, usually by reducing the availability of resources (Paul & James, 2019).

Vr wr graph

This document discusses the Wr-Vr graph, a graphical approach developed by Hayman for diallel cross analysis. The Wr-Vr graph plots the covariance between parents (Wr) against the variance of arrays (Vr). A regression line is fitted and its intercept with the Wr axis indicates the average degree of dominance. The position of parent points relative to the regression line and parabola limits provides information about gene effects and interactions among the parents.

oneway ANOVA.ppt

The document provides an overview of one-way analysis of variance (ANOVA). It explains that one-way ANOVA tests whether the means of three or more populations are equal. Key aspects summarized include: assumptions of one-way ANOVA; calculating between-group, within-group, and total sums of squares and degrees of freedom; determining the F-statistic; and interpreting the p-value to determine whether to reject or fail to reject the null hypothesis of equal population means. An example comparing exam scores of students in different rows is presented to demonstrate a one-way ANOVA calculation.

Diallele selective mating system

This document discusses the diallel selective mating approach (DSM) for genetic improvement of autogamous crops. DSM involves three steps: 1) a parental diallel series of crosses between multiple parents, 2) F1 diallel series of crosses between F1 plants, and 3) selective mating series where selected F2 plants are intercrossed and selfed in successive generations. The goal is to accumulate desirable genes and increase recombination through restoring heterozygosity via intermating selected plants over multiple cycles. While it broadens the genetic base, DSM is more complex than pedigree methods and success depends on identifying desirable plants in segregating generations.

MARKER ASSISTED BACKCROSS BREEDING

This document summarizes three case studies on using marker-assisted breeding techniques:
1) Introgressing rice QTLs controlling root traits from donor Azucena into recipient Kalinga III. Five target QTLs were introgressed over three backcrosses using foreground, background, and recombinant selection with RFLPs and SSRs.
2) Introgressing the submergence tolerance Sub1 QTL from donor IR49830 into popular rice variety Swarna. The QTL was introgressed over three backcrosses and a BC3F2 line identified with minimal donor DNA.
3) Introgressing drought tolerance QTLs from donor CML247 into

Breeding methods in cross pollinated crops

This document discusses methods of breeding in cross-pollinated crops. It describes mass selection, progeny selection (ear-to-row method), modified ear-to-row method, and recurrent selection. It also discusses hybrid varieties, synthetic varieties, and the operations involved in producing hybrids and synthetics. The key methods discussed are mass selection, ear-to-row selection, and recurrent selection.

Central seed committee

The Presentation is prepared by the N.S Institution of science, Markapur.
It consists of a basic introduction related to Central seed committee.

Basic terminology of experimental design in Agriculture

This presentation provides an overview of basic terminology used in the design of agricultural experiments. It defines key terms like experimental units, experimental error, factors, treatments, blocking, randomization, and replication. It also defines concepts like local control, field layouts, yield, and tools. The presentation was delivered by Gurkirat Singh Sidhu to introduce students to foundational concepts in experimental design and data collection in agriculture.

global agriculture research system.ppt

This document discusses the global agricultural research system, which is divided into two sections: national agricultural research systems (NARS) and international agricultural research centers (IARCs). It provides examples of specific research centers for various crops like wheat, maize, rice, cotton, dryland systems, and others. National research is conducted by institutes like the Indian Council of Agricultural Research (ICAR) and state agricultural universities, while international research is led by centers like CIMMYT for wheat and maize, the International Rice Research Institute, and ICRISAT for grain legumes.

Experimental Design | Statistics

Experimental Design | Statistics

Ducan’s multiple range test - - Dr. Manu Melwin Joy - School of Management St...

Ducan’s multiple range test - - Dr. Manu Melwin Joy - School of Management St...

Mating designs..

Mating designs..

Gene introgression from wild relatives to cultivated plants

Gene introgression from wild relatives to cultivated plants

Mutation breeding ppt

Mutation breeding ppt

Heritability , genetic advance

Heritability , genetic advance

Biotic and abiotic stress

Biotic and abiotic stress

LATIN SQUARE DESIGN - RESEARCH DESIGN

LATIN SQUARE DESIGN - RESEARCH DESIGN

Genetic diversity analysis

Genetic diversity analysis

Principles of experimental design

Principles of experimental design

Genetics and plant breeding seminar

Genetics and plant breeding seminar

Managing plant population and competition in Field Crops

Managing plant population and competition in Field Crops

Vr wr graph

Vr wr graph

oneway ANOVA.ppt

oneway ANOVA.ppt

Diallele selective mating system

Diallele selective mating system

MARKER ASSISTED BACKCROSS BREEDING

MARKER ASSISTED BACKCROSS BREEDING

Breeding methods in cross pollinated crops

Breeding methods in cross pollinated crops

Central seed committee

Central seed committee

Basic terminology of experimental design in Agriculture

Basic terminology of experimental design in Agriculture

global agriculture research system.ppt

global agriculture research system.ppt

Randomized complete block_design_rcbd_

The document describes a randomized complete block design (RCBD) experimental method. RCBD involves comparing treatments (e.g. fertilizers) applied to experimental units (e.g. corn crops) grouped into blocks (e.g. fields). Treatments are randomly assigned to experimental units within each block. RCBD controls for variability between blocks (e.g. differences in soil between fields) to isolate the effect of treatments. It provides more precise results than a completely randomized design when blocks are homogeneous within and heterogeneous between.

Design of experiments(

The document provides information on the basic principles of experimental design, including replication, randomization, and local control. It then discusses the completely randomized design (CRD) in detail. The CRD allocates treatments randomly across experimental units. It has advantages like maximum use of units and simple analysis, but disadvantages like more experimental error. The document also introduces the randomized block design (RBD) which controls for variation among blocks. The RBD stratifies the experimental area into blocks and allocates treatments randomly within each block.

Mech ma6452 snm_notes

This document discusses experimental design and different types of designs used in statistics. It begins by introducing the basic principles of experimental design such as randomization, replication, and blocking to control extraneous variables. It then describes the three basic designs: completely randomized design, randomized block design, and Latin square design. For each design, it provides an example to illustrate how treatments are assigned randomly or systematically. Finally, it introduces analysis of variance (ANOVA) which is used to analyze the effects of factors in experimental designs.

Randomized-Complete-Block-Design.pdf

This document describes an experimental design using a randomized complete block design (RCBD) for a single-factor experiment. It explains that RCBD is used when there are differences between observation units, and it involves grouping similar units into blocks to reduce experimental error. Each treatment is randomly assigned to units within blocks, with blocks serving as replicates. The document provides an example of comparing fish pellets across ponds blocked by pond. It also describes how to extend RCBD to a two-factor factorial experiment by considering all combinations of levels for two factors in a blocked design.

factorial design.pptx

DESIGN OF EXPERIMENTS (DOE)
DOE is invented by Sir Ronald Fisher in 1920’s and 1930’s.
The following designs of experiments will be usually followed:
Completely randomised design(CRD)
Randomised complete block design(RCBD)
Latin square design(LSD)
Factorial design or experiment
Confounding
Split and strip plot design
FACTORIAL DESIGN
When a several factors are investigated simultaneously in a single experiment such experiments are known as factorial experiments. Though it is not an experimental design, indeed any of the designs may be used for factorial experiments.
For example, the yield of a product depends on the particular type of synthetic substance used and also on the type of chemical used.
ADVANTAGES OF FACTORIAL DESIGN.
Factorial experiments are advantageous to study the combined effect of two or more factors simultaneously and analyze their interrelationships. Such factorial experiments are economic in nature and provide a lot of relevant information about the phenomenon under study. It also increases the efficiency of the experiment.
It is an advantageous because a wide range of factor combination are used. This will give us an idea to predict about what will happen when two or more factors are used in combination.
DISADVANTAGES
It is disadvantageous because the execution of the experiment and the statistical analysis becomes more complex when several treatments combinations or factors are involved simultaneously.
It is also disadvantageous in cases where may not be interested in certain treatment combinations but we are forced to include them in the experiment. This will lead to wastage of time and also the experimental material.
2(square) FACTORIAL EXPERIMENT
A special set of factorial experiment consist of experiments in which all factors have 2 levels such experiments are referred to generally as 2n factorials.
If there are four factors each at two levels the experiment is known as 2x2x2x2 or 24 factorial experiment. On the other hand if there are 2 factors each with 3 levels the experiment is known as 3x3 or 32 factorial experiment. In general if there are n factors each with p levels then it is known as pn factorial experiment.
The calculation of the sum of squares is as follows:
Correction factor (CF) = (𝐺𝑇)2/𝑛
GT = grand total
n = total no of observations
Total sum of squares = ∑▒〖𝑥2−𝐶𝐹〗
Replication sum of squares (RSS) = ((𝑅1)2+(𝑅2)2+…+(𝑅𝑛)2)/𝑛 - CF
Or
1/𝑛 ∑▒𝑅2−𝐶𝐹
2(Cube) FACTORIAL DESIGN
In this type of design, one independent variable has 2 levels, and the other independent variable has 3 levels.
Estimating the effect:
In a factorial design the main effect of an independent variable is its overall effect averaged across all other independent variable.
Effect of a factor A is the average of the runs where A is at the high level minus the average of the runs

7292015Intro to Biostatistics Homework #8Use R to calculate .docx

7/29/2015
Intro to Biostatistics Homework #8
Use R to calculate the following probability from Z distribution. Please Plot 4) as shown.
1)
P (z > 1.46) =
2)
P (z < -1.56) =
3)
P (0.67 ≤ z ≤ 2.41) =
4)
[P (x ≥ 13.24) with µ = 11 and σ = 2] =
5)
What is the Z value for P(Z > z) = 0.45?
A biology scientist claims that the distribution of the lifespans of their testing animal subjects has a mean of 54 months and a standard deviation of 6 months. Suppose an audit group decides to check the claim by choosing a sample of 50 of these subjects.
1)
Assuming that the scientist’s claim is true, describe the sampling distribution of the mean lifetime of a sample of 50 subjects.
2)
Assuming that the scientist’s claim is true, what the probability the audit group’s sample has a mean life of 52 or fewer months?
3)
Plot your answer using R as shown.
3.
Create 15 random numbers that are normally distributed with mean 10 and s.d. 5. Find a 1-sample t-test CI at the 95% level by modifying the ci95 function in seciton01 of lecture5. Did it get it right? Can you generalize the function so that it works for any given level?
4.
Based on part 1, find 80%, 95% and 99% confidence interval for the mean for the
exec.pay
dataset from “UsingR”.
5.
For the data set
rat
from “UsingR”, do a t-test for mean against 112 using p value. What is your conclusion.
6.
Load library “UsingR”
1)
Load the Simple dataset “homework”. This measures study habits of students from private and public high schools. Make a side-by-side boxplot. Use the appropriate test to test for equality of means at 5% level.
2)
What if I want to test do private schools have higher mean score than that of public ones at 5% level
3)
Load the Simple data set “corn”. Twelve plots of land are divided into two and then one half of each is planted with a new corn seed, the other with the standard. Use the appropriate test to test for equality of means at 1% level.
7.
Consider dataset “juul” from library “ISwR”.
Are the means of igf1 equal among tanner groups at 5% level?
Please use the six step process to test statistical hypotheses for this research problem.
Note: You need to convert tanner from numeric to factor type and ignore all the NAs.
8.
The following ANOVA table was obtained from a balanced completely randomized design:
1.
Fill in the blanks in this table
Source
df
SS
MS
Treatments
4
368
Error
25
575
Total (corrected)
29
2.
Determine the number of treatments
3.
Determine the number of replications per treatment.
4.
What is the F statistics value?
5.
Perform a hypothesis test to see if there is a difference in the true mean responses among the treatments at α = 0.01. The p-value from the test is 0.012.
9.
In a study, among 747 patients exposed to a treatment A, 130 patients were diagnosed with disease D. Out of 661 people exposed to no treatment, 202 were positive with D. Please const.

Randomization Tests

Randomization tests provide an alternative to t-tests and F-tests that does not rely on assumptions of normality or random sampling. However, randomization tests can be too liberal or conservative depending on differences in sample sizes. Bootstrapping and Gill's algorithm can help address these issues. Bootstrapping resamples the larger sample to match the size of the smaller sample, controlling for liberal bias. Gill's algorithm uses Fourier expansion to efficiently calculate p-values from all permutations, reducing computational cost compared to full enumeration. However, conservative bias remains a challenge without a known solution.

Screening of new strains of sugarcane using augmented block designs

The International Institute for Science, Technology and Education (IISTE). Science, Technology and Medicine Journals Call for Academic Manuscripts

ANOVA.ppt

The document discusses analysis of variance (ANOVA) and experimental design. It explains that ANOVA allows testing the hypothesis of equality of multiple population means simultaneously, rather than conducting multiple pairwise t-tests. It describes the components of an ANOVA table including sources of variation (treatments, error), degrees of freedom, sums of squares, and mean squares. An example compares the yields of three potato varieties in a completely randomized design and demonstrates forming the ANOVA table to analyze the data.

Experimental Design presentation slides for level 400.pptx

for agriculture research bbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbb

Design of Experiments chapter 4 - 7.pptx

This is a class note prepared from Book Montgomery. It introduce different design of experiments also it includes examples.

Complete randomized block design - Sana Jamal Salih

The document describes the complete randomized block design (CRBD) experimental method. CRBD controls variation by dividing the experimental area into blocks of similar soil or environmental conditions. Treatments are randomly assigned to experimental units within each block. This design allows treatments to be directly compared while accounting for differences between blocks. The document provides details on blocking, plot size and shape, randomization procedures, statistical analysis methods, and advantages and disadvantages of the CRBD. An example is also presented to illustrate the design and analysis steps.

Anova ppt

This document provides an overview of analysis of variance (ANOVA). It describes how ANOVA was developed by R.A. Fisher in 1920 to analyze differences between multiple sample means. The document outlines the F-statistic used in ANOVA to compare between-group and within-group variations. It also describes one-way and two-way classifications of ANOVA and provides examples of applications in fields like agriculture, biology, and pharmaceutical research.

Chi square test

Chi square test- a test of association, Pearson's chi square test of independence, Goodness of fit test, chi square test of homogeneity, advantages and disadvantages of chi square test.

Assignment On Design Of Experiment

A randomized block design (RBD) is an experimental design where treatment factors are assigned to experimental units at random within each block. Blocking reduces variability between units by grouping similar units together. In an example RBD experiment comparing sales of new menu items, the restaurants were blocked by location to account for differences between locations. Statistical analysis found no significant difference between the mean sales of the three menu items, failing to reject the null hypothesis.

Contingency tables

1) The document discusses contingency tables and goodness-of-fit tests. It provides objectives, definitions, notation, requirements, and examples for conducting chi-square tests of independence and homogeneity using contingency tables.
2) One example tests whether the success of a treatment for a foot injury depends on the type of treatment administered. The chi-square test rejects independence between treatment and outcome, indicating the claim that they are independent is false.
3) A second example is given where data from 3 hospitals is to be tested to see if the number of patient infections depends on the hospital. The steps for conducting this chi-square test of homogeneity are outlined.

anovappt-141025002857-conversion-gate01 (1).pdf

1) Analysis of variance (ANOVA) is a statistical technique developed by R.A. Fisher in 1920 to analyze the differences between group means and their associated procedures.
2) ANOVA divides the total variation into different parts that can be attributed to various sources of variation - between groups, within groups, etc.
3) There are two main classifications of ANOVA - one-way ANOVA, which looks at the effect of one factor on the dependent variable, and two-way ANOVA, which analyzes the effects of two factors.
4) ANOVA has many applications in fields like pharmacy, biology, agriculture, and business research to study the effects of different treatments, products, or interventions.

Effectiveness of split plot design over randomized complete

The International Institute for Science, Technology and Education (IISTE). Science, Technology and Medicine Journals Call for Academic Manuscripts

Introduction and crd

This document provides an overview of experimental design and analysis of variance (ANOVA). It describes the basic principles of experimental design including randomization, replication, and error control. It defines key terms like treatments, experimental units, and experimental error. The document discusses different basic experimental designs like completely randomized design (CRD) and randomized block design (RBD). It also covers one-way and two-way ANOVA. Examples are provided to illustrate how to set up a simple CRD experiment and perform a one-way ANOVA to analyze the results. Post-hoc tests for comparing group means are also briefly mentioned.

chi-Square. test-

This document provides information about the chi-square test. It begins with an introduction to chi-square tests and their use in testing differences between observed and expected frequencies. It then discusses degrees of freedom, assumptions of chi-square tests, and applications like testing goodness of fit. Examples are provided to demonstrate chi-square calculations and comparing results to critical values. The document concludes that chi-square tests are useful statistical tools for analyzing group differences in non-parametric data.

Randomized complete block_design_rcbd_

Randomized complete block_design_rcbd_

Design of experiments(

Design of experiments(

Mech ma6452 snm_notes

Mech ma6452 snm_notes

Randomized-Complete-Block-Design.pdf

Randomized-Complete-Block-Design.pdf

factorial design.pptx

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7292015Intro to Biostatistics Homework #8Use R to calculate .docx

7292015Intro to Biostatistics Homework #8Use R to calculate .docx

Randomization Tests

Randomization Tests

Screening of new strains of sugarcane using augmented block designs

Screening of new strains of sugarcane using augmented block designs

ANOVA.ppt

ANOVA.ppt

Experimental Design presentation slides for level 400.pptx

Experimental Design presentation slides for level 400.pptx

Design of Experiments chapter 4 - 7.pptx

Design of Experiments chapter 4 - 7.pptx

Complete randomized block design - Sana Jamal Salih

Complete randomized block design - Sana Jamal Salih

Anova ppt

Anova ppt

Chi square test

Chi square test

Assignment On Design Of Experiment

Assignment On Design Of Experiment

Contingency tables

Contingency tables

anovappt-141025002857-conversion-gate01 (1).pdf

anovappt-141025002857-conversion-gate01 (1).pdf

Effectiveness of split plot design over randomized complete

Effectiveness of split plot design over randomized complete

Introduction and crd

Introduction and crd

chi-Square. test-

chi-Square. test-

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The document discusses various modern techniques for increasing crop yield, including genetic engineering, tissue culture, mutagenesis, molecular breeding, RNA interference, and nanotechnology. Genetic engineering techniques like agrobacterium-mediated transfer and biolistic transformation are used to introduce genes that increase stress resistance or yield. Tissue culture, mutagenesis, and molecular breeding also introduce beneficial traits. RNA interference works at the post-transcriptional level to silence genes. Nanoparticles like carbon nanotubes and titanium dioxide have been shown to enhance seed germination and plant growth. The overall aim of these techniques is to develop crop varieties with higher yields.

Breeding Methods for better quality fiber in Jute

Breeding methods can improve the quality of jute fiber. Key methods include hybridization to combine desirable traits, mutation breeding to induce traits like reduced lignin, and use of molecular markers to identify genes related to fiber quality. The objectives of jute breeding are to develop varieties with higher yield, better fiber quality, pest resistance, and short duration. Fiber quality traits like length, strength, and color are important breeding targets.

OAT “The future Fodder Crop

Oat is an important fodder crop that originated in Asia. It has many nutritional benefits for both humans and animals. Research institutions in Pakistan have developed high yielding oat varieties that are resistant and adapted to local conditions. Oat shows potential as a crop in Pakistan but is currently underutilized as a human food compared to wheat. More research is needed to develop new oat varieties and promote its uses.

Short Tandem Repeats in plants: Genomic distribution and function prediction

This document summarizes a study on short tandem repeats (STRs) in plants. The study identified over 283 million STRs across 140 plant species. Key findings include: STR abundance correlates with genome size and density varies between 9-58 kb/Mb. Hexanucleotide repeats are most common, comprising 30-64% of STRs. GC-rich STR motifs are more prevalent in high GC genomes. While STRs are mainly in noncoding regions, long STRs may influence gene expression and protein structure. The study provides insight into plant genetics but future work could focus on STR comparisons within genera and varieties.

QTL mapping current status and future prospects

This document discusses quantitative trait locus (QTL) mapping, including what a QTL is, the principles and objectives of QTL mapping, current methods used, and the status and future prospects. A QTL is a section of DNA related to variation in a quantitative trait. QTL mapping identifies genomic regions associated with traits using DNA markers. It can help detect genes influencing traits and provide insight into plant evolution. Current research uses QTL mapping to study abiotic stress tolerance in crops like rice and millet. Future areas of focus include expanding data to enable meta-analysis and using QTL data to inform other efforts like population genomics.

Germplasm Collection activities

This document summarizes a presentation on germplasm collection activities. It discusses the importance of germplasm collection for conservation and breeding purposes. It describes different sources and types of germplasm collection, as well as methods, components, and techniques for collection. Key institutions for germplasm storage in Pakistan and internationally are also outlined. Both merits such as conservation of genetic diversity and risks like disease entry are reviewed. The conclusion emphasizes the importance of collection to avoid loss of indigenous germplasm.

Modern Techniques For Yield Enhancement

Modern Techniques For Yield Enhancement

Breeding Methods for better quality fiber in Jute

Breeding Methods for better quality fiber in Jute

OAT “The future Fodder Crop

OAT “The future Fodder Crop

Short Tandem Repeats in plants: Genomic distribution and function prediction

Short Tandem Repeats in plants: Genomic distribution and function prediction

QTL mapping current status and future prospects

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Germplasm Collection activities

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The Diamonds of 2023-2024 in the IGRA collection

A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.

World environment day ppt For 5 June 2024

for world environment day

June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...

Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202

Main Java[All of the Base Concepts}.docx

This is part 1 of my Java Learning Journey. This Contains Custom methods, classes, constructors, packages, multithreading , try- catch block, finally block and more.

Introduction to AI for Nonprofits with Tapp Network

Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.

CACJapan - GROUP Presentation 1- Wk 4.pdf

Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.

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This slide is special for master students (MIBS & MIFB) in UUM. Also useful for readers who are interested in the topic of contemporary Islamic banking.
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Any substance (other than food) that is used to prevent, diagnose, treat, or relieve symptoms of a
disease or abnormal condition

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In this research, it concludes that while the readiness of teachers in Caloocan City to implement the MATATAG Curriculum is generally positive, targeted efforts in professional development, resource distribution, support networks, and comprehensive preparation can address the existing gaps and ensure successful curriculum implementation.

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আমাদের সবার জন্য খুব খুব গুরুত্বপূর্ণ একটি বই ..বিসিএস, ব্যাংক, ইউনিভার্সিটি ভর্তি ও যে কোন প্রতিযোগিতা মূলক পরীক্ষার জন্য এর খুব ইম্পরট্যান্ট একটি বিষয় ...তাছাড়া বাংলাদেশের সাম্প্রতিক যে কোন ডাটা বা তথ্য এই বইতে পাবেন ...
তাই একজন নাগরিক হিসাবে এই তথ্য গুলো আপনার জানা প্রয়োজন ...।
বিসিএস ও ব্যাংক এর লিখিত পরীক্ষা ...+এছাড়া মাধ্যমিক ও উচ্চমাধ্যমিকের স্টুডেন্টদের জন্য অনেক কাজে আসবে ...

Top five deadliest dog breeds in America

Thinking of getting a dog? Be aware that breeds like Pit Bulls, Rottweilers, and German Shepherds can be loyal and dangerous. Proper training and socialization are crucial to preventing aggressive behaviors. Ensure safety by understanding their needs and always supervising interactions. Stay safe, and enjoy your furry friends!

Thesis Statement for students diagnonsed withADHD.ppt

Presentation required for the master in Education.

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A workshop hosted by the South African Journal of Science aimed at postgraduate students and early career researchers with little or no experience in writing and publishing journal articles.The History of Stoke Newington Street Names

Presented at the Stoke Newington Literary Festival on 9th June 2024
www.StokeNewingtonHistory.com

The Diamonds of 2023-2024 in the IGRA collection

The Diamonds of 2023-2024 in the IGRA collection

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- 1. Principles of Experimental Design Presented By : Rana Asif Abbas Presented to: Dr Fahid Wattoo Course: PBG-507
- 2. Presentation outline: Definition Applications History Why we need? Principles
- 3. Definition of experimental design Experimental design is the branch of statistics that deals with design and analysis of experiment. The experiment design is the laying out of a detailed experimental plan in advance of doing the experiment that will maximize results Experimental design is a way to carefully plan experiment in advance so that your result are both objective and valid.
- 4. Applications of experimental design Agriculture Medicine Biology Industrial production The methods of experimental design are widely used in following fields
- 5. History of experimental design James Lind performed wee organize experiment in 1747 and developed a cure for scurvy. His experiment miss only randomization. Ronald fisher present methodology for designing experiment in his books His work fall under the first era(1918-1940) of design of experiment. The Arrangement of field experiments(1926) The design of experiment (1935).
- 6. Why we need experimental design From a statisticians perspective experiment is performed to decide: Weather there is actual difference among treatments and it is not due to difference in experimental units. Secondly wot is the size of difference among treatments But there is not always such ideal conditions that there is no variation among experimental units. So due to difference among experimental units, variation between treatments is caused other than actual difference need to be tested.
- 7. In simple words We need experimental design to control variability caused by other factors. So that the treatment effect can be identified prominently and accurately. Technically experimental design are for reduction of experimental error (The difference among experimental plots treated alike is called experimental error If experimental error is more , it mean the basic variation among treatment is due to chance. If experimental error is less it mean there is differ
- 8. Example Suppose there are two experimental plots x&y. A rice breeder has to do experiment to check the yield of two new varieties(A & B) he made. He sow variety A in X plot while variety B in Y plot. The results he got from this simple experiment are sure not be accurate. This is because along with the variety difference(treatment difference) , there are many other differences in plots like soil condition, moisture, sunlight etc. Even if he plant same variety A in plot x & Y he will get different results(experimental error) Breeder will follow principles of experimental design and design a suitable experiment for proper evaluation.
- 9. Principles of experimental design
- 10. Replication Reptation of basic experiment is called replication. Helps in getting more accurate estimate of experiment error. More replication means more precision. Replication reduce standard error. Example: Rice breeder, planted his variety A and B in more than one experimental units. The more number of time he plant any variety in experimental unit the more replication it would be. Variety A Variety B Replication 1 Plot 1 Plot 5 Replication 2 Plot 2 Plot 6 Replication 3 Plot 3 Plot 7 Replication 4 Plot 4 Plot 8 n=r= No of replications One Plots= one experimental unit
- 11. Randomization It is process of assigning the treatment to experimental units Each treatment has same probability to get a experimental unit. If treatments 3 (A,B,C) and replications 4 than no of experimental units = 12 . A C B C C B A B A C B A
- 12. Example Treatment Treatment Replication 1 Plot 1(A) Plot 5(B) Replication 2 Plot 2(A) Plot 6(B) Replication 3 Plot 3(A) Plot 7(B) Replication 4 Plot 4(A) Plot 8(B) Rice breeder having two treatments(variety A & B). Number of replications =4 Number of experimental units(plots)=8 The non-random layout is: There is chance for fertility gradient or any other biasness from one direction to other. Breeder follows any randomization method and have following layout. B A A B A B B A
- 13. Methods to do randomization BY Random number table By Drawing lots By Software(GEN STAT, Excel) By Cards
- 14. By Random number table Random number Sequence Rank 204 1 3 279 2 4 711 3 6 100 4 1 197 5 2 619 6 5 889 7 8 Assign the plot number from 1 -8. Open random number table and move finger any where from left to right with eyes close. Stop any where and select a three-digit number and move vertically to took 8 numbers. Write sequence of random numbers and rank from smallest to largest. Plot no Variety Sequence 1 A 1 2 A 2 3 A 3 4 A 4 5 B 5 6 B 6 7 B 7 8 B 8
- 15. Now assign the 8 treatments to 8 plots by seeing sequence corresponding to rank. E.g: The treatment A with sequence 1 will assigned to plot 3 because its rank is 3 Plot 1(A) Plot 5(B) Plot 2(B) Plot 6(A) Plot 3 (A) Plot 7(B) Plot 4(A) Plot 8(B) Remember: Rank correspond to new plot number
- 16. Local control Choose a design in such a manner that all extraneous sources of variation are brought under control Balancing Blocking Proper plot techniques
- 17. Blocking Arrangement of experimental units into blocks of similar entities is called as blocking. Blocking means that the like experimental units should be collected together to far relatively homogeneous groups. Observations collected under similar experimental conditions are grouped in the same block. Blocking reduces sources of deviations and thereby bringing more precision to the experimental design.
- 18. Balancing Balancing means that the treatment should be assigned to the experimental units in such a way that the result is a balanced arrangement of treatment.
- 19. Proper plot technique Plot with homogenous soil Equal slope Equal block size and shape Equal number of replications Removal of border plants Thinning Furrowing for row spacing Fertilizer application Labeling Pesticide application