In this presentation you can able to understand what is split and strip plot design along with that steps to forming ANOVA table and further calculation for critical differences by which you can determine whether the treatment is on par with other
This document describes split plot designs for agricultural experiments. Split plot designs are used when factors require different sized plots. Larger plots are used for factors that need more space, and these plots are divided into smaller subplots to accommodate factors with smaller space needs. The document provides an example of a split plot design layout and discusses how to analyze the data using ANOVA, accounting for the different error terms between main plots and subplots. Main advantages are increased precision and saving experimental resources, while disadvantages include less precision for estimates of main plot treatments and complex analysis with missing data.
Basic Concepts of Split-Plot Design,Analysis Of Covariance(ANCOVA)& Response ...Hasnat Israq
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 .
Split plot and strip plot designs are experimental designs that allow for factors to be tested at different levels of precision. In a split plot design, experimental units are nested within whole plots and split plots. Whole plots are randomly assigned to treatment levels of one factor (the whole plot factor), and split plots within whole plots are randomly assigned to treatment levels of another factor (the split plot factor). This allows the split plot factor to be tested with greater precision than the whole plot factor. Guidelines for assigning factors include testing the factor requiring greater precision at the split plot level. The analysis of variance separates effects into whole plot and split plot portions.
Weed indices are used to study the effect of weed density, growth, and suppression on crop plants. Common indices include weed infestation, weed index, weed control efficiency, and smothering efficiency. The document defines each of these indices and provides examples of how to calculate them. Higher values of weed control efficiency and smothering efficiency indicate better control of weeds. The weed index compares yields between treated and untreated plots, with lower values showing more effective herbicide treatment.
Conservation agriculture practices can help address problems with conventional agriculture in India like erratic rainfall, soil degradation, and high resource use. Minimum soil disturbance, permanent organic soil cover, and diversified crop rotations are the key principles of conservation agriculture. Adopting no-tillage and mulch farming can reduce runoff and evaporation, improve soil health, and increase water storage in the soil. Studies show conservation agriculture practices lead to higher yields and water use efficiency compared to conventional tillage and help promote a more sustainable agricultural system in India.
EFFECT OF MOISTURE STRESS ON PLANT GROWTH AND DEVELOPMENTSHRAVAN KUMAR REDDY
Moisture stress can negatively impact plant growth and development through various mechanisms. Crops have developed different adaptations to moisture stress including escaping drought through short lifecycles, avoiding stress through water conservation or improved uptake, and tolerating stress. Avoiding stress involves mechanisms like reducing leaf area, increasing waxiness, and regulating stomata to conserve water or developing deep, branched root systems and high root to shoot ratios to improve water uptake. Tolerating stress includes osmotic adjustment to maintain turgor under water deficits. Understanding crop adaptations is important for managing plants under moisture stress conditions.
This document describes split plot designs for agricultural experiments. Split plot designs are used when factors require different sized plots. Larger plots are used for factors that need more space, and these plots are divided into smaller subplots to accommodate factors with smaller space needs. The document provides an example of a split plot design layout and discusses how to analyze the data using ANOVA, accounting for the different error terms between main plots and subplots. Main advantages are increased precision and saving experimental resources, while disadvantages include less precision for estimates of main plot treatments and complex analysis with missing data.
Basic Concepts of Split-Plot Design,Analysis Of Covariance(ANCOVA)& Response ...Hasnat Israq
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 .
Split plot and strip plot designs are experimental designs that allow for factors to be tested at different levels of precision. In a split plot design, experimental units are nested within whole plots and split plots. Whole plots are randomly assigned to treatment levels of one factor (the whole plot factor), and split plots within whole plots are randomly assigned to treatment levels of another factor (the split plot factor). This allows the split plot factor to be tested with greater precision than the whole plot factor. Guidelines for assigning factors include testing the factor requiring greater precision at the split plot level. The analysis of variance separates effects into whole plot and split plot portions.
Weed indices are used to study the effect of weed density, growth, and suppression on crop plants. Common indices include weed infestation, weed index, weed control efficiency, and smothering efficiency. The document defines each of these indices and provides examples of how to calculate them. Higher values of weed control efficiency and smothering efficiency indicate better control of weeds. The weed index compares yields between treated and untreated plots, with lower values showing more effective herbicide treatment.
Conservation agriculture practices can help address problems with conventional agriculture in India like erratic rainfall, soil degradation, and high resource use. Minimum soil disturbance, permanent organic soil cover, and diversified crop rotations are the key principles of conservation agriculture. Adopting no-tillage and mulch farming can reduce runoff and evaporation, improve soil health, and increase water storage in the soil. Studies show conservation agriculture practices lead to higher yields and water use efficiency compared to conventional tillage and help promote a more sustainable agricultural system in India.
EFFECT OF MOISTURE STRESS ON PLANT GROWTH AND DEVELOPMENTSHRAVAN KUMAR REDDY
Moisture stress can negatively impact plant growth and development through various mechanisms. Crops have developed different adaptations to moisture stress including escaping drought through short lifecycles, avoiding stress through water conservation or improved uptake, and tolerating stress. Avoiding stress involves mechanisms like reducing leaf area, increasing waxiness, and regulating stomata to conserve water or developing deep, branched root systems and high root to shoot ratios to improve water uptake. Tolerating stress includes osmotic adjustment to maintain turgor under water deficits. Understanding crop adaptations is important for managing plants under moisture stress conditions.
This document discusses several indices for assessing land use in cropping systems:
- Multiple Cropping Index (MCI) measures total area cropped as a percentage of total land area.
- Cultivated Land Utilization Index (CLUI) calculates land area and duration of each crop as a percentage of total land area and time.
- Diversity Index (DI) measures crop diversity based on revenue from individual crops.
- Crop Intensity Index (CII) assesses actual land use over area and time compared to total available land and time.
- Harvest Diversity Index (HDI) is similar to DI but uses crop harvest values instead of revenues.
- Simultaneous Cro
A brief study on Integrated Nutrient Management (INM). This presentation has created by me after studying many articles and research papers regarding INM. Suggestions are kindly invited.
The document discusses the classification, formulations, and methods of application of herbicides. It describes how herbicides are classified based on their method of application, mode of action, mobility, and time of application. The document also outlines common herbicide formulations like emulsifiable concentrates, wettable powders, and granules. It provides details on application methods for both soil-applied and foliar-applied herbicides.
The document defines soil fertility as a soil's ability to supply essential nutrients to plants, while soil productivity refers to a soil's capacity to produce crops per unit area under a specified management system. Soil fertility relates to chemical capacity, while productivity is influenced by additional environmental factors. A fertile soil may not be productive, but a productive soil is always fertile. The document outlines differences between soil fertility and productivity and discusses inorganic and organic soils. Organic soils generally contain over 5% organic matter while inorganic soils contain less than 5%, and organic soils have greater water holding capacity and productivity potential when drained.
The document discusses crop ideotypes and ideotype breeding. It defines an ideotype as an ideal or model plant type designed for a specific environment to maximize yield. Ideotype breeding aims to enhance genetic yield potential through manipulation of individual plant traits. Examples of ideotypes are provided for various crops like wheat, rice, maize, barley and cotton that focus on traits like plant height, tillering ability, leaf characteristics and resistance to stresses. Factors influencing ideotypes and the steps in ideotype breeding are also outlined. Practical achievements highlighted ideotype breeding's role in the green revolution by developing semi-dwarf varieties responsive to fertilizers.
This document outlines the principles of weed management, including prevention, eradication, control, and management. Prevention focuses on stopping weed infestation through measures like using weed-free crop seeds, avoiding contamination of manure pits, and preventing the movement of weeds. Eradication aims to completely remove all parts of a weed from an area and is justified for noxious weeds, while control reduces weed infestations without elimination. Weed management takes a systems approach to minimize weed invasion and give crops a competitive advantage over weeds.
Pulses are a very important source of protein in Indian diets as majority of population is vegetarian. however, the production of pulses is not keeping pace with the growing population in the country. lentil is one of the important Rabi pulses. it is one of the oldest pulse crops and the most nutritious of the pulses. it is also used as a cover crop to check the soil erosion in problem areas. lentil contributes about 6% in total pulses area as well as production of India. It is mostly eaten as "DAL". the pulse is first converted into split pulse or 'dal' by the removal of skin and the separation of the fleshy cotyledons. It is cooked easily and hence preferred. It is good for patients too. Lentil contains about 11% water, 25% protein and 60% carbohydrates. It is also rich in calcium, iron and niacin
The document discusses crop-weather modeling. It defines crop-weather modeling as using mathematical models to simulate crop growth and yield based on temperature, day length, and other weather parameters. It notes that crop-weather models have various applications, including optimizing management, predicting impacts of climate change, and performing "what-if" experiments. The document also outlines different types of crop models and lists some advantages of crop-weather modeling, such as reducing field experiments and helping to maximize agricultural production.
Crop modeling for stress situations, cropping system , assessing stress through remote sensing, understanding the adaptive features of crops for survival under stress .
Dryland farming refers to cultivation of crops in regions receiving less than 750mm of annual rainfall without artificial irrigation. The document discusses dryland farming in India, including that over 69.5% of cultivated area is rainfed. It describes challenges like uncertain rainfall, drought, and poor soil quality. It provides strategies for dryland farming such as moisture conservation tillage, appropriate crops and cultivars with deep roots and drought resistance, and contingency crop planning for unpredictable rainfall. The document emphasizes maximizing production through alternative cropping patterns and conserving soil moisture.
Seed treatment, Seed germination and crop establishment in relation to soil m...Alkesh Patel
Detailed information about the seed treatments, methods of seed treatments, different equipment used in seed treatments, seed germination, component related to seed germination and establishment of crop in relation to soil moisture content.
To get the presentation contact me on alkesh.patel,2711@gmail.com
The document discusses the pedigree selection method for plant breeding. It begins by explaining that the pedigree method was first outlined in 1927 and involves selecting individual plants from segregating generations and recording their progeny relationships until homozygosity is reached.
It then notes that a pedigree record details the relationships between selected plants and their progeny, and is helpful for determining genetic relatedness. The pedigree method is commonly used for self-pollinated crops to select for specific traits like disease resistance over multiple generations. While it is effective for simply inherited traits and faster than bulk methods, maintaining accurate pedigree records takes time and skill from breeders.
1. The document discusses nutrient use efficiency and factors that affect it, such as leaching, gaseous losses, immobilization, and chemical reactions between fertilizer components.
2. It describes methods of increasing fertilizer use efficiency, including applying fertilizers at the right time and quantity, and using the proper fertilizer source and form for different crops to minimize fixation and maximize availability.
3. Integrated nutrient management is defined as maintaining soil fertility and nutrient supply through optimizing organic, inorganic, and biological components to provide balanced nutrition for crops while sustaining soil quality.
This document summarizes key aspects of the randomized complete block design (RCBD). It begins by introducing blocking to account for nuisance factors. It then describes how to conduct an experiment as an RCBD, including assigning treatments to blocks and analyzing the data. Statistical models for the RCBD are presented along with equations for estimating parameters and testing hypotheses. Residual plots are discussed for checking assumptions. The document concludes by covering additional RCBD topics like interactions, sample size choice, and estimating missing values.
Soil fertility evaluation and fertilizer recommendationBharathM64
This document discusses different approaches for evaluating soil fertility and determining fertilizer recommendations, including soil analysis, plant analysis, and visual deficiency symptoms. It describes methods for both rapid tissue tests of fresh plant parts and total laboratory analysis of dried plant materials. Diagnosis and recommendations can be generalized, based on soil test ratings with adjustments, or use the soil test crop response and target yield concept to determine fertilizer doses needed to achieve specific yields.
Grass cutting is the major time-consuming operation in the maintenance of any turfgrass area. Good mowing practices are perhaps the most important single factor contributing to a well-groomed appearance and the longevity of any turfgrass area.
Determination of nutrient need for yield potentiality of crop plantsPreetam Rathore
Crop nutrient needs cannot be met by soil alone, so external fertilizers are needed to achieve yield potential. Three concepts are used to determine fertilizer recommendations: maintenance, cation saturation ratio, and sufficiency level. Precision tools like GPS, sensors, and variable-rate controllers can help tailor fertilizer applications to site-specific crop needs within fields. Field experiments are conducted to develop response equations relating yield to fertilizer levels and determine economic optimum doses.
Unit 1 lecture-1 soil fertility and soil productivityLuxmiKantTripathi
The document discusses the concepts of soil fertility and productivity, outlining key factors that affect each such as parent material, climate, organic matter and crop management practices. It also reviews the history of understanding soil fertility from ancient Greek and Roman scholars to modern scientists who established theories of plant nutrition and developed agricultural experiments. The overall goal is for students to understand essential plant nutrients and their roles in agriculture and crop production.
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.
This document discusses several methods for analyzing drug release from formulations, including similarity factors F1 and F2, Higuchi and Korsmeyer-Peppas models, linearity concept of significance, standard deviation, chi-square test, student-t test, and ANOVA test. It provides definitions and applications of these methods. Similarity factors F1 and F2 are used to compare dissolution profiles and determine if they are similar. The Higuchi and Korsmeyer-Peppas models can be used to describe drug release kinetics from matrix systems. Linearity, standard deviation, chi-square, t-test and ANOVA are statistical tests used to determine the significance and accuracy of results.
This document discusses several indices for assessing land use in cropping systems:
- Multiple Cropping Index (MCI) measures total area cropped as a percentage of total land area.
- Cultivated Land Utilization Index (CLUI) calculates land area and duration of each crop as a percentage of total land area and time.
- Diversity Index (DI) measures crop diversity based on revenue from individual crops.
- Crop Intensity Index (CII) assesses actual land use over area and time compared to total available land and time.
- Harvest Diversity Index (HDI) is similar to DI but uses crop harvest values instead of revenues.
- Simultaneous Cro
A brief study on Integrated Nutrient Management (INM). This presentation has created by me after studying many articles and research papers regarding INM. Suggestions are kindly invited.
The document discusses the classification, formulations, and methods of application of herbicides. It describes how herbicides are classified based on their method of application, mode of action, mobility, and time of application. The document also outlines common herbicide formulations like emulsifiable concentrates, wettable powders, and granules. It provides details on application methods for both soil-applied and foliar-applied herbicides.
The document defines soil fertility as a soil's ability to supply essential nutrients to plants, while soil productivity refers to a soil's capacity to produce crops per unit area under a specified management system. Soil fertility relates to chemical capacity, while productivity is influenced by additional environmental factors. A fertile soil may not be productive, but a productive soil is always fertile. The document outlines differences between soil fertility and productivity and discusses inorganic and organic soils. Organic soils generally contain over 5% organic matter while inorganic soils contain less than 5%, and organic soils have greater water holding capacity and productivity potential when drained.
The document discusses crop ideotypes and ideotype breeding. It defines an ideotype as an ideal or model plant type designed for a specific environment to maximize yield. Ideotype breeding aims to enhance genetic yield potential through manipulation of individual plant traits. Examples of ideotypes are provided for various crops like wheat, rice, maize, barley and cotton that focus on traits like plant height, tillering ability, leaf characteristics and resistance to stresses. Factors influencing ideotypes and the steps in ideotype breeding are also outlined. Practical achievements highlighted ideotype breeding's role in the green revolution by developing semi-dwarf varieties responsive to fertilizers.
This document outlines the principles of weed management, including prevention, eradication, control, and management. Prevention focuses on stopping weed infestation through measures like using weed-free crop seeds, avoiding contamination of manure pits, and preventing the movement of weeds. Eradication aims to completely remove all parts of a weed from an area and is justified for noxious weeds, while control reduces weed infestations without elimination. Weed management takes a systems approach to minimize weed invasion and give crops a competitive advantage over weeds.
Pulses are a very important source of protein in Indian diets as majority of population is vegetarian. however, the production of pulses is not keeping pace with the growing population in the country. lentil is one of the important Rabi pulses. it is one of the oldest pulse crops and the most nutritious of the pulses. it is also used as a cover crop to check the soil erosion in problem areas. lentil contributes about 6% in total pulses area as well as production of India. It is mostly eaten as "DAL". the pulse is first converted into split pulse or 'dal' by the removal of skin and the separation of the fleshy cotyledons. It is cooked easily and hence preferred. It is good for patients too. Lentil contains about 11% water, 25% protein and 60% carbohydrates. It is also rich in calcium, iron and niacin
The document discusses crop-weather modeling. It defines crop-weather modeling as using mathematical models to simulate crop growth and yield based on temperature, day length, and other weather parameters. It notes that crop-weather models have various applications, including optimizing management, predicting impacts of climate change, and performing "what-if" experiments. The document also outlines different types of crop models and lists some advantages of crop-weather modeling, such as reducing field experiments and helping to maximize agricultural production.
Crop modeling for stress situations, cropping system , assessing stress through remote sensing, understanding the adaptive features of crops for survival under stress .
Dryland farming refers to cultivation of crops in regions receiving less than 750mm of annual rainfall without artificial irrigation. The document discusses dryland farming in India, including that over 69.5% of cultivated area is rainfed. It describes challenges like uncertain rainfall, drought, and poor soil quality. It provides strategies for dryland farming such as moisture conservation tillage, appropriate crops and cultivars with deep roots and drought resistance, and contingency crop planning for unpredictable rainfall. The document emphasizes maximizing production through alternative cropping patterns and conserving soil moisture.
Seed treatment, Seed germination and crop establishment in relation to soil m...Alkesh Patel
Detailed information about the seed treatments, methods of seed treatments, different equipment used in seed treatments, seed germination, component related to seed germination and establishment of crop in relation to soil moisture content.
To get the presentation contact me on alkesh.patel,2711@gmail.com
The document discusses the pedigree selection method for plant breeding. It begins by explaining that the pedigree method was first outlined in 1927 and involves selecting individual plants from segregating generations and recording their progeny relationships until homozygosity is reached.
It then notes that a pedigree record details the relationships between selected plants and their progeny, and is helpful for determining genetic relatedness. The pedigree method is commonly used for self-pollinated crops to select for specific traits like disease resistance over multiple generations. While it is effective for simply inherited traits and faster than bulk methods, maintaining accurate pedigree records takes time and skill from breeders.
1. The document discusses nutrient use efficiency and factors that affect it, such as leaching, gaseous losses, immobilization, and chemical reactions between fertilizer components.
2. It describes methods of increasing fertilizer use efficiency, including applying fertilizers at the right time and quantity, and using the proper fertilizer source and form for different crops to minimize fixation and maximize availability.
3. Integrated nutrient management is defined as maintaining soil fertility and nutrient supply through optimizing organic, inorganic, and biological components to provide balanced nutrition for crops while sustaining soil quality.
This document summarizes key aspects of the randomized complete block design (RCBD). It begins by introducing blocking to account for nuisance factors. It then describes how to conduct an experiment as an RCBD, including assigning treatments to blocks and analyzing the data. Statistical models for the RCBD are presented along with equations for estimating parameters and testing hypotheses. Residual plots are discussed for checking assumptions. The document concludes by covering additional RCBD topics like interactions, sample size choice, and estimating missing values.
Soil fertility evaluation and fertilizer recommendationBharathM64
This document discusses different approaches for evaluating soil fertility and determining fertilizer recommendations, including soil analysis, plant analysis, and visual deficiency symptoms. It describes methods for both rapid tissue tests of fresh plant parts and total laboratory analysis of dried plant materials. Diagnosis and recommendations can be generalized, based on soil test ratings with adjustments, or use the soil test crop response and target yield concept to determine fertilizer doses needed to achieve specific yields.
Grass cutting is the major time-consuming operation in the maintenance of any turfgrass area. Good mowing practices are perhaps the most important single factor contributing to a well-groomed appearance and the longevity of any turfgrass area.
Determination of nutrient need for yield potentiality of crop plantsPreetam Rathore
Crop nutrient needs cannot be met by soil alone, so external fertilizers are needed to achieve yield potential. Three concepts are used to determine fertilizer recommendations: maintenance, cation saturation ratio, and sufficiency level. Precision tools like GPS, sensors, and variable-rate controllers can help tailor fertilizer applications to site-specific crop needs within fields. Field experiments are conducted to develop response equations relating yield to fertilizer levels and determine economic optimum doses.
Unit 1 lecture-1 soil fertility and soil productivityLuxmiKantTripathi
The document discusses the concepts of soil fertility and productivity, outlining key factors that affect each such as parent material, climate, organic matter and crop management practices. It also reviews the history of understanding soil fertility from ancient Greek and Roman scholars to modern scientists who established theories of plant nutrition and developed agricultural experiments. The overall goal is for students to understand essential plant nutrients and their roles in agriculture and crop production.
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.
This document discusses several methods for analyzing drug release from formulations, including similarity factors F1 and F2, Higuchi and Korsmeyer-Peppas models, linearity concept of significance, standard deviation, chi-square test, student-t test, and ANOVA test. It provides definitions and applications of these methods. Similarity factors F1 and F2 are used to compare dissolution profiles and determine if they are similar. The Higuchi and Korsmeyer-Peppas models can be used to describe drug release kinetics from matrix systems. Linearity, standard deviation, chi-square, t-test and ANOVA are statistical tests used to determine the significance and accuracy of results.
Experimental Design presentation slides for level 400.pptxSethKoomson1
for agriculture research bbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbb
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
Chi-square is a non-parametric test used to compare observed data with expected data. It can test goodness of fit, independence of attributes, and homogeneity. The document provides an introduction to chi-square terms and calculations including contingency tables, expected and observed frequencies, degrees of freedom, and test steps. Examples demonstrate applying chi-square to test the effectiveness of chloroquine and inoculation. Both examples find the null hypothesis of no effect can be rejected, indicating the treatments were effective.
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.
This document provides information about statistical tests that can be used to make inferences when comparing two samples or populations. Specifically, it discusses:
- Tests for comparing two proportions, means, variances or standard deviations from independent and dependent samples using z-tests, t-tests and F-tests.
- The assumptions and procedures for each test, including how to determine critical values and calculate test statistics.
- Examples of how to perform hypothesis tests and construct confidence intervals for various statistical comparisons between two samples or populations using a TI calculator.
The chi-square test is used to determine if an observed frequency distribution differs from an expected theoretical distribution. It can test goodness of fit, independence of attributes, and homogeneity. The test involves calculating chi-square by taking the sum of the squares of the differences between observed and expected frequencies divided by expected frequencies. For the test to be valid, certain conditions must be met regarding sample size, expected frequencies, independence, and randomness. The test has some limitations such as not measuring strength of association and being unreliable with small expected frequencies.
Complete randomized block design - Sana Jamal SalihSana 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.
A chi-squared test is a statistical hypothesis test that is valid to perform when the test statistic is chi-squared distributed under the null hypothesis, specifically Pearson's chi-squared test and variants
differences between the observed values
This document discusses various optimization techniques used in pharmaceutical development. It begins with defining optimization and providing an outline of topics to be covered, including key terms, parameters, experimental designs, applied methods, and references. Experimental designs discussed include factorial, response surface, central composite, Box-Behnken, Plackett-Burman, and Taguchi designs. Applied optimization methods include classic optimization techniques using calculus as well as statistical methods like EVOP. The objective of pharmaceutical optimization is to develop the optimal formulation while reducing costs through fewer experiments.
1. The document discusses the problem of autocorrelation in regression analysis and time series data. Autocorrelation violates the assumption in classical linear regression models that error terms are independent.
2. Several potential causes of autocorrelation are described, including inertia in time series, omitted variables, incorrect functional form specification, lags, data transformation techniques, and dynamic relationships between variables.
3. Detecting and correcting for autocorrelation is important for obtaining accurate estimates and inferences from regression analyses involving time series data.
Experiments
A Quick History of Design of Experiments
Why We Use Experimental Designs
What is Design of Experiment
How Design of Experiment contributes
Terminology
Analysis Of Variation (ANOVA)
Basic Principle of Design of Experiments
Some Experimental Designs
The t-test is used to test hypotheses about population means when the population variance is unknown. It is closely related to the z-test but uses the t distribution instead of the normal. There are three main types of t-tests: single sample, independent samples, and dependent samples. The t-test compares the sample mean to the population mean and takes into account factors like sample size and variability. Larger sample sizes and stronger associations between variables increase the power of the t-test to detect significant differences or relationships.
The document discusses different experimental design methods. It describes completely randomized design (CRD) where treatments are randomly assigned to experimental units. It also describes randomized complete block design (RCBD) which controls for variation by grouping similar units into blocks. Each block receives one of each treatment. Finally, it discusses Latin square design which controls for two blocking factors by arranging treatments so they each occur once in each row and column.
Quantitative Analysis for Emperical ResearchAmit Kamble
Overview for Approach Methods for quantitative analysis; which includes
1) Planning of Experiments
2) Data Generation
3) presentation of report
some numerical approach methods; data modeling; hypothesis methods
The document discusses design of experiments (DOE) and provides details about:
1) DOE is a process optimization technique that relies on planned experimentation and statistical analysis to study multiple factors and their interactions.
2) Traditional experimentation methods study one factor at a time and ignore interactions, while DOE allows studying multiple factors and interactions using fewer experiments.
3) Steps for DOE include defining objectives, factors, responses, levels, and designing the experiment using full or fractional factorial designs such as orthogonal arrays.
The chi-square test is used to determine if an observed distribution of data differs from the theoretical distribution. It compares observed frequencies to expected frequencies based on a hypothesis. The chi-square value is calculated by summing the squared differences between observed and expected frequencies divided by the expected frequency. The chi-square value is then compared to a critical value from the chi-square distribution table based on the degrees of freedom. If the chi-square value is greater than the critical value, the null hypothesis that the distributions are the same can be rejected.
This document discusses various statistical tests used to analyze dental research data, including parametric and non-parametric tests. It provides information on tests of significance such as the t-test, Z-test, analysis of variance (ANOVA), and non-parametric equivalents. Key points covered include the differences between parametric and non-parametric tests, assumptions and applications of the t-test, Z-test, ANOVA, and non-parametric alternatives like the Mann-Whitney U test and Kruskal-Wallis test. Examples are provided to illustrate how to perform and interpret common statistical analyses used in dental research.
Introduction
Chi square
Categorical data
2x2 contingency table
Yates correction
rxccontingency table
Mc Nemar test
The Cochran-Mantel-Haenszel test
The Kappa Statistic
X2 goodness of fit
Problem solving
References
Similar to critical differences in split plot and strip plot design.pptx (20)
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.
Walmart Business+ and Spark Good for Nonprofits.pdfTechSoup
"Learn about all the ways Walmart supports nonprofit organizations.
You will hear from Liz Willett, the Head of Nonprofits, and hear about what Walmart is doing to help nonprofits, including Walmart Business and Spark Good. Walmart Business+ is a new offer for nonprofits that offers discounts and also streamlines nonprofits order and expense tracking, saving time and money.
The webinar may also give some examples on how nonprofits can best leverage Walmart Business+.
The event will cover the following::
Walmart Business + (https://business.walmart.com/plus) is a new shopping experience for nonprofits, schools, and local business customers that connects an exclusive online shopping experience to stores. Benefits include free delivery and shipping, a 'Spend Analytics” feature, special discounts, deals and tax-exempt shopping.
Special TechSoup offer for a free 180 days membership, and up to $150 in discounts on eligible orders.
Spark Good (walmart.com/sparkgood) is a charitable platform that enables nonprofits to receive donations directly from customers and associates.
Answers about how you can do more with Walmart!"
How to Add Chatter in the odoo 17 ERP ModuleCeline George
In Odoo, the chatter is like a chat tool that helps you work together on records. You can leave notes and track things, making it easier to talk with your team and partners. Inside chatter, all communication history, activity, and changes will be displayed.
Main Java[All of the Base Concepts}.docxadhitya5119
This is part 1 of my Java Learning Journey. This Contains Custom methods, classes, constructors, packages, multithreading , try- catch block, finally block and more.
Exploiting Artificial Intelligence for Empowering Researchers and Faculty, In...Dr. Vinod Kumar Kanvaria
Exploiting Artificial Intelligence for Empowering Researchers and Faculty,
International FDP on Fundamentals of Research in Social Sciences
at Integral University, Lucknow, 06.06.2024
By Dr. Vinod Kumar Kanvaria
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UPRAHUL
This Dissertation explores the particular circumstances of Mirzapur, a region located in the
core of India. Mirzapur, with its varied terrains and abundant biodiversity, offers an optimal
environment for investigating the changes in vegetation cover dynamics. Our study utilizes
advanced technologies such as GIS (Geographic Information Systems) and Remote sensing to
analyze the transformations that have taken place over the course of a decade.
The complex relationship between human activities and the environment has been the focus
of extensive research and worry. As the global community grapples with swift urbanization,
population expansion, and economic progress, the effects on natural ecosystems are becoming
more evident. A crucial element of this impact is the alteration of vegetation cover, which plays a
significant role in maintaining the ecological equilibrium of our planet.Land serves as the foundation for all human activities and provides the necessary materials for
these activities. As the most crucial natural resource, its utilization by humans results in different
'Land uses,' which are determined by both human activities and the physical characteristics of the
land.
The utilization of land is impacted by human needs and environmental factors. In countries
like India, rapid population growth and the emphasis on extensive resource exploitation can lead
to significant land degradation, adversely affecting the region's land cover.
Therefore, human intervention has significantly influenced land use patterns over many
centuries, evolving its structure over time and space. In the present era, these changes have
accelerated due to factors such as agriculture and urbanization. Information regarding land use and
cover is essential for various planning and management tasks related to the Earth's surface,
providing crucial environmental data for scientific, resource management, policy purposes, and
diverse human activities.
Accurate understanding of land use and cover is imperative for the development planning
of any area. Consequently, a wide range of professionals, including earth system scientists, land
and water managers, and urban planners, are interested in obtaining data on land use and cover
changes, conversion trends, and other related patterns. The spatial dimensions of land use and
cover support policymakers and scientists in making well-informed decisions, as alterations in
these patterns indicate shifts in economic and social conditions. Monitoring such changes with the
help of Advanced technologies like Remote Sensing and Geographic Information Systems is
crucial for coordinated efforts across different administrative levels. Advanced technologies like
Remote Sensing and Geographic Information Systems
9
Changes in vegetation cover refer to variations in the distribution, composition, and overall
structure of plant communities across different temporal and spatial scales. These changes can
occur natural.
2. SPLIT PLOT DESIGN
• A split-plot design is an experimental design
in which researchers are interested in studying
two factors in which:
One of the factors is “easy” to change or vary.
One of the factors is “hard” to change or vary.
• This type of design was developed in 1925 by
mathematician Ronald Fisher for use in
agricultural experiments.
3. • It occurs in factors which require larger plots than
for others.
• Eg: Experiments on Tillage and Irrigation require
larger plots whereas experiments on Fertilizers
and Herbicides require no larger plots.
• Larger plots are split into smaller plots to
accommodate the other factors; different
treatment where alloted at random to their
respective plots – Split plot design.
5. CRITICAL DIFFERENCE
• Critical Difference is used to compare means
of different treatments that have an equal
number of replications.
6. • Treatment 1 (T1) is significantly different from Treatment 2 (T2) as their difference is
more than the Critical Difference you have calculated here. (T1-T2 i.e. 10.62 – 5.21 =
5.41 > 0.978887)
• But Treatment 1 (T1) statistically does not differ significantly from Treatment 6 (T6),
as their difference is less than the Critical Difference you have calculated here (T1-T6
i.e. 10.62 – 10.25 = 0.37 < 0.978887)
7. 1. As Treatment 1 (T1) significantly out-yielded -
Treatment (T2) and will likely do so again in
future field trials,
2. But as Treatment 1 (T1) statistically does not
differ significantly from Treatment 6 (T6) i.e.
Treatment 1 (T1) was statistically similar to
Treatment 6 (T6). so
– The treatment effects on yield were similar
– The observed differences are likely due to
simply random chance or background "noise,"
and
– The apparent trends in treatment yields (T1>T6)
would likely not be repeated in subsequent trials
comparing these same treatments.
8. CONFIDENCE LEVEL
• The confidence level, which we usually take
either 90 or 95 percent.
• Confidence level can be identified by its
corresponding alpha value:
• A 95 percent confidence level has an alpha of 5
% (p < 0.05)
• and a 90 percent confidence level has
an alpha of 10 % (p< 0.1).
• A 90 percent confidence level means there is still
a 10 percent chance that, the difference was
actually due to natural variation.
28. STRIP PLOT DESIGN
• This design is also known as split block design. When
there are two factors in an experiment and both the
factors require large plot sizes it is difficult to carryout
the experiment in split plot design.
• Also the precision for measuring the interaction effect
between the two factors is higher than that for
measuring the main effect of either one of the two
factors. Strip plot design is suitable for such
experiments.
• In strip plot design each block or replication is divided
into number of vertical and horizontal strips depending
on the levels of the respective factors.
29. • In this split-plot design, Irrigation was implemented first followed by
a split into two parts. Two fertilizers were randomized among the
split plots.
In the split-block design, the “plots” are split
horizontally and vertically according to how many levels are present
in the experiment. In other words, the first, whole-plot factor is
completely crossed with a second factor.
30. Compute Correction Factor = (GT)²
-------------
a X b X r
TSS = Σyijk ²- CF
Trt SS = ΣYij²/r - CF
Blk SS= ΣY..k²/ ra - CF
31. 1) Vertical Strip Analysis
Form A x R Table and calculate RSS, ASS and
Error(a) SS
32.
33. 2) Horizontal Strip Analysis
• Form B x R Table and calculate RSS, BSS and Error(b)
SS