myaseen208
Thoughts on Statistics, R, Python, LaTeX, Research and other distractions.Topics covered
ancova
anova
bioinformatics
coronavirus
data
data-science
data-visulization
diallel-analysis
dmaic
google-apps
latex
linear-mixed-models
linear-model
pakistan
pakistan-population-census-2017
ppcspatial
python
quality-control
r
regression-analysis
research
six-sigma
spss
statistics
veterinary-research
All myaseen208 posts by date
2020 Coronavirus Pandemic in Pakistan
Design & Analysis of Field Experiments using R
Introduction Regression Analysis Simple Linear Regression Example Example Example Multiple Linear Regression Example Polynomial Regression Analysis Example Analysis of Variance (ANOVA) Example Example Analysis of Covariance (ANCOVA) Example Same intercepts but different slopes Different intercepts and different slopes Correlation Analysis Simple Correlation Analysis Example Partial Correlation Analysis Example Multiple Correlation Analysis Example Completely Randomized Design (CRD) Example Randomized Complete Block Design (RCBD) Example Latin Square Design Example Factorial Experiment under RCBD Stability Analysis Individual Analysis of Variance for each Location Combined Analysis of Variance Additive Main Effects and Multiplicative Interaction (AMMI) Analysis Additive Main Effects and Multiplicative Interaction (AMMI) Biplot Analysis Genotype plus Genotypes by Environment (GGE) Interaction Biplot Analysis Introduction R is a free, open-source programming language and software environment for statistical computing, bioinformatics, visualization and general computing.Training Course on Capacity Building of NARS Scientists in Advance Analytical Techniques
Introduction Regression Analysis Simple Linear Regression Example Example Example Multiple Linear Regression Example Polynomial Regression Analysis Example Analysis of Variance (ANOVA) Example Example Analysis of Covariance (ANCOVA) Example Same intercepts but different slopes Different intercepts and different slopes Correlation Analysis Simple Correlation Analysis Example Partial Correlation Analysis Example Multiple Correlation Analysis Example Completely Randomized Design (CRD) Example Randomized Complete Block Design (RCBD) Example Latin Square Design Example Factorial Experiment under RCBD Stability Analysis Individual Analysis of Variance for each Location Combined Analysis of Variance Additive Main Effects and Multiplicative Interaction (AMMI) Analysis Additive Main Effects and Multiplicative Interaction (AMMI) Biplot Analysis Genotype plus Genotypes by Environment (GGE) Interaction Biplot Analysis Introduction R is a free, open-source programming language and software environment for statistical computing, bioinformatics, visualization and general computing.How to wrtie a Research Paper and Hands on Training of SPSS - A Statistical Tool
Introduction Statistics Variable Measurement Measurement Scales Descriptive Statistics Example Boxwhisker Diagram Example Regression Analysis Simple Linear Regression Example Exercise Exercise Multiple Linear Regression Example Correlation Analysis Simple Correlation Analysis Example Partial Correlation Analysis Example Introduction Statistics Statistics deals with uncertainty & variability Statistics turns data into information Data -> Information -> Knowledge -> Wisdom Statistics is the interpretation of Science Statistics is the Art & Science of learning from data Variable Characteristic that may vary from individual to individual Measurement Process of assigning numbers or labels to objects or states in accordance with logically accepted rules Measurement Scales Nominal Scale: Obersvations may be classified into mutually exclusive & exhaustive categories Ordinal Scale: Obersvations may be ranked Interval Scale: Difference between obersvations is meaningful Ratio Scale: Ratio between obersvations is meaningful & true zero point Descriptive Statistics No of observations Measures of Central Tendency Measures of Dispersion Measures of Skewness Measures of Kurtosis Example Fertilizer (Kg/acre) Production (Bushels/acre) 100 70 200 70 400 80 500 100 Analyze > Descriptive Statistics > Descriptives …Linear Model using Python
Python Basics Variables and Data Types Variable Assignment Calculations With Variables Types and Type Conversion Logical Operators Comparison If-Else Function Help Simple Linear Regression Multiple Linear Regression Polynomial Regression Regression with Dummy Variables Example 1 Example 2 Example 3 Regression with same slopes and different intercepts Regression with different slopes and different intercepts Python Basics Variables and Data Types Variable Assignment x = 5 x # dir(x) 5 Calculations With Variables x + 2 # Sum of two variables 7 x - 2 # Subtraction of two variables 3 x*2 # Multiplication of two variables 10 x**2 # Exponentiation of a variable 25 x%2 # Remainder of a variable 1 x/float(2) # Division of a variable 2.Improving Quality in Textile Industry using Six Sigma with R