Publications by Muhammad Farhaad
Detailed Linear Regression Analysis
Introduction In this section, we’ll delve into the details of a linear regression analysis conducted on our dataset. The aim is to understand the impact of both a categorical variable (Category) and a quantitative variable (QuantVar) on our response variable (ResponseVar). Data Preparation We’ve previously prepared the dataset, recoding th...
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Multiple Regression Analysis Summary
title: “Multiple Regression Analysis Summary” author: “Muhammad Farhaad” date: “02/19/2024” output: html_document — Multiple Regression Analysis Summary Introduction In this analysis, we conducted a multiple regression to examine the relationships between several explanatory variables and our response variable. The dataset used f...
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Interactive Linear Regression Analysis Program
Introduction In this analysis, we’ll perform a basic linear regression model to explore the association between a response variable (ResponseVar) and an explanatory variable (ExplanatoryVar). Customize the variables as needed. Input Selection Shiny applications not supported in static R Markdown documents Output Display The user can interact...
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Analysis of Variance Blog
Introduction In this blog post, we will explore the analysis of variance (ANOVA) in the context of a synthetic dataset. ANOVA helps us assess whether the means of two or more groups are statistically different from each other. Synthetic Dataset Let’s generate a synthetic dataset for illustration purposes. set.seed(123) # for reproducibility ...
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Chi-Square Test of Independence Analysis
Understanding Relationships with Chi-Square Test In this analysis, we will explore the relationship between two categorical variables using the Chi-Square Test of Independence. This statistical test helps us determine whether there is a significant association between the variables, providing valuable insights into the data. Generating Random ...
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Correlation Coefficient Analysis
Introduction In this analysis, we will explore the correlation between two variables using the correlation coefficient. The correlation coefficient assesses the degree of linear relationship between two variables, ranging from +1 to -1. Objective The objective of this analysis is to calculate and interpret the correlation coefficient between �...
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Testing Moderation: An Exploration of Statistical Methods
Introduction In the field of statistical analysis, testing moderation plays a crucial role in understanding the relationship between different constructs within a sample. In this blog post, we will explore the process of testing moderation using statistical methods like ANOVA, Chi-Square Test, or correlation coefficient. Understanding Moderati...
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Unveiling the Layers of Data Analysis: A Comprehensive Exploration
Introduction Embarking on a journey of data analysis requires not only statistical prowess but also a profound understanding of the dataset under scrutiny. In this blog post, I delve into the intricate layers of my data analysis project, shedding light on the sample, data collection procedure, and the measures employed to address my research qu...
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Data Analysis Blog: Exploring Frequency Distributions
Introduction This week’s focus was on running frequency distributions on a chosen dataset. In this blog post, I’ll walk you through the steps I took to run my first program, display frequency distributions for selected variables, and provide insights into the values and patterns observed. Step 1: Running the First Program # Load necessary ...
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DocumentExploring the Association Between Smoking Levels and Nicotine Dependence M
Introduction In this blog, I will document my process of exploring the association between smoking levels and nicotine dependence using randomly generated data. Step 1: Generate Random Data Let’s create some random data for illustration purposes. # Set a seed for reproducibility set.seed(123) # Generate random data nesarc_data <- data.fram...
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