Publications by Will Henderson
HW3
Q1 Reproduce the covariance matrix in the upper right part of Table 4.1 from the correlations and standard deviations in the upper left part of the table. # Install Packages library(mvtnorm) # Enter the covariance/correlation matrix x <- as.matrix(data.frame(c(1.000, .2721, .6858), c(.2721, 1.0000, .4991), c(.6858, .4991, 1....
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Question 1 a) [1 point] What are the number of parameters to be estimated of each type (path coefficients/direct effects, variances, covariances)? Direct Effects: 8 Variances: 6 Covariances: 1 b) [1 point] What is the model degree of freedom? Data Observed p= 6*(6+1)/2 = 21 Estimated Parameters q = 8 + 6 + 1 = 15 Model degree of freedom 21-15 =...
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Hw 7 Will Henderson 3/30/2022 Data In this data, four factors (Positive affect, Self-regard, Social connectedness, and Meaning in life) were measured with a 6-point Likert scale. A paper survey with 16 questions was distributed with four items under each construct. Table 1 presents the descriptive statistics (number of observations, means, and s...
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HW8 Will Henderson 2022-11-23 Problem Description [7 points + 2 bonus points] Using the data from Roth et al., 1989 (see Table 4.2), do the following: Import Data Table 1. Corelation Matrix of the Variables exercise hardiness fitness stress illness exercise 1.00 -0.03 0.39 -0.05 -0.08 hardiness -0.03 1.00 0.07 -0.23 -0.16 fitness 0.39 0.07...
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Final Project
Final Project Will Henderson 3/30/2022 Introduction (~1 points) Introduce the research problem briefly (literature review is not required) The research question proposed is to understand the main factors influencing the perceived usefulness of Wikipedia within teaching. Wikipedia can become a great learning tool within the classroom and provides...
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Module 6
Module 6 First Step: Import the data. dat <- read.csv("uav.csv") Create Factors and Labels dat$Training <- factor(dat$Training, labels = c("Standard Training", "New Training")) dat Check Summary & Labelss summary(dat) ## Training Maneuver Sensor Knowledge ## Standard Training:6 Min. :14.00 Min. :2...
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Correlation & Simple Linear Regression Assignment
library(car) ## Loading required package: carData Question 2: cor(Duncan$prestige, Duncan$income) ## [1] 0.8378014 cor(Duncan$prestige, Duncan$education) ## [1] 0.8519156 cor(Duncan$income, Duncan$education) ## [1] 0.7245124 Prestige & Income = .8378014 Prestige & Education = .8519156 Income & Education = .7245124 prestige.predictor <- lm(presti...
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