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Figure 1: R code to generate strength of studying technique data set.seed(10) data <- data.frame(technique = rep(c("A", "B", "C"), each = 30), current_grade = runif(90, 65, 95), exam = c(runif(30, 80, 95), runif(30, 70, 95), runif(30, 70, 90)))

Figure 1: R code to generate strength of studying technique data set.seed(10) data <- data.frame(technique = rep(c("A", "B", "C"), each = 30), current_grade = runif(90, 65, 95), exam = c(runif(30, 80, 95), runif(30, 70, 95), runif(30, 70, 90)))

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
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Figure 1: R code to generate strength of studying technique data set.seed (10) data <- data.frame(technique = rep(c("A", "B", "C"), each = 30), current_grade = runif(90, 65, 95), exam = c(runif (30, 80, 95), runif(30, 70, 95), runif(30, 70, 90))) USING R CODE: Test the significance of the covariate, that is, current grade (x) and the adjusted treatment (studying technique) means at 5 % level of significance. For the test provide the null and al- ternative hypotheses, critical region (or rejection region), test statistics and your conclusions.
Transcribed Image Text:Figure 1: R code to generate strength of studying technique data set.seed (10) data <- data.frame(technique = rep(c("A", "B", "C"), each = 30), current_grade = runif(90, 65, 95), exam = c(runif (30, 80, 95), runif(30, 70, 95), runif(30, 70, 90))) USING R CODE: Test the significance of the covariate, that is, current grade (x) and the adjusted treatment (studying technique) means at 5 % level of significance. For the test provide the null and al- ternative hypotheses, critical region (or rejection region), test statistics and your conclusions.
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