Publications by saisree
stat lab 7
statistical learning lab 7 8a set.seed(123) # Set seed for reproducibility n <- 100 X <- rnorm(n) epsilon <- rnorm(n) 8b beta_0 <- 1 beta_1 <- 2 beta_2 <- 3 beta_3 <- -1 beta_4 <- 5 Y <- beta_0 + beta_1*X + beta_2*X^2 + beta_3*X^3 + beta_4*X^4 + epsilon data <- data.frame(Y, X) for (i in 2:10) { data[[paste0("X", i)]] <- X^i } 8c...
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stat lab 6
Statistical learning- lab 6 question 5 5a library(ISLR) set.seed(1) # Set a random seed for reproducibility # Part (a): Fit a logistic regression model using income and balance to predict default model1 <- glm(default ~ income + balance, data = Default, family = binomial) summary(model1) ## ## Call: ## glm(formula = default ~ income + ba...
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Exam1 (Take Home)
Please hand this result in on Canvas no later than 11:59pm on Wednesday, March 12! Do not work in groups! Consider the data from R package . We will use linear regression to investigate the relationship between variables in this data set and estimated performance (variable ). Do not use published performance as a predictor of performance in th...
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stat lab 5
question 13 13a library(ISLR2) library(MASS) ## ## Attaching package: 'MASS' ## The following object is masked from 'package:ISLR2': ## ## Boston library(class) library(e1071) # Load the dataset data(Weekly) # Numerical and graphical summaries summary(Weekly) ## Year Lag1 Lag2 Lag3 ...
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stats lab 1
QUESTION 9 install.packages("ISLR2", repos = "https://cloud.r-project.org/") ## Installing package into 'C:/Users/saisr/AppData/Local/R/win-library/4.4' ## (as 'lib' is unspecified) ## package 'ISLR2' successfully unpacked and MD5 sums checked ## ## The downloaded binary packages are in ## C:\Users\saisr\AppData\Local\Temp\RtmpCkAdgm\download...
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Final project- obesity
My final project focuses on finding the distinctions between those who are obese and those who are not. The project will be split into three primary parts: lifestyle habits, family history, and physical activity. The obesity dataset will be used in this research because it contains a variety of characteristics, such as family history, physical ...
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Final Project - Obesity
My final project focuses on finding the distinctions between those who are obese and those who are not. The project will be split into three primary parts: lifestyle habits, family history, and physical activity. The obesity dataset will be used in this research because it contains a variety of characteristics, such as family history, physical ...
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Week 13 | Data Dive — Critiquing Models and Analyses
I did this assignment based on week 6 lab notes. # Load necessary libraries library(ggplot2) library(dplyr) ## ## Attaching package: 'dplyr' ## The following objects are masked from 'package:stats': ## ## filter, lag ## The following objects are masked from 'package:base': ## ## intersect, setdiff, setequal, union # Load the datas...
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Week 12 | Data Dive — Time-based Data
library(tidyverse) ## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ── ## ✔ dplyr 1.1.4 ✔ readr 2.1.5 ## ✔ forcats 1.0.0 ✔ stringr 1.5.1 ## ✔ ggplot2 3.5.1 ✔ tibble 3.2.1 ## ✔ lubridate 1.9.3 ✔ tidyr 1.3.1...
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Week 11 | Data Dive — GLMs (Part 2)
# Load necessary libraries library(tidyverse) ## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ── ## ✔ dplyr 1.1.4 ✔ readr 2.1.5 ## ✔ forcats 1.0.0 ✔ stringr 1.5.1 ## ✔ ggplot2 3.5.1 ✔ tibble 3.2.1 ## ✔ lubridate 1...
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