Category: R

This is an assignment for an Intro to Computational Statistics with R course. Please make sure to follow the instructions/guidelines provided to complete the assignment! This is very important! I I have attached the instructions for this hw assignment. Please make sure to check that all the instructions are followed and that everything that is being asked for is completed in what you give me. I posted this question a few hours ago but the tutor that was assigned to my question cancelled it because they could no longer work on it due to an emergency. However, they provided me with the work that they had done thus far, so I am hoping to find a suitable tutor to finish it (where they left off). I have attached that work that they were able to do in the zip file below. Let me know if you have any questions or if there’s something that you find confusing about the instructions that you would like me to clear up with you!

This is an assignment for an Intro to Computational Statistics with R course. Please make sure to follow the instructions/guidelines provided to complete the assignment! This is very important! I I have attached the instructions for this hw assignment. Please make sure to check that all the instructions are followed and that everything that is being asked for is completed in what you give me. I posted this question a few hours ago but the tutor that was assigned to my question cancelled it because they could no longer work on it due to an emergency. However, they provided me with the work that they had done thus far, so I am hoping to find a suitable tutor to finish it (where they left off). I have attached that work that they were able to do in the zip file below. Let me know if you have any questions or if there’s something that you find confusing about the instructions that you would like me to clear up with you!

This is an assignment for a Intro to Computational Statistics with R course. Please make sure to follow the instructions/guidelines provided to complete the assignment! This is very important! I I have attached the instructions for this hw assignment. Please make sure to check that all the instructions are followed and that everything that is being asked for is completed in what you give me. Let me know if you have any questions or if there’s something that you find confusing about the instructions that you would like me to clear up with you!

1. Drills with R on K-NN models
This problem is related to Nearest neighbors classifiers described in section 9.5 in “Modern Statistics with R” – https://modernstatisticswithr.com: Fit a kNN classification model to the wine data, using pH, alcohol, fixed.acidity, and residual.sugar as explanatory variables. Evaluate its performance using 10-fold cross-validation, using AUC to choose the best k.
To solve the problem, you’ll need to load the data and libraries with:
# Import data about white and red wines:
white <- read.csv("https://tinyurl.com/winedata1",sep = ";") red <- read.csv("https://tinyurl.com/winedata2",sep = ";") # Add a type variable: white$type <- "white" red$type <- "red" # Merge the datasets: wine <- rbind(white, red) wine$type <- factor(wine$type) install.packages('caret', dependencies = TRUE) library(caret) # to visualize results you need the following install.packages('MLeval', dependencies = TRUE) library(MLeval) For the submission: 1. Provide the commands in plain text that you used to solve the problem. Attach the figure that resulted after command: plots$roc Output after executed command: plots$optres[[1]][13,] Attach the figure that resulted after command: plots$cc 2. Dissimilarities between data objects This project demonstrates how to measure similarities between data objects. These topics described are mostly in chapter 6 Statistical Machine Learning from ‘Practical Statistics for Data Scientists’. Cover in the project the following: Find some data examples and show examples of calculatingEuclidean distance L1 distance Prove or disprove that Euclidean and L1 distance satisfyPositivity d(x,y) >= 0 for all x and y, d(x,y) == 0 only if x == y.
Symmetry d(x,y) == d(y,x) for all x and y.
Triangle Inequality d(x,z) <= d(x,y) + d(y,z) for all points x, y, and z Explain why it is not possible or why it is possible torearrange data so Euclidean distance gives the same meaning as Hamming distance show that measure d=1-cos(x,y) satisfies positivity, symmetry, and triangle Inequality Draw conclusions about what is important when choosing the distance measure for the evaluation of dissimilarities between data objects. Assignment 1 and 2 are to be done in 2 different papers in APA format

I am trying to take an R introductory quiz. A few questions require me to make simple codes to answer the questions.
example of the functions: rename, summarize(), mean(), filter, … .

Make two models using statistical tools in R for a machine learning project.
State the aim/ objective of the model.
Use tools like linear regression, multiple regression, KNN, tree based models, random Forest, cross validations and such to create those models.
Explain if it will be inference or prediction route you take to create the model.
Explain the two models created and why you choose those model.
Also explain the findings and elaborate on the results that is achieved.
Conclude the overall project with if the objective is met or not and such
Using R to do this project and also includes graphs for the model that is created

identify a research or business problem using the ,mentioned dataset that required data analysis.
Will you use prediction or inference? Select at least two statistical methods (linear regression, logistic regression, decision tree, randomForest, KNN and such) to create the models. Two model needed.
Present preliminary analytics results and explain about the methods used and why.
Filter the year for >2012.

This is an assignment for a Intro to Computational Statistics with R course. Please make sure to follow the instructions/guidelines provided to complete the assignment! This is very important! I I have attached the instructions for this hw assignment. I mainly need help writing the functions in an R file that would work to generate something like what is shown in the second pdf file that I attached. The second pdf file that I attached is how the output should look like, so make sure that what you have looks something like that. Another priority is solving Question 2.3 and writing R code for Question 2.1. Please make sure to check that all the instructions are followed and that everything that is being asked for is completed in what you give me. Let me know if you have any questions or if there’s something that you find confusing about the instructions that you would like me to clear up with you!

As usual please share the answers with me in word doc and please include the screenshot of your RStudio. Thank you so much in advance!

For the Houses data at Index of Datasets consider Y = selling price, x1 = tax bill (in dollars), and x2 = whether the house is new:
1. Form the scatter plot of y and x1. Then answer, does the normal GLM structure of constant variability in y seem appropriate? If not, how does it seem to be violated?
Using the identity link function, fit the
A. Normal GLM
B. Gamma GLM
C. For each model, interpret the effect of x2.
2. For each model, describe how the estimated variability in selling prices varies as the mean selling price varies from 100 thousand to 500 thousand dollars.
3. Which model is preferred according to AIC?
Datasets needed are listed at Index of Datasets
Useful functions in R to solve problems in this assignment: read.table, head, glm, summary
APA format and attach the results in word doc