# We Helped With This R Language Programming Assignment: Have A Similar One?

SOLVED Category Programming R | R Studio Graduate Solved Help With Statistics Assignment

## Short Assignment Requirements

Task 1: Tutorial â€¢ Reading chapter â€œPrincipal components and factor analysis.â€ Task 2: Perform principal component analysis â€¢ Input the raw data matrix to fa.parallel() function to determine the number of components to extract â€¢ Input the raw data matrix to principal() function to extract the components. If raw data is input, the correlation matrix is automatically calculated by principal() function. â€¢ Rotate the components â€¢ Compute component scores â€¢ Graph an orthogonal solution using factor.plot() â€¢ Interpret the results Task 3: Perform factor analysis â€¢ Input the raw data matrix to fa.parallel() function to determine the number of components to extract â€¢ Input the raw data matrix to fa() function to extract the components. If raw data is input, the correlation matrix is automatically calculated by fa() function. â€¢ Rotate the factors â€¢ Compute factor scores â€¢ Graph an orthogonal solution using factor.plot() â€¢ Graph an oblique solutions using fa.diagram() â€¢ Interpret the results Task 4: Perform multidimensional scaling â€¢ Input the raw data matrix to fa.parallel() function to determine the number of components to extract â€¢ Input the raw data matrix to cmdscale() function to perform multidimensional scaling. cmdscale() function which is available in the base installation performs a classical multidimensional scaling. â€¢ Graph an orthogonal solution using factor.plot() â€¢ Interpret the results

## Assignment Description

Homework 2

IE 7275 Data Mining in Engineering

Reading chapter “Principal components and factor analysis.”

### Task 2: Perform principal component analysis

Input the raw data matrix to fa.parallel() function to determine the number of components to extract

Input the raw data matrix to principal() function to extract the components. If raw data is input, the correlation matrix is automatically calculated by principal() function.

Rotate the components

Compute component scores

Graph an orthogonal solution using factor.plot()

Interpret the results

### Task 3: Perform factor analysis

Input the raw data matrix to fa.parallel() function to determine the number of components to extract

Input the raw data matrix to fa() function to extract the components. If raw data is input, the correlation matrix is automatically calculated by fa() function.

Rotate the factors

Compute factor scores

Graph an orthogonal solution using factor.plot()

Graph an oblique solutions using fa.diagram()

Interpret the results

### Task 4: Perform multidimensional scaling

Input the raw data matrix to fa.parallel() function to determine the number of components to extract

Input the raw data matrix to cmdscale() function to perform multidimensional scaling. cmdscale() function which is available in the base installation performs a classical multidimensional scaling.

Graph an orthogonal solution using factor.plot()

Interpret the results

Problem 1

Perform Task 2 on US Judge Ratings.dat

Problem 2

Perform Task 2 on Glass Identification Data.xlsx

Problem 3

Problem 4

### Problem 5

Perform Task 4 on Vertebral Column Data.xlsx

Files Included in the Folder:

Homework 1.pdf

PCA and FA Tutorial.pdf

US Judge Rating.dat

Glass Identification Data.xlsx

Glass Identification Data Description.pdf

Herman23.cor

Herman74.cor

Vertebral Column Data.xlsx

Vertebral Column Description.pdf

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