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The Homework Library (HL) is a database of solved homework problems derived from the endless collaborations between our tutors and students. Every item in the HL is the result of one of our tutors helping to raise a student's understanding and skills to a level sufficient to produce the final product on display in the HL, a testament to the success of the academic partnership.

HL materials are not original and are therefore made available for the sole purpose of studying and learning. **Misuse of HL materials is strictly forbidden.**

The HL was created for students who need immediate help, and in many cases you can find step-by-step explanations on how to solve a problem or examples of proper writing, including the use of citations, references, bibliographies, and formatting. If you don’t find what you are looking for within our HL database, please reach out to one of our tutors and schedule a tutoring session.

Clusters For IKEA Department Stores

$25.00

Mathematics

Statistics

Clusters

Properties

IKEA

Department Stores

K Means

R Programming

Features

Municipalities

Development

Diagrams

Mathematics

Statistics

Clusters

Properties

IKEA

Department Stores

K Means

R Programming

Features

Municipalities

Development

Diagrams

Probability & Stats Practice Questions

$15.00

Mathematics

Probability

Statistics

Car Styles

Variables

Random Samples

Clusters

Surveys

Students

Histograms

Distribution

Box Plot

Standard Deviation

Mathematics

Probability

Statistics

Car Styles

Variables

Random Samples

Clusters

Surveys

Students

Histograms

Distribution

Box Plot

Standard Deviation

Clustering Problems

$65.00

Statistics

Clustering

Baseline Models

K Means

Confusion Matrix

Logistic Regression

Classification

Accuracy

Percentage

Train Data

Observations

Classifiers

Statistics

Clustering

Baseline Models

K Means

Confusion Matrix

Logistic Regression

Classification

Accuracy

Percentage

Train Data

Observations

Classifiers

Statistics Questions

$60.00

Mathematics

Statistics

R Programming

Annual Spending

Variables

Attributes

Clustering

Data Sets

Customers

Spending Habits

Distributors

Mathematics

Statistics

R Programming

Annual Spending

Variables

Attributes

Clustering

Data Sets

Customers

Spending Habits

Distributors

Clustering Problems in Java

$60.00

Computer Science

Java Programming

Algorithms

Clustering

K Means

Real Factors

Voronoi Diagram

Toy Problem

Brute Force

Centroids

Iterations

Statements

Variables

Computer Science

Java Programming

Algorithms

Clustering

K Means

Real Factors

Voronoi Diagram

Toy Problem

Brute Force

Centroids

Iterations

Statements

Variables

K Means Clustering in Java

$65.00

Computer Science

Java Programming

K Means Clustering

Points

Greedy Implementation

Algorithms

Data Sets

Distances

Performances

Centroid

Subsets

Pseudocodes

Minimization

Computer Science

Java Programming

K Means Clustering

Points

Greedy Implementation

Algorithms

Data Sets

Distances

Performances

Centroid

Subsets

Pseudocodes

Minimization

Engineering Questions

$40.00

Engineering

Technology

Mathematics

Clustes

Interference

Pros

Cons

Cell Phones

Expenses

Data Rates

5G Network

Loss Exponents

Power

Layers

Mobile Terminals

Walkie-Talkie Systems

Engineering

Technology

Mathematics

Clustes

Interference

Pros

Cons

Cell Phones

Expenses

Data Rates

5G Network

Loss Exponents

Power

Layers

Mobile Terminals

Walkie-Talkie Systems

Exploratory Factor and Cluster Analysis

$100.00

Applied Statistics

Factors

Clusters

Data Sets

Fitting

Likert Scale

Descriptive Statistics

Rotation Method

Variables

Data Representation

Matrices

Factors

Square Sums

Summary Scales

Variance

Plots

Applied Statistics

Factors

Clusters

Data Sets

Fitting

Likert Scale

Descriptive Statistics

Rotation Method

Variables

Data Representation

Matrices

Factors

Square Sums

Summary Scales

Variance

Plots

Data Science Questions: Admission to Graduate School

$75.00

Mathematics

Statistics

Computer Science

Data Science

R-Programming

Logistic Regression

Clustering

K-Means

Transformations

Attributes

Trained Models

Matrices

Accuracy

Cross Validation

Applicants

Dirty Data

Visualization

Variables

Mathematics

Statistics

Computer Science

Data Science

R-Programming

Logistic Regression

Clustering

K-Means

Transformations

Attributes

Trained Models

Matrices

Accuracy

Cross Validation

Applicants

Dirty Data

Visualization

Variables

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