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Replicate the textbook's code shown in Chapter 2 (2.3 Lab: Introduction to R). 2.3 Lab: Introduction to R In this lab, we will introduce some simple R commands to understand how R works. 2.3.1 Basic Commands 2.3.2 Graphics 2.3.3 Indexing Data 2.3.4 Loading Data

Applied Business Statistics – Week1 PROBLEM -1 For each of the following variables, determine whether the variable is categorical or numerical. If the variable is numerical, determine whether the variable is discrete or continuous. a. Average bill amount paid to an Internet service provider b. Mall store used most frequently for holiday shopping c. Number of cars purchased during the person's lifetime d. Day in which the person does the most holiday shopping (weekday, Saturday, Sunday) ...

Capstone Project – You can contact me from the messages section for assistance regarding this project. Description: MCIT Capstone Project Guidelines In this course, a final team project is developed and presented to demonstrate the integration of knowledge and skills acquired from all aspects of the MCIT program. Students will develop the necessary source code and Cloud infrastructure to support the implementation of the project they designed. Minimum Requirements The minimum requir...

Solver Using your own problem find an optimization solution. Maybe you want to maximize the profit of your sewing operation that makes pants and shirts. Maybe you want to find the optimum balance of stocks in your portfolio. Or, maybe you want to come up with your own example. Submit a Word document with your explanation, in 500 words or more, of how you used Solver to answer your business question. Include screenshots of your work (with the desktop slice, of course). Note: This document is...

Linear Regression Open the attached .csv file. Select Regression from the data analysis tab Weight will be our predictor variable and MPG the response variable. Select your x (predictor) and y (response) ranges accordingly. Check the labels button and and output cell. Observe the ANOVA matrix. The F-statistic will tell you whether your model is better than simply using the mean. You will want the F-statistic to be as high as possible and the significance to be as low as possible. The equati...

According to , RFM analysis is a marketing technique used to quantitatively rank and group customers based on the recency, frequency and monetary total of their recent transactions to identify the best customers and perform targeted marketing campaigns. Using your own dataset, execute an RFM analysis and explain your analysis and your findings in 500 words or more. Note: This document is for learning purposes only.

KPI analysis using process behavior/control charts and this video with an example business process behavior chart. Note that Langer uses a natural end to the time series (end of year) to allow him to create two process charts which can be compared, as well. Read the attached document showing how to create and analyze the process control chart. Using your own choice of dataset and what you have learned from the video use a KPI analysis to learn about your data set. Discuss in 500 words or more, w...

Market Basket Analysis. Using what you have learned use Market Basket Analysis to mine association rules from your own data set. Discuss in 500 words or more, what patterns in association rules reveal about your business question. Share the business question you are attempting to answer. Submit a Word document with screenshots of your Market Basket Analysis including your use of the Solver and your discussion. Always include a slice of your desktop with any screenshot. Note: This document i...

Treemaps Using what you have learned create treemaps visualizing data from your data set. Discuss, in 500 words or more, what the treemaps reveal about your business question. Share the business question you are attempting to answer. Submit a Word document with screenshots of your treemaps and your discussion. Always include a slice of your desktop with any screenshot, Please note that all code assignments must be submitted as a screenshot with a slice of your desktop showing the timestamp....

Navigation and Advertisement Reports Two of the newest features of GA 4.0 includes navigation and advertisement reports. After reading through the chapter, test out these two reports. Provide 3 screenshots per report (6 total). Below each screenshot, provide a 1-2 paragraph summary on what the image/report is highlighting. In addition, provide a sentence on how this is beneficial to web analysts. Note: This document is for learning purposes only.

Creating a dashboard Part I: Log into the Google Analytics Demo Account () Create a dashboard. Choose a data source. Customize the report to bring forward the most relevant results. Take a screenshot for each question and provide a brief explanation of your experience completing the question. Part II: Log into the Answer the following questions by taking a screenshot and explaining what is being represented. Identify the terms driving the most organic traffic. Identify the terms lead...

Data Mining for Data Sci & Anlyc_NEC_All_7_Weeks_Solved

Study this example: Copy and paste the provided R source code into an R markdown file and make it run. Weave an explanation of the model and it's conculsions into your markdown file.

Using Chapter 5, we will experiment with association analysis.

Using Chapter 4, let's look at other ways to do classification - nearest neighbors, decisions trees, support vector machines, even neural nets.

Using Chapter 3, let's about classification. This week we will be using the zoo dataset, another common dataset among data mining classes.

Using Chapter 2, let's learn how to explore data. We will be using the Iris dataset which is commonly one of the first datasets used in data mining classes.

Edit the provided R Markdown document so that It contains your name and then knit it as HTML.

We will be using examples from the book An R Companion for Introduction to Data Mining by Michael Hahsler. Every week you will be assigned a new example from this book. The instructions for each week are identical: copy and paste the source code into R studio and run it. understand what it does, explain how the dataset is processed, generate every graph, etc. document your work in an R Markdown document.

Information_Visualization_NEC_All_7_Weeks_Solved