NAME: STEELMANUF$\_$CLIENTS$\_$SV$.$xlsx

DESCRIPTION: This database contains client characteristics from a steel manufacturer operating in America. Initially, it was created to analyze purchasing patterns within a newly implemented web$-$based system designed to automate the entire client order$-$to$-$purchase process. The automation aimed to reduce reliance on human client service agents in the corporate call center. The database classifies the firm's clients into four categories: Browser, Selector, Quote$-$only, and Buyer $($the desired end stage for every client using the web system$).$ These classifications serve as metrics to assess the new system's effectiveness. The records in the database cover nationwide data. You can find a simplified graphic illustrating the order and purchase process within the web system:For this assignment, you will go through the dataset that has been assigned to you, and create a deliverable where you address the following points. A list of all the databases can be accessed here

$1.$ An overview of your dataset $($you can refer to the documentation provided along with the dataset$),$ to include the following:

A$.$ A table with:

I. Names of variables $($in column $1),$ their measurement type $($nominal$/$ordinal$/$scale$/$ratio$)($in column $2),$ the role of the variable $($excluded$/$predictor$/$outcome$)$

B$.$ The industry to which it belongs $($this is also indicated as part of the documentation associated with the dataset$)$

$2.$ A brief list of $2-3$ research questions that indicate the types of investigations that will be of interest to a decision$-$maker of the organization from which the dataset was obtained. Note that this list of questions may be modified by you in the future, adding more details, expanding on the initial set of questions,

$3.$ Preliminary exploratory analyses of the variables to address the following questions for each variable:

A$.$ Are there any missing values, outliers, or anomalies? Provide the evidence to inform your response.

B$.$ The rationale for assigning a particular role to the variable. If you choose to exclude a variable, explain why. If you choose to use a variable as a predictor, explain why. If you choose to use a variable as an outcome, explain why. Your explanations should tie with your research questions, and with any literature review you do of studies that look at similar datasets $($search for studies that included the same or similar sounding variables and$/$or are from the same industry$).$

Submission requirements

Submit the following files.

$1.$ Either a Python Notebook or an R Markdown file. The file should include all the code needed to perform the analyses to address the above questions. The file should also include detailed answers to each of the above questions.

$2.$ An exported$-$to$-$HTML version of your work. This should contain all the explanations, code, and appropriate output, allowing the reader to go through all your work, without having to execute your code for producing the outputs.