Reference no: EM131428907
Project Overview -
This project is a continuation of Project 2.1 regarding trying to find the best city to expand for Pawdacity's newest pet store.
Scenario
Pawdacity is a leading pet store chain in Wyoming with 13 stores throughout the state. This year, Pawdacity would like to expand and open a 14th store. Your manager has asked you to perform an analysis to recommend the city for Pawdacity's newest store, based on predicted yearly sales.
How Do I Complete this Project?
This project uses skills learned throughout the "Multivariable Linear Regression" lesson. To complete this project:
- Go through the course
- Apply the skills learned in the course to solve the business problem given in the project details section.
- Use our guidelines and rubric to help build your project.
- When you're ready, submit it to us for review using the submission template found in the supporting materials section.
Skills Required
In order to complete this project, you must be able to:
- Choose appropriate predictor variables
- Analyze for correlations between predictor variables
- Build a linear model
The Business Problem
Pawdacity is a leading pet store chain in Wyoming with 13 stores throughout the state. This year, Pawdacity would like to expand and open a 14th store. Your manager has asked you to perform an analysis to recommend the city for Pawdacity's newest store, based on predicted yearly sales.
In the first part, you've already cleaned up the dataset and dealt with outliers.
In this project, you will take this dataset that you cleaned up and use this dataset to train a linear regression model in order to predict sales
Here are the criterias given to you in choosing the right city:
1. The new store should be located in a new city. That means there should be no existing stores in the new city.
2. The total sales for the entire competition in the new city should be less than $500,000
3. The new city where you want to build your new store must have a population over 4,000 people (based upon the 2014 US Census estimate).
4. The predicted yearly sales must be over $200,000.
5. The city chosen has the highest predicted sales from the predicted set.
Steps to Success
Step 1: Build a Linear Regression Model
Analyze the dataset you created in Project 2.1 and look at the distribution of your data. You can create histograms to look at each of your continuous and categorical data to determine the nature of the data you're working with.
Important: Make sure you have dealt with outliers and removed one city from your training set. You should have 10 rows of data before you begin modeling the dataset.
Build a linear regression model to help you predict total sales.
Step 2: Perform the Analysis
Use your regression model to calculate predicted sales for all of the cities and use the criteria given to you to make a recommendation.
Attachment:- Assignment Files.rar
|
What subgroup size is analyst 1 using
: What subgroup size is Analyst 2 using? (c) Which analyst is making the most appropriate chart? Why?
|
|
What are the most interesting points you noticed
: What are the most interesting points you noticed from your comparative analysis of your two sources and how might these points be helpful to your target audience (an academic audience)?
|
|
Which of the Theory -X or Y do you most align with
: Which of the Theory -X or Y do you most align with ? How does that affect your behavior as a manager ? Based upon what you know about the pros and cons of both perspectives, what one thing can you do to make you more effective manager?
|
|
What might happen if in fact y is inversely related to x
: In the context of problem 1, suppose that no one is really sure whether Y is affected by changes in X and, if it is, whether the relationship is "direct" or "inverse".
|
|
Analyze the dataset you created in project
: Build a Linear Regression Model - Analyze the dataset you created in Project 2.1 and look at the distribution of your data. You can create histograms to look at each of your continuous and categorical data to determine the nature of the data you'r..
|
|
What kind of images does the novel use
: ENGL 157W What kind of images does the novel use? Why? Analyze specific images to lay out their role in generating a social critique of the establishment or the continuing racial oppression.
|
|
What is the all ok arl of the monitoring scheme
: An upward shift in the process mean of at least 1 unit occurs, while the process standard deviation variation does not change. At worst, how many hours on average will pass before this change produces a subgroup average outside the control limits?
|
|
Business and organization that had constraints
: Identify and business/organization that had constraints. What are the constraints? What were the source of the constraints? How did the business/organization manage the constraints?
|
|
Explain difference between direct retailing-direct marketing
: Explain the difference between direct retailing and direct marketing. Then, provide two examples of companies that sell using direct retailing and two examples of companies that sell using direct marketing. Where is there overlap among these three se..
|