IS3310 Troy Inflation Consumer Prices for United States Data Analysis

User Generated

zrat619569523

Business Finance

IS3310

Troy University

Description

1. We have obtained a dataset for evaluation from ____<Provide link>________. Describe what the data is about (eg the cars dataset is about cars that are for sale). The dataset was collected by ___<credit organization and indicate how the data was collected>_______. It contains ______ records and _______ attributes. The attributes include <list the key attributes>. The following is our findings of the appropriateness of using this data.

2. In this paragraph discuss any extra steps you needed take before uploading the data. You should then discuss the results of your initial exploration. You should reference relevant statistics such as missing data and the ranges of numeric data (you should reference the summary table). Include, reference and discuss at least two figures, either a boxplot (distribution and outliers), histogram (frequency and distribution), or a scatter plot (correlation). Refer to DAX 2 if you need help in creating and including these figures in your memo. (REMEMBER----- If you are unable to run the summary statistics in SAS, then you will not be able to use this data.)

3. In this paragraph make a recommendation to use this data or not. If it can’t be used, then you should discuss why. If you feel it is an adequate dataset then you should discuss an interesting question that you could explore from the data. Would the dataset need to be filtered in some way?

Below the text you should provide the summary table and at least two figures.

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2019/9/8 Data Analytics Exercise 3 Fall 2019 Data Analytics Exercise 3 Fall 2019 Submit Assignment Due Sep 15 by 11:59pm Points 100 Submitting a file upload File Types pdf Download and use the "DAX3 Instructions" attached below, and download and edit the"Business Memo Template DAX 3.docx" file per the instructions. Once you have completed editing the file, save it, and then save it as a PDF file to upload to this assignment. If you have already identified your IRP dataset, you may use it for this assignment. Deliverable DAX3 Report Example (Fall 2019) (002).docx Attachments DAX3 Instructions-1.pdf DAX 3 Fall 2019 https://troy.instructure.com/courses/51397/assignments/726677?module_item_id=2578538 1/3 2019/9/8 Data Analytics Exercise 3 Fall 2019 Criteria Business Memo Submitted on time. Memo Headings Correct Date, To, From, and relevant subject lines are all correct. Imported Dataset Description Paragraph 1. Description, references, data preparation steps Ratings 10.0 pts Full Marks 0.0 pts No Marks 10.0 pts Full Marks 8.0 pts Mostly Correct 15.0 pts Full Marks 12.0 pts Mostly Complete Imported Data Summary Table Figures 1 and 2 Two useful graphics, captions, properly formatted. Boxplot, histogram, or Scatter Plot. Data Exploration Briefly discussed what the figures and table represent. Discussing important factors such as missing data, ranges of numeric data, and frequency of categorical data. Recommendation Recomend whether the data is appropriate for use. If it is inappropriate then discuss why. If useful then discuss an important question that you can address. 5.0 pts Partially correct. Some inaccurate information 8.0 pts Mostly Incomplete Few missing components or errors. Table 1 Pts Missing major elements or contains numerous errors 10.0 pts Full Marks 6.0 pts Table provided 20.0 pts Full Marks 15.0 pts Two figures 10.0 pts One figure 5.0 pts One figure Two figures but not properly formatted One properly formatted figure One figure poorly formatted 25.0 pts Full Marks 15.0 pts Some ommisions or mistakes Table provided but not correct or properly formatted 10.0 pts Missing components or numerous mistakes 10.0 pts Full Marks 6.0 pts Missing components Clear recommendation and interesting question, or an explanation why dataset should not be used. Recommendation not provide, missing the interesting question that could be asked, or an inadequate explanation on why the dataset should not be used. 10.0 pts 0.0 pts No Marks 0.0 pts No Marks 0.0 pts No Marks 0.0 pts No Marks 0.0 pts No Marks 10.0 pts 15.0 pts 10.0 pts 20.0 pts 25.0 pts 0.0 pts No Marks 10.0 pts Total Points: 100.0 https://troy.instructure.com/courses/51397/assignments/726677?module_item_id=2578538 2/3 2019/9/8 Data Analytics Exercise 3 Fall 2019 https://troy.instructure.com/courses/51397/assignments/726677?module_item_id=2578538 3/3 Today’s Date (e.g. June 28, 2018) To: Example Mrs. Rouse From: Student Name Subject: ______ Dataset 1. We have obtained a dataset for evaluation from ____________. Describe what the data is about (eg the cars dataset is about cars that are for sale). The dataset was collected by __________. It contains ______ records and _______ attributes. The attributes include . The following is our findings of the appropriateness of using this data. 2. In this paragraph discuss any extra steps you needed take before uploading the data. You should then discuss the results of your initial exploration. You should reference relevant statistics such as missing data and the ranges of numeric data (you should reference the summary table). Include, reference and discuss at least two figures, either a boxplot (distribution and outliers), histogram (frequency and distribution), or a scatter plot (correlation). Refer to DAX 2 if you need help in creating and including these figures in your memo. (REMEMBER----- If you are unable to run the summary statistics in SAS, then you will not be able to use this data.) 3. In this paragraph make a recommendation to use this data or not. If it can’t be used, then you should discuss why. If you feel it is an adequate dataset then you should discuss an interesting question that you could explore from the data. Would the dataset need to be filtered in some way? Below the text you should provide the summary table and at least two figures.
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September 10, 2018
To: Instructor
From: Student Name
Subject: Inflation, consumer prices for the United States

We have obtained a dataset for evaluation from
https://fred.stlouisfe...


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