DATCB/565: Data Analysis And Business Analytics
Competency 3 – Assessment
Competency 3 – Overview and Assessment Information
Competency Statement
Utilizing statistical regression and time series analysis models, you will be able to evaluate and analyze how multiple variables impact an organization. You will also be able to create forecasts and interpret data to analyze performance as it impacts strategic planning and comparative advantage for an organization.
Competency
Examine statistical patterns and trends to highlight organizational performance and support organizational strategic planning.
Learning Objective (LO)
Learning Objective 5
Use regression models to forecast.
Learning Objective 6
Construct and interpret time series models.
Competency Assessment Description
Apply statistical time series modeling techniques to identify patterns and develop time-dependent demand models.
Why It Matters
Watch the video below to learn more about this competency. CBE no longer uses the term modules; they are now called Learning Resources.
Assessment Information
This assignment illustrates how data analytics can be used to create strategies for sustainable organizational success while integrating the organization’s mission with societal values. You’ll apply statistical time series modeling techniques to identify patterns and develop time-dependent demand models. You’ll practice organizing and delivering a presentation to senior decision-makers. The PowerPoint presentation includes an audio component in addition to speaker notes.
Download and review the rubric!
Download and save the Competency 3 Assessment Rubric and use it as a guide when completing your assessment.
Assessment Directions
Assessment Details
Scenario:
A city’s administration isn’t driven by the goal of maximizing revenues or profits but instead looks at improving the quality of life of its residents. Many American cities are confronted with high traffic and congestion. Finding parking spaces, whether in the street or a parking lot, can be time consuming and contribute to congestion. Some cities have rolled out data-driven parking space management to reduce congestion and make traffic more fluid.
You’re a data analyst working for a mid-size city that has anticipated significant increments in population and car traffic. The city is evaluating whether it makes sense to invest in infrastructure to count and report the number of parking spaces available at the different parking lots downtown. This data would be collected and processed in real-time, feeding an app that motorists can access to find parking space availability in different parking lots throughout the city.
Part 1: Data Manipulation
Download the Parking Lot Use data set. The data set has the following columns:
- LotCode: a unique code that identifies the parking lot
- LotCapacity: a number with the respective parking lot capacity
- LotOccupancy: a number with the current number of cars in the parking lot
- TimeStamp: a day/time combination indicating the moment when occupancy was measured
- Day: the day of the week corresponding to the TimeStamp
Insert a new column, OccupancyRate, recording occupancy rate as a percentage with 1 decimal. For instance, if the current LotOccupancy is 61 and LotCapacity is 577, then the OccupancyRate would be reported as 10.6 (or 10.6%).
Using the OccupancyRate and Day columns, construct box plots for each day of the week. You can use Insert > Insert Statistic Chart >Box and Whisker for this purpose. Is the median occupancy rate approximately the same throughout the week? If not, which days have lower median occupancy rates? Which days have higher median occupancy rates? Is this what you expected?
Using the OccupancyRate and LotCode columns, construct box plots for each parking lot. You can use Insert > Insert Statistic Chart >Box and Whisker for this purpose. Do all parking lots experience approximately equal occupancy rates? Are some parking lots more frequented than others? Is this what you expected?
Select any 2 parking lots. For each of them, prepare a scatter plot showing occupancy rate against TimeStamp for the week 11/20/2016 – 11/26/2016. Are occupancy rates time dependent? If so, which times seem to experience the highest occupancy rates? Is this what you expected?
Continue to Part 2: Presentation.
Part 2: Presentation
Prepare a 12- to 16-slide presentation with detailed speaker notes and audio, graphs, and tables.
Your audience is the city council, which is responsible for deciding whether the city invests resources to set in motion the smart parking space app.
Complete the following in your presentation:
- Outline the rationale and goals of the project
- Utilize box plots showing the occupancy rates for each day of the week. Include your interpretation of results.
- Utilize box plots showing the occupancy rates for each parking lot. Include your interpretation of results
- Provide scatter plots showing occupancy rate against the time of day of your selected 2 parking lots. Include your interpretation of results
- Make a recommendation about continuing with the implementation of this project.
Include speaker notes that convey the details you would give if you were presenting. You will record your speaker notes.
Ensure that the slides contain only essential information and as little text as possible.
Resources
Note: Please ensure that when citing or referencing an outside resource or external entity that proper attribution is made to that source. An example of a method for citing outside resources can be found in the APA 7th edition manual. Although you will not be graded on your ability to format citations in a specific format, it is expected that all learners submit work that is representative of their own original thoughts and work, and clearly attribute when referencing outside sources or entities when completing competency assessments.
Assignment / Performance Criteria Mastery 100%
1. 1. Rationale and goals (weight 20%) Thoroughly outlined the rationale and goals of the project
2. Box plots: occupancy rate/day of week (weight 20%) Accurately utilized and interpreted box plots showing the occupancy rates for each day of the week
3. Box plots: parking lot occupancy rates (weight 20%) Accurately utilized and interpreted box plots showing the occupancy rates for each lot
4. Scatter plots with interpretation (weight 20%) Thoroughly interpreted scatter plots showing occupancy rate against time of day of selected four parking lots
5. Recommendation (weight 20%) Made a thorough recommendation about continuing with the implementation of this project
Additional Note:
FOLLOW Assignment / Performance Criteria Mastery 100%
This needs to pass ZERO GPT and plagiarism checks.
Need, scholarly references and intext citations.
Excel needed, PowerPoint needed, word needed for speaker notes, , now there is a section for audio notes, use bulletin points for slides, take same bulletin points in slides, make it headings in speaker notes and then in brackets type what can be recorded in the audio)
Example
Slide Bulletin
· Dell as a Powe Hub
Speaker Notes
- Dell as a Power Hub: Dell serves as a central engine for modern enterprise, integrating high-performance hardware with AI-driven software solutions. By streamlining complex workflows into a unified ecosystem, it empowers businesses to scale efficiently while maintaining robust security. This centralized approach transforms standard infrastructure into a dynamic hub for continuous innovation.
([Audio]: “Think of Dell not just as a hardware provider, but as the central power hub of your entire operation. We’re going to look at how integrating these systems creates a seamless flow of data and energy across your business.”)
Thank you.