# PU Finding Automobile Parking

Purpose

This assignment illustrates how you can use data analytics to create sustainable organizational success strategies while integrating its mission with societal values. You will (a) apply statistical time series modeling techniques to identify patterns, develop time-dependent demand models, and (b) practice organizing and delivering a presentation to senior decision-makers.

Scenario. The city’s administration is motivated to improve its residents’ quality of life, i.e., finding automobile parking. Unfortunately, not finding parking can be time-consuming and contribute to congestion. Some cities have initiated data-driven parking space management to reduce congestion and make traffic more fluid. You’re assisting a mid-size city’s data analyst in helping the city evaluate whether it should invest in the infrastructure to count and report the number of parking spaces available at various parking lots downtown.

Instructions. Use the Week 6 Data File (in Resources below) with the variables.

• Lot Code – The code identifies a city parking lot
• Lot Capacity – The quantifies each parking lot’s capacity
• Lot Occupancy – The current number of cars in the city parking lot
• Time Stamp – A date-time of measured occupancy
• Day – The day of the week corresponding to the Time Stamp

Presentation Preparation Steps

A. Create a New Column Occupancy Rate

1. Calculate occupancy rate as a percentage with one decimal. Use Lot Occupancy/Lot Capacity * 100.

2. Example

Given: Lot Occupancy = 61, Lot Capacity = 577

Occupancy Rate = 61/577*100 = 10.6 percent

B. Construct a Single Box and Whisker Plot

1. Use the columns Day and Occupancy Rate

2. Select all data in both the Day and Occupancy Rate columns

3. Use Insert > Insert Statistic Chart > Box and Whisker. (This will produce one chart with seven box plots)

4. Finish the chart with x- and y-axis labels.

Is the median occupancy rate approximately the same throughout the week? If not, which days have lower median occupancy rates? Conversely, which days have higher median occupancy rates? Is this what you expected?

C. Construct a Single Box and Whisker Plot

1. Use the columns Lot Code and Occupancy Rate

2. Select all data in both the Lot Code and Occupancy Rate columns

3. Use Insert > Insert Statistic Chart > Box and Whisker (you may need to segregate these columns to select the data)

4. Finish the chart with x- and y-axis labels.

Do all parking lots experience approximately equal occupancy rates? Are some parking lots more frequented than others? Is this what you expected?

D. Construct Two Scatter Plots

1. Use the columns Time Stamp (X) and Occupancy Rate (Y) (for one Lot Code)

2. Select data in both columns the Time Stamp and Occupancy Rate columns for the week 11/20/2016 –11/26/2016 (about 126 data per column)

3. Use Insert > X-Y Scatter

4. Finish each chart with x- and y-axis labels.

5. Repeat Steps 1-4 for a second Lot Code (You will have two scatter plots)

Are the occupancy rates time-dependent? If so, which times seem to experience the highest occupancy rates? Is this what you expected?

Presentation.

E. Create approximately a 10-slide Presentation. Your audience is the City Council members responsible for deciding whether the city should invest resources to set the Smart parking space app in motion.

Complete the following in your Presentation:

• Title Page and Agenda (not graded but customary for such a presentation)
• Outline the rationale and goals of the project.
• Utilize boxplots showing the occupancy rates for each day of the week. Include your interpretation of the results.
• Utilize box plots showing the occupancy rates for each parking lot. Include your interpretation of the results.
• Provide scatter plots showing the occupancy rate against the time of day of your two parking lots. Include your interpretation of the results.
• Make a recommendation about continuing with the implementation of this project.