• Home

## Content

1. Purpose
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.

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.

Instructions: Work with the provided Excel database. This database 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 one 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 one, prepare a scatter plot showing the 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?
• Presentation:
Create a 10- to 12-slide presentation with speaker notes and audio. Your audience is the City Council members who are responsible for deciding whether the city invests in 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 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 occupancy rate against the time of day of your selected four parking lots. Include your interpretation of the results.
• Make a recommendation about continuing with the implementation of this project.

## Smart Parking Space App Presentation

DAT/565 v3

Data for Time Series Modeling Exercise Questions Requiring MegaStat

DAT/565 v3

Page 2 of 2

# Data for Time Series Modeling Exercise Questions Requiring MegaStat

Use the following data for Wk 6 time series modeling exercise questions that require MegaStat.

Time Series Modeling Exercise 14-30, Connect Question 7

See output and graph MegaStat:

 Qtr1 Index Qtr2 Index Qtr3 Index Qtr4 Index 0.800 0.979 0.901 1.320

Time Series Modeling Exercise 14-32, Connect Question 8

Columns 2-4 contain calculation of seasonal indexes. From MegaStat:

 1 2 3 4 1005 – – 1.045 0.957 1006 0.890 1.084 1.053 0.927 1007 0.910 1.099 1.043 0.952 1008 0.928 1.129 1.054 0.909 1009 0.932 1.074 1.032 0.952 1010 0.942 1.032 – – mean 0.920 1.083 1.045 0.940 adjusted 0.923 1.087 1.048 0.942

Time Series Modeling Exercise 14-7, Connect Question 16

From MegaStat:

 Error a = .10 a = .20 a = .30 Mean Squared Error 0.039 0.028 0.021 Mean Absolute Percent Error 3.8% 3.1% 2.7% Percent Positive Errors 42.3% 46.2% 51.9% Forecast for Period 53 4.3 4.37 4.43

Data courtesy of McGraw-Hill Education

## ParkingLotUtilization

LotCode LotCapacity LotOccupancy TimeStamp Day
Lot01 863 174 11/20/16 8:01 Sunday
Lot01 863 179 11/20/16 8:27 Sunday
Lot01 863 189 11/20/16 9:01 Sunday
Lot01 863 197 11/20/16 9:27 Sunday
Lot01 863 226 11/20/16 10:01 Sunday
Lot01 863 247 11/20/16 10:27 Sunday
Lot01 863 331 11/20/16 11:01 Sunday
Lot01 863 400 11/20/16 11:27 Sunday
Lot01 863 469 11/20/16 12:01 Sunday
Lot01 863 510 11/20/16 12:34 Sunday
Lot01 863 594 11/20/16 13:07 Sunday
Lot01 863 618 11/20/16 13:27 Sunday
Lot01 863 637 11/20/16 14:01 Sunday
Lot01 863 655 11/20/16 14:27 Sunday
Lot01 863 634 11/20/16 15:01 Sunday
Lot01 863 597 11/20/16 15:27 Sunday
Lot01 863 533 11/20/16 16:01 Sunday
Lot01 863 476 11/20/16 16:31 Sunday
Lot01 863 363 11/21/16 8:04 Monday
Lot01 863 453 11/21/16 8:31 Monday
Lot01 863 569 11/21/16 9:04 Monday
Lot01 863 681 11/21/16 9:31 Monday
Lot01 863 787 11/21/16 10:04 Monday
Lot01 863 857 11/21/16 10:31 Monday
Lot01 863 862 11/21/16 11:04 Monday
Lot01 863 857 11/21/16 11:30 Monday
Lot01 863 860 11/21/16 11:57 Monday
Lot01 863 848 11/21/16 12:31 Monday
Lot01 863 852 11/21/16 12:57 Monday
Lot01 863 836 11/21/16 13:31 Monday
Lot01 863 823 11/21/16 14:04 Monday
Lot01 863 804 11/21/16 14:31 Monday
Lot01 863 769 11/21/16 14:57 Monday
Lot01 863 713 11/21/16 15:31 Monday
Lot01 863 669 11/21/16 15:57 Monday
Lot01 863 593 11/21/16 16:31 Monday
Lot01 863 321 11/22/16 7:57 Tuesday
Lot01 863 417 11/22/16 8:31 Tuesday
Lot01 863 526 11/22/16 9:04 Tuesday
Lot01 863 616 11/22/16 9:31 Tuesday
Lot01 863 746 11/22/16 10:04 Tuesday
Lot01 863 809 11/22/16 10:31 Tuesday
Lot01 863 825 11/22/16 11:04 Tuesday
Lot01 863 835 11/22/16 11:31 Tuesday
Lot01 863 837 11/22/16 12:04 Tuesday
Lot01 863 837 11/22/16 12:31 Tuesday
Lot01 863 840 11/22/16 12:57 Tuesday
Lot01 863 836 11/22/16 13:31 Tuesday
Lot01 863 822 11/22/16 13:57 Tuesday
Lot01 863 800 11/22/16 14:31 Tuesday
Lot01 863 782 11/22/16 14:57 Tuesday
Lot01 863 733 11/22/16 15:31 Tuesday
Lot01 863 681 11/22/16 15:57 Tuesday
Lot01 863 606 11/22/16 16:30 Tuesday
Lot01 863 335 11/23/16 8:04 Wednesday
Lot01 863 423 11/23/16 8:30 Wednesday
Lot01 863 533 11/23/16 8:57 Wednesday
Lot01 863 646 11/23/16 9:31 Wednesday
Lot01 863 758 11/23/16 10:04 Wednesday
Lot01 863 816 11/23/16 10:31 Wednesday
Lot01 863 836 11/23/16 11:04 Wednesday
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Lot01 863 838 11/23/16 13:04 Wednesday
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Lot01 863 820 11/23/16 13:57 Wednesday
Lot01 863 801 11/23/16 14:30 Wednesday
Lot01 863 775 11/23/16 15:04 Wednesday
Lot01 863 748 11/23/16 15:31 Wednesday
Lot01 863 693 11/23/16 16:04 Wednesday
Lot01 863 644 11/23/16 16:30 Wednesday
Lot01 863 347 11/24/16 8:00 Thursday
Lot01 863 435 11/24/16 8:27 Thursday
Lot01 863 547 11/24/16 9:00 Thursday
Lot01 863 682 11/24/16 9:34 Thursday
Lot01 863 748 11/24/16 10:01 Thursday
Lot01 863 797 11/24/16 10:27 Thursday
Lot01 863 833 11/24/16 11:00 Thursday
Lot01 863 845 11/24/16 11:27 Thursday
Lot01 863 847 11/24/16 12:00 Thursday
Lot01 863 839 11/24/16 12:30 Thursday
Lot01 863 846 11/24/16 13:04 Thursday
Lot01 863 836 11/24/16 13:30 Thursday
Lot01 863 829 11/24/16 13:57 Thursday
Lot01 863 792 11/24/16 14:30 Thursday
Lot01 863 778 11/24/16 14:57 Thursday
Lot01 863 736 11/24/16 15:31 Thursday
Lot01 863 711 11/24/16 15:57 Thursday
Lot01 863 644 11/24/16 16:31 Thursday
Lot01 863 337 11/25/16 8:00 Friday
Lot01 863 337 11/25/16 8:00 Friday
Lot01 863 529 11/25/16 9:00 Friday
Lot01 863 614 11/25/16 9:27 Friday
Lot01 863 709 11/25/16 10:00 Friday
Lot01 863 757 11/25/16 10:27 Friday
Lot01 863 781 11/25/16 11:00 Friday
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Lot01 863 797 11/25/16 12:34 Friday
Lot01 863 772 11/25/16 13:00 Friday
Lot01 863 780 11/25/16 13:27 Friday
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Lot01 863 738 11/25/16 14:34 Friday
Lot01 863 710 11/25/16 15:00 Friday
Lot01 863 683 11/25/16 15:27 Friday
Lot01 863 634 11/25/16 16:00 Friday
Lot01 863 570 11/25/16 16:27 Friday
Lot01 863 226 11/26/16 8:01 Saturday
Lot01 863 235 11/26/16 8:28 Saturday
Lot01 863 272 11/26/16 9:01 Saturday
Lot01 863 326 11/26/16 9:35 Saturday
Lot01 863 388 11/26/16 10:01 Saturday
Lot01 863 454 11/26/16 10:35 Saturday
Lot01 863 513 11/26/16 11:01 Saturday
Lot01 863 546 11/26/16 11:28 Saturday
Lot01 863 614 11/26/16 12:01 Saturday
Lot01 863 661 11/26/16 12:28 Saturday
Lot01 863 715 11/26/16 13:01 Saturday
Lot01 863 742 11/26/16 13:28 Saturday
Lot01 863 756 11/26/16 14:01 Saturday
Lot01 863 777 11/26/16 14:41 Saturday
Lot01 863 782 11/26/16 15:01 Saturday
Lot01 863 777 11/26/16 15:28 Saturday
Lot01 863 739 11/26/16 16:01 Saturday
Lot01 863 723 11/26/16 16:28 Saturday
Lot01 863 253 11/27/16 8:02 Sunday
Lot01 863 260 11/27/16 8:32 Sunday
Lot01 863 264 11/27/16 9:02 Sunday
Lot01 863 278 11/27/16 9:32 Sunday
Lot01 863 305 11/27/16 10:01 Sunday
Lot01 863 359 11/27/16 10:32 Sunday
Lot01 863 453 11/27/16 11:01 Sunday
Lot01 863 558 11/27/16 11:31 Sunday
Lot01 863 624 11/27/16 12:01 Sunday
Lot01 863 700 11/27/16 12:32 Sunday
Lot01 863 758 11/27/16 13:08 Sunday
Lot01 863 785 11/27/16 13:32 Sunday
Lot01 863 790 11/27/16 14:02 Sunday
Lot01 863 776 11/27/16 14:31 Sunday
Lot01 863 760 11/27/16 15:01 Sunday
Lot01 863 715 11/27/16 15:32 Sunday
Lot01 863 670 11/27/16 16:01 Sunday
Lot01 863 603 11/27/16 16:32 Sunday
Lot01 863 389 11/28/16 8:01 Monday
Lot01 863 480 11/28/16 8:32 Monday
Lot01 863 567 11/28/16 9:02 Monday
Lot01 863 650 11/28/16 9:28 Monday
Lot01 863 772 11/28/16 10:01 Monday
Lot01 863 846 11/28/16 10:32 Monday
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Lot01 863 860 11/28/16 11:32 Monday
Lot01 863 858 11/28/16 12:01 Monday
Lot01 863 849 11/28/16 12:28 Monday
Lot01 863 844 11/28/16 13:02 Monday
Lot01 863 820 11/28/16 13:31 Monday
Lot01 863 821 11/28/16 14:02 Monday
Lot01 863 800 11/28/16 14:32 Monday
Lot01 863 777 11/28/16 15:02 Monday
Lot01 863 718 11/28/16 15:41 Monday
Lot01 863 658 11/28/16 16:02 Monday
Lot01 863 608 11/28/16 16:28 Monday
Lot01 863 326 11/29/16 7:55 Tuesday
Lot01 863 400 11/29/16 8:28 Tuesday
Lot01 863 513 11/29/16 9:02 Tuesday
Lot01 863 618 11/29/16 9:28 Tuesday
Lot01 863 766 11/29/16 10:01 Tuesday
Lot01 863 851 11/29/16 10:28 Tuesday
Lot01 863 849 11/29/16 11:01 Tuesday
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Lot01 863 852 11/29/16 11:55 Tuesday
Lot01 863 850 11/29/16 12:28 Tuesday
Lot01 863 843 11/29/16 13:02 Tuesday
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Lot01 863 839 11/29/16 14:01 Tuesday
Lot01 863 834 11/29/16 14:28 Tuesday
Lot01 863 804 11/29/16 14:55 Tuesday
Lot01 863 738 11/29/16 15:28 Tuesday
Lot01 863 686 11/29/16 16:02 Tuesday
Lot01 863 610 11/29/16 16:28 Tuesday
Lot01 863 385 11/30/16 8:02 Wednesday
Lot01 863 458 11/30/16 8:28 Wednesday
Lot01 863 571 11/30/16 9:01 Wednesday
Lot01 863 682 11/30/16 9:28 Wednesday
Lot01 863 791 11/30/16 10:01 Wednesday
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Lot01 863 861 11/30/16 10:55 Wednesday
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Lot01 863 862 11/30/16 12:01 Wednesday
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Lot01 863 840 11/30/16 14:01 Wednesday
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Lot01 863 783 11/30/16 15:01 Wednesday
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Lot01 863 687 11/30/16 16:01 Wednesday
Lot01 863 626 11/30/16 16:28 Wednesday
Lot01 863 357 12/1/16 8:05 Thursday
Lot01 863 410 12/1/16 8:25 Thursday
Lot01 863 517 12/1/16 8:58 Thursday
Lot01 863 628 12/1/16 9:25 Thursday
Lot01 863 720 12/1/16 9:58 Thursday
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Lot01 863 831 12/1/16 11:32 Thursday
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Lot01 863 848 12/1/16 12:25 Thursday
Lot01 863 833 12/1/16 12:58 Thursday
Lot01 863 839 12/1/16 13:25 Thursday
Lot01 863 850 12/1/16 13:58 Thursday
Lot01 863 821 12/1/16 14:25 Thursday
Lot01 863 791 12/1/16 14:58 Thursday
Lot01 863 771 12/1/16 15:25 Thursday
Lot01 863 732 12/1/16 15:58 Thursday
Lot01 863 683 12/1/16 16:25 Thursday
Lot01 863 344 12/2/16 7:55 Friday
Lot01 863 425 12/2/16 8:28 Friday
Lot01 863 536 12/2/16 9:01 Friday
Lot01 863 608 12/2/16 9:28 Friday
Lot01 863 673 12/2/16 10:02 Friday
Lot01 863 716 12/2/16 10:28 Friday
Lot01 863 763 12/2/16 11:01 Friday
Lot01 863 769 12/2/16 11:28 Friday
Lot01 863 784 12/2/16 12:01 Friday
Lot01 863 793 12/2/16 12:28 Friday
Lot01 863 807 12/2/16 12:58 Friday
Lot01 863 795 12/2/16 13:25 Friday
Lot01 863 805 12/2/16 13:58 Friday
Lot01 863 779 12/2/16 14:25 Friday
Lot01 863 745 12/2/16 14:58 Friday
Lot01 863 675 12/2/16 15:31 Friday
Lot01 863 610 12/2/16 15:58 Friday
Lot01 863 561 12/2/16 16:32 Friday
Lot01 863 863 12/6/16 7:56 Tuesday
Lot01 863 863 12/6/16 8:29 Tuesday
Lot01 863 863 12/6/16 8:56 Tuesday
Lot01 863 863 12/6/16 9:29 Tuesday
Lot01 863 863 12/6/16 10:02 Tuesday
Lot01 863 863 12/6/16 10:29 Tuesday
Lot01 863 863 12/6/16 11:02 Tuesday
Lot01 863 863 12/6/16 11:29 Tuesday
Lot01 863 863 12/6/16 11:56 Tuesday
Lot01 863 858 12/6/16 12:29 Tuesday
Lot01 863 861 12/6/16 12:56 Tuesday
Lot01 863 853 12/6/16 13:29 Tuesday
Lot01 863 834 12/6/16 14:02 Tuesday
Lot01 863 813 12/6/16 14:29 Tuesday
Lot01 863 777 12/6/16 15:02 Tuesday
Lot01 863 722 12/6/16 15:29 Tuesday
Lot01 863 669 12/6/16 16:02 Tuesday
Lot01 863 604 12/6/16 16:29 Tuesday
Lot01 863 346 12/7/16 7:59 Wednesday
Lot01 863 407 12/7/16 8:26 Wednesday
Lot01 863 486 12/7/16 8:55 Wednesday
Lot01 863 596 12/7/16 9:26 Wednesday
Lot01 863 702 12/7/16 9:59 Wednesday
Lot01 863 787 12/7/16 10:26 Wednesday
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Lot01 863 860 12/7/16 11:25 Wednesday
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Lot01 863 826 12/7/16 14:26 Wednesday
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Lot01 863 739 12/7/16 15:32 Wednesday
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Lot01 863 643 12/7/16 16:32 Wednesday
Lot01 863 330 12/8/16 7:59 Thursday
Lot01 863 417 12/8/16 8:26 Thursday
Lot01 863 522 12/8/16 8:59 Thursday
Lot01 863 623 12/8/16 9:26 Thursday
Lot01 863 750 12/8/16 9:59 Thursday
Lot01 863 838 12/8/16 10:32 Thursday
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Lot01 863 856 12/8/16 11:32 Thursday
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Lot01 863 851 12/8/16 12:25 Thursday
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Lot01 863 861 12/8/16 13:25 Thursday
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Lot01 863 852 12/8/16 14:26 Thursday
Lot01 863 819 12/8/16 14:59 Thursday
Lot01 863 774 12/8/16 15:26 Thursday
Lot01 863 725 12/8/16 15:59 Thursday
Lot01 863 676 12/8/16 16:32 Thursday
Lot01 863 402 12/9/16 8:02 Friday
Lot01 863 471 12/9/16 8:29 Friday
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Lot01 863 626 12/9/16 16:02 Friday
Lot01 863 570 12/9/16 16:29 Friday
Lot01 863 257 12/10/16 7:59 Saturday
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Lot01 863 260 12/11/16 8:02 Sunday
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Lot01 863 369 12/12/16 8:02 Monday
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Lot01

## Smart Parking Space App Presentation

Purpose

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.

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.

Instructions: Work with the provided Excel database. This database 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 one 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 one, prepare a scatter plot showing the 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?

Presentation:

Create a 10- to 12-slide presentation with speaker notes and audio. Your audience is the City Council members who are responsible for deciding whether the city invests in 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 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 occupancy rate against the time of day of your selected four parking lots. Include your interpretation of the results.
• Make a recommendation about continuing with the implementation of this project.

## ParkingLotUtilization

LotCode LotCapacity LotOccupancy TimeStamp Day
Lot01 863 174 11/20/16 8:01 Sunday
Lot01 863 179 11/20/16 8:27 Sunday
Lot01 863 189 11/20/16 9:01 Sunday
Lot01 863 197 11/20/16 9:27 Sunday
Lot01 863 226 11/20/16 10:01 Sunday
Lot01 863 247 11/20/16 10:27 Sunday
Lot01 863 331 11/20/16 11:01 Sunday
Lot01 863 400 11/20/16 11:27 Sunday
Lot01 863 469 11/20/16 12:01 Sunday
Lot01 863 510 11/20/16 12:34 Sunday
Lot01 863 594 11/20/16 13:07 Sunday
Lot01 863 618 11/20/16 13:27 Sunday
Lot01 863 637 11/20/16 14:01 Sunday
Lot01 863 655 11/20/16 14:27 Sunday
Lot01 863 634 11/20/16 15:01 Sunday
Lot01 863 597 11/20/16 15:27 Sunday
Lot01 863 533 11/20/16 16:01 Sunday
Lot01 863 476 11/20/16 16:31 Sunday
Lot01 863 363 11/21/16 8:04 Monday
Lot01 863 453 11/21/16 8:31 Monday
Lot01 863 569 11/21/16 9:04 Monday
Lot01 863 681 11/21/16 9:31 Monday
Lot01 863 787 11/21/16 10:04 Monday
Lot01 863 857 11/21/16 10:31 Monday
Lot01 863 862 11/21/16 11:04 Monday
Lot01 863 857 11/21/16 11:30 Monday
Lot01 863 860 11/21/16 11:57 Monday
Lot01 863 848 11/21/16 12:31 Monday
Lot01 863 852 11/21/16 12:57 Monday
Lot01 863 836 11/21/16 13:31 Monday
Lot01 863 823 11/21/16 14:04 Monday
Lot01 863 804 11/21/16 14:31 Monday
Lot01 863 769 11/21/16 14:57 Monday
Lot01 863 713 11/21/16 15:31 Monday
Lot01 863 669 11/21/16 15:57 Monday
Lot01 863 593 11/21/16 16:31 Monday
Lot01 863 321 11/22/16 7:57 Tuesday
Lot01 863 417 11/22/16 8:31 Tuesday
Lot01 863 526 11/22/16 9:04 Tuesday
Lot01 863 616 11/22/16 9:31 Tuesday
Lot01 863 746 11/22/16 10:04 Tuesday
Lot01 863 809 11/22/16 10:31 Tuesday
Lot01 863 825 11/22/16 11:04 Tuesday
Lot01 863 835 11/22/16 11:31 Tuesday
Lot01 863 837 11/22/16 12:04 Tuesday
Lot01 863 837 11/22/16 12:31 Tuesday
Lot01 863 840 11/22/16 12:57 Tuesday
Lot01 863 836 11/22/16 13:31 Tuesday
Lot01 863 822 11/22/16 13:57 Tuesday
Lot01 863 800 11/22/16 14:31 Tuesday
Lot01 863 782 11/22/16 14:57 Tuesday
Lot01 863 733 11/22/16 15:31 Tuesday
Lot01 863 681 11/22/16 15:57 Tuesday
Lot01 863 606 11/22/16 16:30 Tuesday
Lot01 863 335 11/23/16 8:04 Wednesday
Lot01 863 423 11/23/16 8:30 Wednesday
Lot01 863 533 11/23/16 8:57 Wednesday
Lot01 863 646 11/23/16 9:31 Wednesday
Lot01 863 758 11/23/16 10:04 Wednesday
Lot01 863 816 11/23/16 10:31 Wednesday
Lot01 863 836 11/23/16 11:04 Wednesday
Lot01 863 835 11/23/16 11:31 Wednesday
Lot01 863 845 11/23/16 11:57 Wednesday
Lot01 863 838 11/23/16 12:31 Wednesday
Lot01 863 838 11/23/16 13:04 Wednesday
Lot01 863 837 11/23/16 13:31 Wednesday
Lot01 863 820 11/23/16 13:57 Wednesday
Lot01 863 801 11/23/16 14:30 Wednesday
Lot01 863 775 11/23/16 15:04 Wednesday
Lot01 863 748 11/23/16 15:31 Wednesday
Lot01 863 693 11/23/16 16:04 Wednesday
Lot01 863 644 11/23/16 16:30 Wednesday
Lot01 863 347 11/24/16 8:00 Thursday
Lot01 863 435 11/24/16 8:27 Thursday
Lot01 863 547 11/24/16 9:00 Thursday
Lot01 863 682 11/24/16 9:34 Thursday
Lot01 863 748 11/24/16 10:01 Thursday
Lot01 863 797 11/24/16 10:27 Thursday
Lot01 863 833 11/24/16 11:00 Thursday
Lot01 863 845 11/24/16 11:27 Thursday
Lot01 863 847 11/24/16 12:00 Thursday
Lot01 863 839 11/24/16 12:30 Thursday
Lot01 863 846 11/24/16 13:04 Thursday
Lot01 863 836 11/24/16 13:30 Thursday
Lot01 863 829 11/24/16 13:57 Thursday
Lot01 863 792 11/24/16 14:30 Thursday
Lot01 863 778 11/24/16 14:57 Thursday
Lot01 863 736 11/24/16 15:31 Thursday
Lot01 863 711 11/24/16 15:57 Thursday
Lot01 863 644 11/24/16 16:31 Thursday
Lot01 863 337 11/25/16 8:00 Friday
Lot01 863 337 11/25/16 8:00 Friday
Lot01 863 529 11/25/16 9:00 Friday
Lot01 863 614 11/25/16 9:27 Friday
Lot01 863 709 11/25/16 10:00 Friday
Lot01 863 757 11/25/16 10:27 Friday
Lot01 863 781 11/25/16 11:00 Friday
Lot01 863 796 11/25/16 11:27 Friday
Lot01 863 797 11/25/16 12:00 Friday
Lot01 863 797 11/25/16 12:34 Friday
Lot01 863 772 11/25/16 13:00 Friday
Lot01 863 780 11/25/16 13:27 Friday
Lot01 863 775 11/25/16 14:00 Friday
Lot01 863 738 11/25/16 14:34 Friday
Lot01 863 710 11/25/16 15:00 Friday
Lot01 863 683 11/25/16 15:27 Friday
Lot01 863 634 11/25/16 16:00 Friday
Lot01 863 570 11/25/16 16:27 Friday
Lot01 863 226 11/26/16 8:01 Saturday
Lot01 863 235 11/26/16 8:28 Saturday
Lot01 863 272 11/26/16 9:01 Saturday
Lot01 863 326 11/26/16 9:35 Saturday
Lot01 863 388 11/26/16 10:01 Saturday
Lot01 863 454 11/26/16 10:35 Saturday
Lot01 863 513 11/26/16 11:01 Saturday
Lot01 863 546 11/26/16 11:28 Saturday
Lot01 863 614 11/26/16 12:01 Saturday
Lot01 863 661 11/26/16 12:28 Saturday
Lot01 863 715 11/26/16 13:01 Saturday
Lot01 863 742 11/26/16 13:28 Saturday
Lot01 863 756 11/26/16 14:01 Saturday
Lot01 863 777 11/26/16 14:41 Saturday
Lot01 863 782 11/26/16 15:01 Saturday
Lot01 863 777 11/26/16 15:28 Saturday
Lot01 863 739 11/26/16 16:01 Saturday
Lot01 863 723 11/26/16 16:28 Saturday
Lot01 863 253 11/27/16 8:02 Sunday
Lot01 863 260 11/27/16 8:32 Sunday
Lot01 863 264 11/27/16 9:02 Sunday
Lot01 863 278 11/27/16 9:32 Sunday
Lot01 863 305 11/27/16 10:01 Sunday
Lot01 863 359 11/27/16 10:32 Sunday
Lot01 863 453 11/27/16 11:01 Sunday
Lot01 863 558 11/27/16 11:31 Sunday
Lot01 863 624 11/27/16 12:01 Sunday
Lot01 863 700 11/27/16 12:32 Sunday
Lot01 863 758 11/27/16 13:08 Sunday
Lot01 863 785 11/27/16 13:32 Sunday
Lot01 863 790 11/27/16 14:02 Sunday
Lot01 863 776 11/27/16 14:31 Sunday
Lot01 863 760 11/27/16 15:01 Sunday
Lot01 863 715 11/27/16 15:32 Sunday
Lot01 863 670 11/27/16 16:01 Sunday
Lot01 863 603 11/27/16 16:32 Sunday
Lot01 863 389 11/28/16 8:01 Monday
Lot01 863 480 11/28/16 8:32 Monday
Lot01 863 567 11/28/16 9:02 Monday
Lot01 863 650 11/28/16 9:28 Monday
Lot01 863 772 11/28/16 10:01 Monday
Lot01 863 846 11/28/16 10:32 Monday
Lot01 863 860 11/28/16 11:01 Monday
Lot01 863 860 11/28/16 11:32 Monday
Lot01 863 858 11/28/16 12:01 Monday
Lot01 863 849 11/28/16 12:28 Monday
Lot01 863 844 11/28/16 13:02 Monday
Lot01 863 820 11/28/16 13:31 Monday
Lot01 863 821 11/28/16 14:02 Monday
Lot01 863 800 11/28/16 14:32 Monday
Lot01 863 777 11/28/16 15:02 Monday
Lot01 863 718 11/28/16 15:41 Monday
Lot01 863 658 11/28/16 16:02 Monday
Lot01 863 608 11/28/16 16:28 Monday
Lot01 863 326 11/29/16 7:55 Tuesday
Lot01 863 400 11/29/16 8:28 Tuesday
Lot01 863 513 11/29/16 9:02 Tuesday
Lot01 863 618 11/29/16 9:28 Tuesday
Lot01 863 766 11/29/16 10:01 Tuesday
Lot01 863 851 11/29/16 10:28 Tuesday
Lot01 863 849 11/29/16 11:01 Tuesday
Lot01 863 852 11/29/16 11:28 Tuesday
Lot01 863 852 11/29/16 11:55 Tuesday
Lot01 863 850 11/29/16 12:28 Tuesday
Lot01 863 843 11/29/16 13:02 Tuesday
Lot01 863 834 11/29/16 13:28 Tuesday
Lot01 863 839 11/29/16 14:01 Tuesday
Lot01 863 834 11/29/16 14:28 Tuesday
Lot01 863 804 11/29/16 14:55 Tuesday
Lot01 863 738 11/29/16 15:28 Tuesday
Lot01 863 686 11/29/16 16:02 Tuesday
Lot01 863 610 11/29/16 16:28 Tuesday
Lot01 863 385 11/30/16 8:02 Wednesday
Lot01 863 458 11/30/16 8:28 Wednesday
Lot01 863 571 11/30/16 9:01 Wednesday
Lot01 863 682 11/30/16 9:28 Wednesday
Lot01 863 791 11/30/16 10:01 Wednesday
Lot01 863 863 11/30/16 10:28 Wednesday
Lot01 863 861 11/30/16 10:55 Wednesday
Lot01 863 857 11/30/16 11:28 Wednesday
Lot01 863 862 11/30/16 12:01 Wednesday
Lot01 863 858 11/30/16 12:28 Wednesday
Lot01 863 859 11/30/16 13:01 Wednesday
Lot01 863 856 11/30/16 13:28 Wednesday
Lot01 863 840 11/30/16 14:01 Wednesday
Lot01 863 812 11/30/16 14:28 Wednesday
Lot01 863 783 11/30/16 15:01 Wednesday
Lot01 863 746 11/30/16 15:28 Wednesday
Lot01 863 687 11/30/16 16:01 Wednesday
Lot01 863 626 11/30/16 16:28 Wednesday
Lot01 863 357 12/1/16 8:05 Thursday
Lot01 863 410 12/1/16 8:25 Thursday
Lot01 863 517 12/1/16 8:58 Thursday
Lot01 863 628 12/1/16 9:25 Thursday
Lot01 863 720 12/1/16 9:58 Thursday
Lot01 863 787 12/1/16 10:25 Thursday
Lot01 863 836 12/1/16 10:58 Thursday
Lot01 863 831 12/1/16 11:32 Thursday
Lot01 863 838 12/1/16 11:58 Thursday
Lot01 863 848 12/1/16 12:25 Thursday
Lot01 863 833 12/1/16 12:58 Thursday
Lot01 863 839 12/1/16 13:25 Thursday
Lot01 863 850 12/1/16 13:58 Thursday
Lot01 863 821 12/1/16 14:25 Thursday
Lot01 863 791 12/1/16 14:58 Thursday
Lot01 863 771 12/1/16 15:25 Thursday
Lot01 863 732 12/1/16 15:58 Thursday
Lot01 863 683 12/1/16 16:25 Thursday
Lot01 863 344 12/2/16 7:55 Friday
Lot01 863 425 12/2/16 8:28 Friday
Lot01 863 536 12/2/16 9:01 Friday
Lot01 863 608 12/2/16 9:28 Friday
Lot01 863 673 12/2/16 10:02 Friday
Lot01 863 716 12/2/16 10:28 Friday
Lot01 863 763 12/2/16 11:01 Friday
Lot01 863 769 12/2/16 11:28 Friday
Lot01 863 784 12/2/16 12:01 Friday
Lot01 863 793 12/2/16 12:28 Friday
Lot01 863 807 12/2/16 12:58 Friday
Lot01 863 795 12/2/16 13:25 Friday
Lot01 863 805 12/2/16 13:58 Friday
Lot01 863 779 12/2/16 14:25 Friday
Lot01 863 745 12/2/16 14:58 Friday
Lot01 863 675 12/2/16 15:31 Friday
Lot01 863 610 12/2/16 15:58 Friday
Lot01 863 561 12/2/16 16:32 Friday
Lot01 863 863 12/6/16 7:56 Tuesday
Lot01 863 863 12/6/16 8:29 Tuesday
Lot01 863 863 12/6/16 8:56 Tuesday
Lot01 863 863 12/6/16 9:29 Tuesday
Lot01 863 863 12/6/16 10:02 Tuesday
Lot01 863 863 12/6/16 10:29 Tuesday
Lot01 863 863 12/6/16 11:02 Tuesday
Lot01 863 863 12/6/16 11:29 Tuesday
Lot01 863 863 12/6/16 11:56 Tuesday
Lot01 863 858 12/6/16 12:29 Tuesday
Lot01 863 861 12/6/16 12:56 Tuesday
Lot01 863 853 12/6/16 13:29 Tuesday
Lot01 863 834 12/6/16 14:02 Tuesday
Lot01 863 813 12/6/16 14:29 Tuesday
Lot01 863 777 12/6/16 15:02 Tuesday
Lot01 863 722 12/6/16 15:29 Tuesday
Lot01 863 669 12/6/16 16:02 Tuesday
Lot01 863 604 12/6/16 16:29 Tuesday
Lot01 863 346 12/7/16 7:59 Wednesday
Lot01 863 407 12/7/16 8:26 Wednesday
Lot01 863 486 12/7/16 8:55 Wednesday
Lot01 863 596 12/7/16 9:26 Wednesday
Lot01 863 702 12/7/16 9:59 Wednesday
Lot01 863 787 12/7/16 10:26 Wednesday
Lot01 863 845 12/7/16 10:59 Wednesday
Lot01 863 860 12/7/16 11:25 Wednesday
Lot01 863 860 12/7/16 11:59 Wednesday
Lot01 863 856 12/7/16 12:26 Wednesday
Lot01 863 854 12/7/16 12:59 Wednesday
Lot01 863 841 12/7/16 13:26 Wednesday
Lot01 863 841 12/7/16 13:59 Wednesday
Lot01 863 826 12/7/16 14:26 Wednesday
Lot01 863 776 12/7/16 14:59 Wednesday
Lot01 863 739 12/7/16 15:32 Wednesday
Lot01 863 703 12/7/16 15:59 Wednesday
Lot01 863 643 12/7/16 16:32 Wednesday
Lot01 863 330 12/8/16 7:59 Thursday
Lot01 863 417 12/8/16 8:26 Thursday
Lot01 863 522 12/8/16 8:59 Thursday
Lot01 863 623 12/8/16 9:26 Thursday
Lot01 863 750 12/8/16 9:59 Thursday
Lot01 863 838 12/8/16 10:32 Thursday
Lot01 863 857 12/8/16 10:59 Thursday
Lot01 863 856 12/8/16 11:32 Thursday
Lot01 863 858 12/8/16 11:59 Thursday
Lot01 863 851 12/8/16 12:25 Thursday
Lot01 863 862 12/8/16 12:59 Thursday
Lot01 863 861 12/8/16 13:25 Thursday
Lot01 863 859 12/8/16 13:59 Thursday
Lot01 863 852 12/8/16 14:26 Thursday
Lot01 863 819 12/8/16 14:59 Thursday
Lot01 863 774 12/8/16 15:26 Thursday
Lot01 863 725 12/8/16 15:59 Thursday
Lot01 863 676 12/8/16 16:32 Thursday
Lot01 863 402 12/9/16 8:02 Friday
Lot01 863 471 12/9/16 8:29 Friday
Lot01 863 566 12/9/16 8:55 Friday
Lot01 863 667 12/9/16 9:29 Friday
Lot01 863 735 12/9/16 9:55 Friday
Lot01 863 787 12/9/16 10:29 Friday
Lot01 863 807 12/9/16 10:56 Friday
Lot01 863 839 12/9/16 11:29 Friday
Lot01 863 844 12/9/16 11:56 Friday
Lot01 863 859 12/9/16 12:29 Friday
Lot01 863 849 12/9/16 13:02 Friday
Lot01 863 830 12/9/16 13:29 Friday
Lot01 863 815 12/9/16 14:02 Friday
Lot01 863 809 12/9/16 14:29 Friday
Lot01 863 771 12/9/16 14:56 Friday
Lot01 863 726 12/9/16 15:29 Friday
Lot01 863 626 12/9/16 16:02 Friday
Lot01 863 570 12/9/16 16:29 Friday
Lot01 863 257 12/10/16 7:59 Saturday
Lot01 863 269 12/10/16 8:29 Saturday
Lot01 863 303 12/10/16 9:02 Saturday
Lot01 863 338 12/10/16 9:29 Saturday
Lot01 863 400 12/10/16 9:55 Saturday
Lot01 863 468 12/10/16 10:29 Saturday
Lot01 863 521 12/10/16 11:02 Saturday
Lot01 863 562 12/10/16 11:29 Saturday
Lot01 863 605 12/10/16 12:02 Saturday
Lot01 863 618 12/10/16 12:29 Saturday
Lot01 863 651 12/10/16 12:55 Saturday
Lot01 863 677 12/10/16 13:29 Saturday
Lot01 863 684 12/10/16 13:56 Saturday
Lot01 863 693 12/10/16 14:25 Saturday
Lot01 863 685 12/10/16 15:02 Saturday
Lot01 863 667 12/10/16 15:25 Saturday
Lot01 863 614 12/10/16 15:59 Saturday
Lot01 863 582 12/10/16 16:25 Saturday
Lot01 863 260 12/11/16 8:02 Sunday
Lot01 863 261 12/11/16 8:25 Sunday
Lot01 863 264 12/11/16 8:59 Sunday
Lot01 863 271 12/11/16 9:26 Sunday
Lot01 863 302 12/11/16 9:59 Sunday
Lot01 863 371 12/11/16 10:25 Sunday
Lot01 863 486 12/11/16 10:59 Sunday
Lot01 863 569 12/11/16 11:26 Sunday
Lot01 863 660 12/11/16 11:59 Sunday
Lot01 863 723 12/11/16 12:32 Sunday
Lot01 863 780 12/11/16 13:05 Sunday
Lot01 863 823 12/11/16 13:26 Sunday
Lot01 863 860 12/11/16 13:59 Sunday
Lot01 863 851 12/11/16 14:32 Sunday
Lot01 863 823 12/11/16 14:59 Sunday
Lot01 863 797 12/11/16 15:25 Sunday
Lot01 863 749 12/11/16 15:59 Sunday
Lot01 863 677 12/11/16 16:25 Sunday
Lot01 863 369 12/12/16 8:02 Monday
Lot01 863 459 12/12/16 8:29 Monday
Lot01 863 557 12/12/16 9:02 Monday
Lot01 863 651 12/12/16 9:29 Monday
Lot01 863 763 12/12/16 10:02 Monday
Lot01 863 809 12/12/16 10:29 Monday
Lot01 863 842 12/12/16 11:02 Monday
Lot01 863 863 12/12/16 11:29 Monday
Lot01 863 855 12/12/16 11:55 Monday
Lot01 863 845 12/12/16 12:29 Monday
Lot01

## Smart Parking Space App Presentation

Purpose

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.

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.

Instructions: Work with the provided Excel database. This database 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 one 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 one, prepare a scatter plot showing the 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?

Presentation:

Create a 10- to 12-slide presentation with speaker notes and audio. Your audience is the City Council members who are responsible for deciding whether the city invests in 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 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 occupancy rate against the time of day of your selected four parking lots. Include your interpretation of the results.
• Make a recommendation about continuing with the implementation of this project.