Chat with us, powered by LiveChat This assignment illustrates how data analytics can be used to create strategies for sustainable organizational success while integrating the organizations mission with societal values. Yo | Wridemy

This assignment illustrates how data analytics can be used to create strategies for sustainable organizational success while integrating the organizations mission with societal values. Yo

 

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.  

Resource: Microsoft Excel DAT/565 Week 6 Data File

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:

Search the Internet and University Library for information on “smart cities” to provide guidance and support for your presentation.

Create a 10- to 12-slide presentation with speaker notes. 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.
  • Include citations of resources.

***

Boxplot

Data Set 75 69 84 112 74 104 81 90 94 144 79 98
Sorted 69 74 75 79 81 84 90 94 98 104 112 144
Step 1
Step 2
Step 3
step 4
step 5

Median=(84+90/2=87) Q1=(75+79)/2=77 Q3=(98+104)/2=101 IQR=Q3−Q1=101−77= 24    

 Find the points that are 1.5×IQR below Q1 and 1.5×IQR above Q3  These two points are called the lowerLower inner fenceThe value in a data set that is 1.5×IQR below the first quartile. and the upper inner fencesUpper inner fenceThe value in a data set that is 1.5×IQR above the third quartile., respectively.  

1.5×IQR=1.5×24 =36 Lower inner fence = Q1−36=77−36=41 Upper inner fence = Q3+36=101+36=137  

These two values for our example are as follows: Smallest value within the two inner fences=69 Largest value within the two inner fences=112  

Draw a horizontal line and mark the income levels on it such that all the values in the given data set are covered. Above the horizontal line, draw a box with its left side at the position of the first quartile and the right side at the position of the third quartile. Inside the box, draw a vertical line at the position of the median.  

By drawing two lines, join the points of the smallest and the largest values within the two inner fences to the box. These values are 69 and 112 in this example as listed in Step 3. The two lines that join the box to these two values are called whiskers. A value that falls outside the two inner fences is shown by marking an asterisk and is called an outlier.  

Determine the smallest and the largest values in the given data set within the two inner fences.

By drawing two lines, join the points of the smallest and the largest values within the two inner fences to the box. These values are 69 and 112 in this example as listed in Step 3. The two lines that join the box to these two values are called whiskers. A value that falls outside the two inner fences is shown by marking an asterisk and is called an outlier.  

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ParkingLotUtilization

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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