pART 1 Required: Calculate the grand totals of Customer Count, Sum of InvoiceAm

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pART 1
Required:
Calculate the grand totals of Customer Count, Sum of InvoiceAm

pART 1
Required:
Calculate the grand totals of Customer Count, Sum of InvoiceAmount, and Count of Due Date.
Subtotal the accounts receivable by date in a pivot table.
Add in conditional formatting to the count of the Customer field.
Create a line chart representing customer orders by day.
Data: Lab 2.1 Data.xlsx
Specify the Question: How do data types affect the way I can analyze data in Excel? How many payments were due on which dates?
Obtain the Data: This lab uses the Excel file titled Lab 2.1 Data.xlsx. The data file contains 200 individual transactions representing the amount of money each customer (column A) owes (column B) and when the invoice is due (column C). All of these receivables are past their due date as of today’s date, 12/31/2025.
Analyze the Data: Refer to lab 2.1 in your text for additional instructions and steps.
Upload one Word or PDF document containing all of your screenshots for this Lab using the button below.
Note: Please submit your file attachment response in one of the approved file formats; Word file (.doc or .docx), Excel file (.xls or .xlsx), or PDF. To submit photo or image files please paste them into Word or PDF. Consult with your instructor as needed on their preferred file attachment format.
Take a screenshot of the first several rows in the pivot table with the conditional formatting, paste it into a Word document named “Lab 2.1 Excel Submission”, and label the screenshot Submission 1.
Take a screenshot of the Line Chart, paste it into the Word document named “Lab 2.1 Excel Submission”, and label the screenshot Submission 2.
PART 2
Answer the following questions based on the details computed. (ATTACHED)
PART 3
Describe how Excel interprets dates numerically. Why is it meaningful to attach a serial number to dates?
Given the data that is provided in this dataset (Customer, Invoice Amount, and Due Date), list two questions that would be interesting to answer regarding the accounts receivable data in this dataset.

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