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Data measurement is an important aspect of data analytics. Identifying trends in key attributes of data is a fundamental measurement for various aspects of business data and an important skill for bus
Data measurement is an important aspect of data analytics. Identifying trends in key attributes of data is a fundamental measurement for various aspects of business data and an important skill for business professionals. In this scenario, you are a business consultant trainee assigned to work with your first client, TC Ice Cream.
TC Ice Cream is a private-label ice cream manufacturer. Located in the northern region of Michigan, TC Ice Cream specializes in premium ice cream flavors. TC Ice Cream is categorized in the food/agriculture business sector. The company has gained popularity over the past three years due to recent publicity such as winning awards on network television food shows, hosting and attending promotional events, and actively using social media.
The management team of TC Ice Cream is looking to see if there are specific trends that could be identified to help them improve their operations and sales and grow their business. You will report the research and analysis of the data to the TC Ice Cream management team. Periodically, you will be expected to apply your training and submit a deliverable to the management team.
The TC Ice Cream information technology team has provided you with a data set, TC Ice Cream Excel Workbook, that contains data about orders over a span of three years.
You will use the data variables to create descriptive statistics and visualizations for TC Ice Cream. This will enable you to effectively and efficiently gain helpful insights into the data and its attributes. You will continue to delve further into your analysis of TC Ice Cream throughout the course.
Prompt
For this assignment, you will perform the following steps as you begin your analysis of the data provided.
Within the TC Ice Cream Excel Workbook, review the sheet “Data Dictionary.” This will help you understand the data provided and specific information about each variable. Review the sheet “TC Ice Cream Data.” DO NOT EDIT this data.
Next, you will calculate the central tendency of the TC Ice Cream data set using the average, median, minimum, maximum, and range. You will also create multiple charts to present the descriptive analysis you performed.
Specifically, you must address the following rubric criteria:
- Create a table to represent the average, median, minimum, maximum and range values for each variable. Within the TC Ice Cream Excel Worksheet, use the sheet “Descriptive Statistics” to create the following table.
- Use Excel formulas to calculate the average, median, minimum, maximum, and range values for each of the quantitative variables (Quantity Sold, Advertising Expenses, Flavor Rating, Social Media Posts, Event Promotions).
- Create charts to represent the key variables of the data. Within the TC Ice Cream Excel Worksheet, use the sheet “Overall Analysis” to create the charts listed below. It is recommended that you use pivot tables/pivot charts to create the visualizations. Feel free to use this sheet to create any additional visualizations that might help you better understand the data.
- Create a pie chart using the qualitative variable Region and the quantitative variable Quantity Sold to provide a visualization of percentage overview of quantity sold by region.
- Create a line chart (also known as a trend chart) using the qualitative variable Date and the quantitative variable Quantity Sold to provide a visualization displaying quantity sold by month.
- Create a bar chart using the qualitative variable Flavor and the quantitative variable Quantity Sold to provide a visualization displaying quantity sold by flavor.
- Use the Module One PowerPoint Template to create a PowerPoint presentation that explains the data and its key variables. This should include key visualizations and analysis to support your answers. The PowerPoint Template includes specific questions to answer as you explain the data and variables. Use the visualizations and data analysis you created in the “Descriptive Statistics” and “Overall Analysis” sheets to support your analysis.
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********************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************* of Quantity SoldMidwest2009%Northeast2585%South3415%West1990%Grand Total10000%Sum ** Quantity ********** **************************** TotalQtr1Jan336406976735472617524175915332 ****************************************** ****************************************** ********************************************** ****************************************** ****************************************** ********************************************** 224769972Aug498896583655620278665992091334 ****************************************** 136615564Qtr4Oct4030781794453067124565525943 ****************************************** ****************************************** ************** *********************************** 1759114778FlavorSum ** ******** ********** ****************** 243011599Coconut 211159135Coffee *************** ***** 190148412Cookies *** ***** 125227041Neapolitan ************** **** ******************* **************** ************** ********************** ********