Office 2016 MyITLab Grader Instructions For Excel Project

Office 2016 Myitlabgrader Instructionsexcel Projectdescribing Da

The present study shows data for sales of different sports equipment in 2017 in a sports supplies store. The sales are provided per month. We will identify the type of data for different variables and their measurement levels. We will analyze the data numerically using measures of central tendency (mean, median, minimum and maximum) and variability (range, interquartile range, standard deviation and variance). We will construct a frequency table and investigate the relationship between variables by analyzing the correlation.

We will also represent the data graphically by using line charts and pie charts. Instructions: For the purpose of grading the project you are required to perform the following tasks: Step Instructions Points Possible 1 Use a cell reference or a single formula where appropriate in order to receive full credit. Do not copy and paste values or type values, as you will not receive full credit for your answers. Start Excel. Download and open the workbook named: Describing Data Graphically and Numerically Start 0 2 In merged cells D11-E11, select the data type of "Equipment ID". 3 3 In merged cells D12-E12, select the data type of "sales for each month”. 3 4 In merged cells D13-E13, select the data type of "Equipment". 3 5 In cells O3 through O8, find the total sales for each equipment. Hint: Highlight the range C3:N8 and click the Quick Analysis Button that appears on the lower right corner then click on the totals tab and use the second Sum function. 7 6 In cells C9 through N9, find the total sales for each month. In cell O9, find the total sales for the year. Hint: Use the sum shortcut; click on cell C9 and then on your keyboard press ALT then press =. 6 7 In cells P3 through P9, insert Sparklines. Hint: Click on cell P3, go to Insert Sparklines Line. Use the data range C3:N3. 7 8 In cell D17, choose the correct conclusion from the dropdown menu based on the line in cell P9. 3 9 In cell D18, find the average sales per month in 2017. 4 10 In cell D19, find the median sales per month in 2017. 4 11 In merged cells D20-E20, choose the correct answer from the dropdown menu based on the answers in cells D18 and D19. 4 12 In cell D21, find the minimum sales per month in 2017. 3 13 In cell D22, find the maximum sales per month in 2017. 3 14 In cell D23, find the range of sales per month in 2017. 4 15 In cells D24 and D25, find Q1 and Q3, respectively, for the sales per month in 2017. 4 16 In cell D26, find the interquartile range per month in 2017. 3 17 In cells D27 through D31, find the five-number summary for the sales per month in 2017. 5 18 In cell D32, find the standard deviation in sales per month in 2017. 3 19 In cell D33, find the variance in sales per month in 2017. 3 20 In cell F35 through F40, construct a frequency table for the total sales in 2017 for each piece of equipment. 6 21 In merged cells E41-F41, find the correlation between "Balls" sales and "Goals" sales. 3 22 In merged cells E42-F42, find the correlation between "Nets" sales and "Rods and tackles" sales. 3 23 In merged cells D43-F43, choose the correct answer from the dropdown menu based on the correlation values. 3 24 In merged cells D44-H44, choose the correct answer from the dropdown menu based on the correlation values. 3 25 Insert a recommended line chart using the range A2 through N8. Change the chart title to "Monthly Sales per Equipment". Resize the chart to fit in the range A46 through G56. Hint: Highlight the range A2:A8 then press control and highlight C2:N8 then go to the Insert tab and click recommended chart and then line chart. 5 26 Insert a 3D pie chart using the range A2:A8 and O2:O8. Remove the legend and display the data labels in the center showing the category name and percentage. Add a chart title “Total Sales in 2017”. Resize the chart to fit in the range A58 through G68. 5 27 Save your file and submit for grading. 0 Total Points 100 Updated: 05/20/2018 1 Current_Instruction.docx

Paper For Above instruction

The analysis of sales data for sports equipment in a retail store in 2017 provides valuable insights into sales performance, customer preferences, seasonal trends, and relationships among different product categories. This comprehensive study employs various statistical and graphical tools to interpret raw sales numbers, facilitating data-driven decision-making to optimize inventory, marketing, and sales strategies.

Data Identification and Measurement Levels: The dataset includes variables such as Equipment ID, Equipment type, sales figures per month, and total sales. Equipment ID and Equipment are categorical variables with nominal measurement levels, categorizing products without intrinsic ordering. Sales figures and total sales are continuous variables measured at the ratio level, allowing for meaningful computation of averages, variances, and ratios.

Numerical Data Analysis: The initial phase involves summarizing sales performance through measures of central tendency—mean, median, minimum, and maximum—accompanied by measures of variability such as range, interquartile range (IQR), standard deviation, and variance. These statistics provide insights into the typical sales volume, the dispersion of data, and the presence of outliers.

The calculations reveal that the average monthly sales per equipment type are indicative of overall demand, with the median offering robustness against outliers. The minimum and maximum sales figures highlight sales extremes, informing inventory management. The range, interquartile range, and standard deviation quantify the variability, indicating the consistency or fluctuation in sales across months. The five-number summary consolidates this information, aiding in quick assessments.

Frequency and Correlation Analysis: Constructing a frequency table for total sales categorizes equipment into sales brackets, revealing sales concentration trends. Further, analyzing correlations between sales of related product categories, such as “Balls” versus “Goals” and “Nets” versus “Rods and tackles,” uncovers relationships that may influence cross-promotional strategies. The strength and direction of correlations inform whether product sales move together, complement each other, or vary independently.

Graphical Representation: Visual tools include line charts and pie charts that exemplify sales trends over time and share of each equipment type in total sales. The line chart displays monthly sales variations, revealing seasonal patterns, peaks, and declines. The pie chart illustrates the proportional contribution of each equipment category, facilitating quick visual assessment of sales dominance. Labels and titles are customized for clarity, ensuring effective communication of insights.

Conclusion and Business Implications: The detailed statistical analysis underscores the importance of understanding sales variability and relationships among product categories. Recognizing peak sales months enables targeted promotions, while understanding product correlations supports bundling strategies. The graphical visualizations enhance stakeholder interpretation, supporting strategic planning and inventory control. Ultimately, such data analysis empowers the store to maximize sales and improve customer satisfaction through data-informed decisions.

References

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