About

In this section, we will be using Tableau to learn concepts on data outliers, seasonality effect, and the relationships and impacts. There is no R coding in this lab session.

Setup

This worksheet will be used to capture your images from Tableau and to share your observations. Example of capturing and including an image is included at the end of this sheet for your reference. You will need to log onto Tableau and Connect/Import the file EuroStore.xls found in the ‘bsad_lab10’ folder.

Remember to always set your working directory to the source file location. Go to ‘Session’, scroll down to ‘Set Working Directory’, and click ‘To Source File Location’. Read carefully the below and follow the instructions to complete the tasks and answer any questions. Submit your work to RPubs as detailed in previous notes.

Note

For your assignment you may be using different data sets than what is included here. Always read carefully the instructions on Sakai. Tasks/questions to be completed/answered are highlighted in larger bolded fonts and numbered according to their particular placement in the task section.

mydata = read.csv("data/EuroStore.csv")
head(mydata)
##   Week Sales   TV Radio Fuel.Volume Fuel.Price Temp Holiday
## 1   26 24864 74.5  66.5       61825     104.24 27.9       1
## 2   27 23809 74.5  66.5       62617     103.97 27.7       1
## 3   28 24476 90.0  75.0       60227     107.48 29.1       1
## 4   29 25279 90.0  75.0       63273     111.75 30.0       1
## 5   30 26263 90.0  75.0       65196     109.08 29.3       1
## 6   31 24299 90.0  75.0       64789     105.36 28.1       1

PART A: DATA OUTLIERS AND SEASONALITY EFFECT

First get familiar with the data and what each columns represent. A description of the data is provided in a seperate sheet called ‘Desc’ in the same Excel file. Refer to Lab05 for early exercise using Tableau.

In a new Tableau sheet

TASK 1: Plot Sales (Rows) versus Week (Columns). Include a snapshot here. (To save the image go to Worksheet, select Export, Image, Save.) Analyse the data source and explain in clear words the behavior you observe.

##ANSWER TASK 1:

Sales increased gradually from weeks 0 to 20. From week 20 to 25, there is a substantial decrease in sales. During week 25, sales increased dramatically, then repeatedly fluctuated in the weeks after.

TASK 2: Switch from SUM(Sales) to Average AVG(Sales) by clicking the arrow on the right of Sum(Sales), select Measure and Average. Change the Sales scale to be more reflective of the data (double click on the Avg. Sales axis, under Range select Fixed, change the Fixed Start and Fixed End then close the window). Include a snapshot here. Explain the new behavior relative to Task 1).

##ANSWER TASK 2:

Relative to TASK 1, the sales continued to fluctuate between increasing to decreasing over the weeks. However, there are no dramatic increases or decreases in the graph. ##### TASK 3: Add Temp to the Color scale found in Marks. Change SUM(Temp) to AVG(Temp). Edit the color legend to be more reflective of hot and cold temperatures (by clicking on Color, Edit Color, select relevant color, Apply, OK). Include a snapshot here. Explain the combined behavior of sales and temperature. ##ANSWER TASK 3:

The combined behavior of sales and temperature shows us that sales were the highest from week 25 to 35, which was also when the temperature was the warmest. As the temperature increases, sales increase. As temperature decreases, sales decrease. The relationship between sales and temperature is positive.

PART B: RELATIONSHIPS AND IMPACTS

In a seperate Tableau sheet

TASK 4: Plot Sales (Rows) versus TV (Columns). Switch both measures from SUM() to Dimension. The plot should look more like a scatter plot. Include a snapshot here. Explain the behavior of Sales versus TV. How much you think is the upper limit amount that should be invested in TV ads?

##ANSWER TASK 4:

This scatter plot does not portray a direct relationship between Sales and TV and there seems to be no pattern to follow. The upper limit should be $100,000. After that, there are not enough sales to justify investing $220,000 into TV advertisements, as very few sales are being made above $100,000. ##### TASK 5: Overlay Radio to the previous plot using the Size scale found in Marks. Include a snapshot here. Explain how the additional Radio ads to Tv ads is impacting Sales. ##ANSWER TASK 5:

Based on the plot, Radio advertisements seem to usually increase sales more than TV advertisements. At some points, like when there are $24,829 in sales, there is more spent on TV than Radio, but usually it is the other way around. Just like in TASK 4, most of the sales occur at or below the $100,000 range. Radio advertisements are similar to TV advertisements in that by adding more advertisements, sales go up (but the upper limit should stilll be $100,000).

In a separate Tableau sheet

TASK 6: Plot Sales versus Fuel Volume. Switch both measures from SUM() to Dimension. Explain behavior.

##ANSWER TASK 6:

TASK 7: Overlay Temperature using the Color scale. Follow TASK 3 for temperature settings. Explain the new combined behavior and the impact of temperature.

##ANSWER TASK 7:

Based on this plot, the warmer the weather, the more fuel volume gets sold, which results in higher sales. There is a positive relationship and correlation between increased temperatures and increased fuel volume, which leads to increased sales. This is likely because people are more likely to drive during warmer weather, and therefore will need and buy more fuel to do so.

TASK 8: Overlay Holiday using the Label scale. Include a snapshot here. Explain the new combined behavior and the impact of Holiday.

##ANSWER TASK 8:

The weeks which had holidays are indicated with the number “1”. If there is a holiday during the week, there are usually higher sales that week. A positive relationship and correlation also exists between holidays and increased sales.

In a separate sheet

TASK 9: Use a Tree Map to best show the combined effect of Sales, Fuel Volume, Temp, and Holiday. A sample view is shown below. Consider using the Quick Filter on Holiday and Temp to isolate and better view the impact of each. You can have more than one filter at a time. Include a snapshot here.

TASK 10: Write a small paragraph summarizing your final conclusions on what you think most affect Sales and under what conditions.

##ANSWER TASK 10: Sales seem to be most effected by temperature and holidays. Sales go up as temperatures increase or during the holidays. Fuel volume does not seem to have mucn impact on sales, however, it seems to have positive relationships with both higher temperatures and holidays. People are willing to drive more during warmer weather and during the holidays, thus fuel volume increases. During colder temperatures, people are less likely to go out and drive, even during the holidays. Thus, fuel volume doesn’t have drastic increases during the colder temperatures.