Lab 10

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:

Task 1 Throughout the first few weeks, sales were increasing and then around week 22 it started deacreasing dramatically. In week 23 sales reached its lowest point and then began incrasing again and in week 26 sales reached the same level it had before the deacrease in week 22. In week 32 sales deacrease again but by week 37 sales kind of remain steady.

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:

Task 2 Everything looks exactly the same except around week 23. There is not such a drmatic deacrease in sales there.

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, Applu, OK). Include a snapshot here. Explain the combined behavior of sales and temperature.

ANSWER TASK 3:

Task 3 There is no reall patter. At the beggining it seems like as the temperature increases so do sales. Then in the midlle we see the highest temperatures lead to the highes sales and as the temperature falls so do sales. As the temperature drops more, the dales fluctuate around the same values (between 20,000 and 22,000).

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?

ASNWER TASK 4:

Task 4 The higher sales values tend to be associated with a high amount of $ spent on ads. However the amount of sales seem to be very similar when the co spends just around $100 in ads and $220 therfore I think that the company should not spend more than 100 in ads.

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:

Task 5 High amount of money spet on radio seems to lead to high sales. In the upper right part of the graph we see the data points with the highest levels of sales, they all seem to have spent the same amount of money on radio (between 200 and 240). What really makes a difference is the amount spent on tv. The highest sale values are acompained by high quantities of money spent on tv ads.

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 6 The pattern seems much clearer. as the fuel volume increases so do sales.

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:

Task 7 The higher the temperature the higher the fuel volume and the sales.

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

ASNWER TASK 8:

Task 8 When there is a holiday sales are higher. Fuel volume is also pretty high when there is a holiday.

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 9

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

ASNWER TASK 10:

I believe that the factors that affect the sales the most are holiday and temperature. We continously saw that the highest sales were associated with a high temperature and the appearance of a holiday.