Quarto Presentation – Starter Example

INTRODUCTION

• This is an introduction to creating presentation output using Quarto
  
• Notice how headers are used to create pages of content
  
• This is just a simple example - we will improve on the design and flow throughout the semester
  
• Use the CRISP-DM Model to create a relevant story line
  

Data Understanding

• We will use the Titanic dataset for our analysis
  
• The dataset has information on all 1309 passengers aboard the Titanic when it sank in April 1912
  
• The dataset has the following variables
  

'data.frame':   1309 obs. of  12 variables:
 $ PassengerId: int  1 2 3 4 5 6 7 8 9 10 ...
 $ Survived   : int  0 1 1 1 0 0 0 0 1 1 ...
 $ Pclass     : int  3 1 3 1 3 3 1 3 3 2 ...
 $ Name       : chr  "Braund, Mr. Owen Harris" "Cumings, Mrs. John Bradley (Florence Briggs Thayer)" "Heikkinen, Miss. Laina" "Futrelle, Mrs. Jacques Heath (Lily May Peel)" ...
 $ Sex        : chr  "male" "female" "female" "female" ...
 $ Age        : num  22 38 26 35 35 NA 54 2 27 14 ...
 $ SibSp      : int  1 1 0 1 0 0 0 3 0 1 ...
 $ Parch      : int  0 0 0 0 0 0 0 1 2 0 ...
 $ Ticket     : chr  "A/5 21171" "PC 17599" "STON/O2. 3101282" "113803" ...
 $ Fare       : num  7.25 71.28 7.92 53.1 8.05 ...
 $ Cabin      : chr  "" "C85" "" "C123" ...
 $ Embarked   : chr  "S" "C" "S" "S" ...

Passenger Statistics by Gender

• The Titanic had more men than women – almost two-thirds were men.
  

female   male 
   466    843 

• Percent distribution by gender

female   male 
  35.6   64.4 

Passenger Statistics by Survival

• These data show that fewer passengers survive than did not survive.
  
• However, there are quite a few passengers for whom no survival information is available.
  

Did Not Survive        Survived          Unsure 
            549             342             418 

• Percent distribution by survival

Did Not Survive        Survived          Unsure 
           41.9            26.1            31.9 

Passenger Statistics by Gender and Survival

• About half of the women are known to have survived
  
• While over half of the men are known to have perished
  

Cross-Tabulation, Row Proportions  
Sex * Survived.f  
Data Frame: titanic  

-------- ------------ ----------------- ------------- ------------- ---------------
           Survived.f   Did Not Survive      Survived        Unsure           Total
     Sex                                                                           
  female                     81 (17.4%)   233 (50.0%)   152 (32.6%)    466 (100.0%)
    male                    468 (55.5%)   109 (12.9%)   266 (31.6%)    843 (100.0%)
   Total                    549 (41.9%)   342 (26.1%)   418 (31.9%)   1309 (100.0%)
-------- ------------ ----------------- ------------- ------------- ---------------

Passenger Statistics by Gender and Survival

• Most of the non-survivors were men while most of the survivors were women.
  

Cross-Tabulation, Column Proportions  
Sex * Survived.f  
Data Frame: titanic  

-------- ------------ ----------------- -------------- -------------- ---------------
           Survived.f   Did Not Survive       Survived         Unsure           Total
     Sex                                                                             
  female                    81 ( 14.8%)   233 ( 68.1%)   152 ( 36.4%)    466 ( 35.6%)
    male                   468 ( 85.2%)   109 ( 31.9%)   266 ( 63.6%)    843 ( 64.4%)
   Total                   549 (100.0%)   342 (100.0%)   418 (100.0%)   1309 (100.0%)
-------- ------------ ----------------- -------------- -------------- ---------------

Average Age by Gender

[1] 30

# A tibble: 1 × 2
  Sex    Average_Age
  <chr>        <dbl>
1 female          29

# A tibble: 1 × 2
  Sex   Average_Age
  <chr>       <dbl>
1 male           31

• The average age of passengers on board the Titanic is 30 years.
  
• The average age of female passengers is 29 years
  
• The average age of male passengers is 31 years.
  

Average Age by Survival

Survivors tended to be younger than those who did not survive.

Average Age by Gender and Survival

Non-surviving females are younger than surviving females. The opposite is true among males.
The youngest group are female non-survivors.

Average Age by Fare Class and Survival

• Passengers booked fares in First, Second, or Third class
  
• First class passengers tended to be older, regardless of survival status
  

Average Age by Fare Class, Gender, and Survival

Among males, those who did not survive tended to be older than survivors, regardless of fare class.
Among females, first class passengers who did not survive were younger than survivors.

Start your analysis using the Embark variable here

Note that passengers embarked at one of three locations.
S: Southampton, England
C: Cherbourg, France
Q: Queenstown, Ireland

Amount of Passengers by Embarkation Place and Survival Status

Examining the graph provided provides vital insights regarding the distribution of Titanic passengers at various embarkation locations. Notably, the majority of passengers boarded the Titanic in Southampton, England, demonstrating a significant difference as compared to other embarkation points. In comparison, both Queenstown and Cherbourg have substantially lower passenger counts, with similar passenger ratings. When evaluating the survival results based on embarkation points, a surprising discovery emerges. Cherbourg is the only location where the number of passengers who escaped the Titanic disaster outnumbers those who died. In Southampton and Queenstown, however, the most common survival status is “Did Not Survive.” This opens up an intriguing path for additional investigation, as it invites the investigation of potential correlations between embarkation places and survival odds. Insights into the dynamics of passenger demographics and their accompanying results during this historic maritime event may be gained by delving deeper into such linkages.

Number of Titanic Passengers by Embarkation Place and Class

In this graph we can see a definite pattern about the embarkation places of passengers from various classes. Notably, Southampton emerges as the primary embarkation location for Third-class passengers, with the highest number of passengers of any class.We can also see a dynamic in Queenstown, where passengers predominantly belong to Class 3, with minimal representation from Class 1 and Class 2. This unique distribution hints at specific demographic characteristics associated with passengers embarking from Queenstown. Cherbourg, on the other hand, has the second-highest number of First-Class passengers, after only Southampton. Despite this, Cherbourg has a significantly lower total passenger count than Southampton, highlighting a concentration of upper-class passengers within a smaller demography.