1. Statistics and Storytelling with Data
Dr. Lam
TECM 4180

2. Let’s Review Line charts are good for?? Bar charts?? Pie Charts??
Pictographs??
Tables??

3. Types of Variables Quantitative variables (interval, ordinal)
Interval – numerical with meaningful distance between the numbers (e.g., temperature)
Ordinal – Numerical without meaningful distance between the numbers (e.g., happiness from 1-5)
Qualitative variables (categorical)
Non-numerical variables with no sense of ordering (e.g., hair color, eye color, job title)
Sample dataset collected 5 variables from 100 undergraduate students:
Academic status (freshman, sophomore, junior, and senior)
Major
SAT score
GPA
# of detentions in high school

4. Descriptive vs. inferential statistics
Descriptive stats provide us with a broad overview of our variables
Central tendencies- Mean, median, and mode
E.g., AVG SAT score
Frequencies and frequency distribution
E.g., How many freshman vs. senior students
Inferential Stats tell us about how variables relate
Do variables correlate?
Does one group have a significantly different average on SAT scores to another group?

5. Descriptive statistics and visualizations
Year
SAT AVG.
Freshman
1369
Sophomore
1198
Junior
1245
Senior
1009
Central tendencies (1 variable)
Mean – average
E.g., Average SAT score in the dataset
Visualize with tables, bar charts, and line charts

6. Frequency Distribution
Frequency distribution (1 variable) – How many times (how frequently) each variable appears
E.g., You are examining 100 undergraduates; 22 are freshman, 33 are sophomores, 21 are juniors, and 24 are seniors.
Can be visualized using tables or histograms (which are essentially bar charts)
Year
Total Participants
Freshman 22
Sophomore 33
Junior 21
Senior 24

7. Inferential Statistics – Correlations
Correlation (2 quantitative variables) – dependency between 2 or more variables
Positive – When 1 variable increases, the other also increases
E.g., GPA and SAT scores
Negative – When 1 variable increases, the other variable decreases
E.g., GPA and Detentions
R, which is the correlation coefficient, tells you how strong the relationship is.
-1 and 1
Values closer to 1 show a stronger positive correlation
Values closer to -1 show a stronger negative correlation
In Excel, use the following formula:
“CORREL(FirstCell:LastCell, FirstCell:LastCell)

8. Inferential Statistics – comparing means
What groups can we compare means to?
Process:
Calculate the means for each group separately
”AVERAGE(FirstCell:LastCell)”
Visualize the results using a bar chart or column chart

9. Three elements to a successful infographic
Understands audience
Anderson page 62 communication goals worksheet due with Project 2
A clear framework
Essentially, what is the data? Is it clear to everyone? What parts of the data will need explaining?
It tells a story
From Harvard Business Review (

10. What makes a good story?
Poll

11. Parts of a Story Introduction to the situation
A series of events involving tension or conflict
Resolution

12. Storytelling with data

13. Four characteristics of storytelling with data
Connect with people
Try to convey one (or a centralized) idea
Keep it simple
Explore what you know

14. Practical strategies for infographics
Repeat yourself in a variety of visual ways
Draw your reader in with a compelling question or problem
Use transitional statements if necessary

15. With a partner
Complete the storytelling analysis activity on the resources page of the website.