The document discusses the differences between descriptive and inferential statistics. Descriptive statistics are used to describe characteristics of a whole population, while inferential statistics are used when the whole population cannot be measured and conclusions are drawn from a sample to generalize to the larger population. Examples are provided to illustrate when each type of statistic would be used. Key differences include descriptive statistics examining entire populations while inferential statistics examine samples that aim to infer conclusions about populations.

1. Is this question …
Inferential?Descriptive? or

2. Descriptive Statistics

3. Descriptive statistics are used when you want to
know something about everyone in an entire
group or population.
Central Tendency, Spread, or Symmetry?
Everyone in the
population

4. A population can be
- everyone in a country (e.g., United States,
Zimbabwe, Peru, China, etc.)
- everyone in a company.
- every student in a state, in a school district, in
a school or in a class.

5. A population can be
- everyone in a country (e.g., United States,
Zimbabwe, Peru, China, etc.)
- everyone in a company
- every student in a state, in a school district, in a
school or in a class.
The key words you look for in your research
question are all, everyone, census, entire group…

6. Example
Let’s say we want to know something about all
taxi drivers in New York (e.g., how fast they
drive, how much they charge…).

7. Example
Let’s say we want to know something about all
taxi drivers in New York (e.g., how fast they
drive, how much they charge…).
While it is unlikely, imagine we are able to ask all
13,500 taxi drivers in New York.

8. Example
Let’s say we want to know something about all
taxi drivers in New York (e.g., how fast they
drive, how much they charge…).
While it is unlikely, imagine we are able to ask all
13,500 taxi drivers in New York.
In this case, we would use descriptive statistics
to summarize our findings!

9. Inferential Statistics

10. Central Tendency, Spread, or Symmetry?
Sample of the
population
Everyone in the
population
Inferential statistics are used when you want to know
something about everyone. Since you can’t access the
entire group. You take a small sample from the entire
group and infer or generalize the results to the entire
group.

11. Central Tendency, Spread, or Symmetry?
Sample of the
population
Everyone in the
population
This is when you use
inferential statistics!
Inferential statistics are used when you want to know
something about everyone. Since you can’t access the
entire group. You take a small sample from the entire
group and infer or generalize the results to the entire
group.

12. Central Tendency, Spread, or Symmetry?
Sample of the
population
Everyone in the
population
Look for words like, “infer,”
“generalize,” “statistical
significance”…
Inferential statistics are used when you want to know
something about everyone. Since you can’t access the
entire group. You take a small sample from the entire
group and infer or generalize the results to the entire
group.

13. Example
Let’s say we want to know something about all taxi
drivers in New York (e.g., how fast they drive, how
much they charge…)
But we do not have the ability to ask all 13,500 of
them.
Let’s say we chose a small group of 80 and asked
them. Inferential statistics make it possible to infer
what is happening with the 80 to all 13,500.

14. Example
Let’s say we want to know something about all taxi
drivers in New York (e.g., how fast they drive, how
much they charge…)
But we do not have the ability to ask all 13,500 of
them.
Let’s say we chose a small group of 80 and asked
them. Inferential statistics make it possible to infer
what is happening with the 80 to all 13,500.

15. Example
Let’s say we want to know something about all taxi
drivers in New York (e.g., how fast they drive, how
much they charge…)
But we do not have the ability to ask all 13,500 of
them.
Let’s say we choose a small group of 80 and ask
them. Inferential statistics make it possible to infer
what is happening with the 80 to all 13,500.
infer

16. Example
Let’s say we want to know something about all taxi
drivers in New York (e.g., how fast they drive, how
much they charge…)
But we do not have the ability to ask all 13,500 of
them.
Let’s say we choose a small group of 80 and ask
them. Inferential statistics make it possible to infer
what is happening with the 80 to all 13,500.
infer

17. Let’s Practice!

18. Find the average driving distance from home to
work for all employees at your company.
Inferential Descriptive

19. Find the average driving distance from home to
work for all employees at your company.
Inferential Descriptive

20. Find the average driving distance from home to
work for all employees at your company.
Inferential Descriptive

21. Find the average driving distance from home to
work for all employees at your company.
Inferential Descriptive
Descriptive statistics are used when you want to
know something about everyone in an entire
group.
Everyone in the
population

22. Next Example

23. What factors influence employees to stay at
your company? You take a sample of 40
employees and generalize the results to all
employees who stay.
Inferential Descriptive

24. What factors influence employees to stay at
your company? You take a sample of 40
employees and generalize the results to all
employees who stay.
Inferential Descriptive

25. What factors influence employees to stay at
your company? You take a sample of 40
employees and generalize the results to all
employees who stay.
Inferential Descriptive

26. What factors influence employees to stay at
your company? You take a sample of 40
employees and generalize the results to all
employees who stay.
Inferential Descriptive
Inferential statistics are used when you want to know
something about everyone from a smaller group.
Sample
from the
population
Everyone in the
population

27. Final Example

28. How do the customer satisfaction levels
compare between English and Spanish speaking
customers? You compare samples from each
group and infer the results to both populations.
Inferential Descriptive

29. How do the customer satisfaction levels
compare between English and Spanish speaking
customers? You compare samples from each
group and infer the results to both populations.
Inferential Descriptive

30. How do the customer satisfaction levels
compare between English and Spanish speaking
customers? You compare samples from each
group and infer the results to both populations.
Inferential Descriptive

31. How do the customer satisfaction levels
compare between English and Spanish speaking
customers? You compare samples from each
group and infer the results to both populations.
Inferential Descriptive
Sample
from the
population
Everyone in the
population
Inferential statistics are used when you want to know
something about everyone from a smaller group.

32. In this course you will learn when to run 24
statistical methods.

33. In this course you will learn when to run 24
statistical methods. By choosing descriptive that
narrows the number down to 6 possible
methods.

34. In this course you will learn when to run 24
statistical methods. By choosing descriptive that
narrows the number down to 6 possible
methods.
Mean Median Mode Range Stdev IQR
Descriptive?

35. In this course you will learn when to run 24
statistical methods. By choosing inferential that
narrows the number down to 18 possible
methods.

36. In this course you will learn when to run 24
statistical methods. By choosing inferential that
narrows the number down to 18 possible
methods.
Inferential?or
Single t Ind t Pair t anova ancova F-anova
RM Split Pearson Partial Point-B Phi
Spear Kendall Single R Multi R Chi Ind Chi Fit
Mean Median Mode Range Stdev IQR
Descriptive?

37. Return to your original question. What type of
research question is it?
Inferential?Descriptive? or