1. Introduction to Statistics for the Social Sciences SBS200 - Lecture Section 001, Fall 2017 Room 150 Harvill Building 10: :50 Mondays, Wednesdays & Fridays.
Welcome

2. writing assignment forms notebook and clickers to each lecture
Remember bring your
writing assignment forms
notebook and clickers to each lecture

3. Three tries
Will show up in grades within 24 hours

4. Lab sessions Labs continue Today Everyone will want to be enrolled
in one of the lab sessions
Labs continue Today

5. Project 1 Likert Scale (summated scale) Correlation (scatterplots) Comparing two means (bar graph)

7. Project 1 - Likert Scale - Correlations - Comparing two means (bar graph)
Questions?

8. Break up group of kids into two groups
If you want to know if studying improves test performance in young children
Group 1 - studies & tested
Break up group of kids into two groups
What is the independent variable?
What is the dependent variable?
How many levels are there of the IV?
Is this a “quasi” or “true” experiment?
“Between” or “within” participant design?
Group 2 - does not study & tested

9. What is the independent variable?
If you want to know if “Ginseng drink” is associated with feelings of satisfaction
First test group with placebo drink (sugar pill)
What is the independent variable?
What is the dependent variable?
How many levels are there of the IV?
“Between” or “within” participant design?
Placebo
Then test same group with “Ginseng drink”

15. Placebo (single blind) versus double blind procedure
Single blind procedure (example: use of placebo)
Double blind procedure
What about experimenter bias?

16. Continuous versus discrete
Continuous variable: Variables that can assume any value. There are
(in principle) an infinite number of values between any two numbers
Discrete variable: Variables that can only assume whole numbers.
There are no intermediate values between the whole numbers
Duration
Amount of sand
Number of eggs in a carton
Amount of milk in a glass
Height
Number of cookies on a plate
Distance to the moon
Grains of sand
Number of kids in classroom
Number of textbooks required for class

17. Categorical versus Numerical data
Categorical data (also called qualitative data)
- a set of observations where any single observation is a
word or a number that represents a class or category
Numerical data (also called quantitative data)
- a set of observations where any single observation is a
number that represents an amount or count

18. Handedness - right handed or left handed
Categorical data (also called qualitative data) - a set of observations where any single observation is a word or a number that represents a class or category
Numerical data (also called quantitative data) - a set of observations where any single observation is a number that represents an amount or count
Handedness - right handed or left handed
Family size
Hair color
Ethnic group
GPA
Age (Time since birth)
Temperature
(Kelvin)
Yearly salary
Breed of dog
Gender - male or female
Temperature
(Fahrenheit)
Please note this is a binary variable

19. On a the top half of a writing assignment form
Categorical data (also called qualitative data) - a set of observations where any single observation is a word or a number that represents a class or category
Numerical data (also called quantitative data) - a set of observations where any single observation is a number that represents an amount or count
On a the top half of a writing assignment form
please generate two examples of categorical
data and two examples of numerical data
Please note we’ll use the bottom half for something else

20. What are the four “levels of measurement”?
Ratio
Absolute
zero
Most numeric
Categories
Intrinsic
ordering
Equal sized
intervals
Units
meaningful
Interval
Names
Categories
Intrinsic
ordering
Ordinal
Approaching
Numeric
Categories
Least
numeric
Names
Nominal
Weakest

21. What are the four “levels of measurement”?
Categorical data
Nominal data - classification, differences in kind, names of categories
Ordinal data - order, rankings, differences in degree
Numerical data
Interval data - measurable differences in amount, equal intervals
Ratio data - measurable differences in amount with a “true zero”
Gender - male or female
Family size
Jersey number
Place in a foot race (1st, 2nd, 3rd, etc)
Handedness - right handed or left handed

22. What are the four “levels of measurement”?
Categorical data
Nominal data - classification, differences in kind, names of categories
Ordinal data - order, rankings, differences in degree
Numerical data
Interval data - measurable differences in amount, equal intervals
Ratio data - measurable differences in amount with a “true zero”
Age
Hair color
Telephone number
Ethnic group
Breed of dog
Temperature
Yearly salary

23. Please note :
page 29 in text

25. What are the four “levels of measurement”?
Categorical data
Nominal data - classification, differences in kind, names of categories
Ordinal data - order, rankings, differences in degree
Numerical data
Interval data - measurable differences in amount, equal intervals
Ratio data - measurable differences in amount with a “true zero”
Look at your examples of qualitative and quantitative data.
Which levels of measurement are they?

26. Thank you!
See you next time!!