1. Basic Statistics
Vernon E. Reyes

2. Topics What is statistics in relation to social science research?
Organizing data
Measures of central tendency
Measures of variability
Probability, samples and population
Testing differences between means
ANOVA
Chi-Square
Correlation
Spearmans ro

3. Social Science Research
Social science = study of the obvious?
Thus there is a need to test hypotheses
Example: Mass Murderers
*which of the following are obvious and therefore not worth studying?

4. Mass murderers?
Mass murderers are almost ALWAYS insane (a person who is sane will never kill people who are having lunch)
Mass murderers are usually strangers to their victims who are unlucky enough to be at the wrong place and at the wrong time
Mass murderers typically run amok, expressing themselves in a spontaneous outpouring of anger
Mass murderers look different from the rest of us

5. However… 697 mass killers from 1976 – 1995
Mass murderers are rarely insane, they know what they are doing and NOT because “voices of demons”
Random shootings in public places are rare, most killings happen within families or acquiantances
Most murderers are methodical and selctive NOT impulsive or spontaneous
Murderers do not look different, they look just ordinary people

6. Social science research
Social scientists attempt to explain and predict human behavior
In the process, soc. Scientists examine characteristics of human behaviors called variables – characteristics that differ from one individual to another (i.e. age, social class, attitude) or from one point in time to another (i.e. unemployment, crime, population).
Constant: gender of mothers
Variable: age, race, mental health of mothers

7. Are there different variables?
Independent variable/s (IV)
- This is the one presumed to cause the changes in the DV
Dependent variable/s (DV)
This is one presumed to to change or be the effect because of your IV.
Give your own examples…

8. Series of numbers for social science research
Series of numbers have a level of measurement.
1. Classify or categorize = nominal level of measurement
2. Rank or order = ordinal levels of measurement
3. Assign a score = interval level (no true value of zero, i.e. temperature) or ratio (has an absolute zero i.e. weight, height, etc) of measurement

9. NOMINAL LEVEL
Involves naming or labeling, meaning we place cases into categories and count frequency
Examples: gender (male, female), political party (Lakas, Liberal, Nacionalista), time (past, present, future) etc

10. Notes for nominal data
Every case must be placed in one, and only 1, category = categories must not be overlapping or mutually exclusive
Must be exhaustive = a place for every case that arises
Nominal data are not graded, ranked or scaled… i.e. better or worse, higher or lower, more or less

11. Ordinal Level Degree of ranking
Example: instead of just categorizing nationalists versus not nationalist, we might want to study the degree of nationalism
Not a measure of magnitude. i.e. we do not know how nationalist one respondent from another.
Example, beauty contests

12. Interval/Ratio level
Not only shows order but also exact distance of one score to another.
Uses constant units of measurements (pesos, celsius, yards, feet, minutes) and yield equal intervals

13. What is what?!
There is clear distinction between nominal data and ordinal data
Example:
color of hair [black, brown, blonde] (nominal) vs
condition of hair [dry, normal, oily] (ordinal)
Distinction between ordinal and interval is not always clear cut

14. Attitude toward professor
Scale value
Rank of professor
Attitude toward professor 1
University professor
Very favorable 2
Full professor
Favorable 3
Assoc. professor
Somewhat favorable 4
Asst. Professor
Neutral 5
Instructor
Somewhat unfavorable 6
Lecturer
Unfavorable 7
Teaching asst.
Very unfavorable

15. From the previous table
Difference between instructor and lecturer is minimal in terms of prestige, salary or qualifications
The difference between instructor and asst. professor is substantial wherein there should be at least a doctorate and higher salary
Attitude is evenly spaced
ie strongly agree – strongly diagree
 instead, whenever possible, we treat ordinal variables as interval ONLY if safe to assume that the scale has relatively equal intervals!
Attitude = interval and Rank of Prof = ordinal only!

16. Functions of Statistics
Description
Decision making / inferences