1. HSB4M Culminating Activity
The Social Science Research Project – Part 2

2. Oh Yea, and How To Do It Right!

3. No, we would NEVER do that…..

4. Instead of taking all the bother and time to sample at all…..

5. Identifying BIAS in your SSRP
Do I Have To???? YEP!
There are many different types of sampling bias. Some examples include:
 Area Bias
 Self-Selection Bias
 Leading Question Bias
 Social Desirability Bias
Biased Sampling

6. Here’s an Example of a Sampling Technique
 We wanted to analyze San Diego ocean temperatures
 Our population was the ocean off the coast of San Diego.
 Our sample, was the temperatures recorded by Buoy100 over the last 9 years.
Here’s an Example of a Sampling Technique

7. How to Lie, Cheat, Manipulate and Mislead through Poor Sampling
If we were to claim that our results were representative of:
 California coastal waters
 Southern California coastal waters
 San Diego coastal waters
 Or even La Jolla coastal waters
Area Bias
That would be called
Biased Sampling
and we could use it to lie, cheat, etc……and therefore, mislead the public.

8. Self-Selection Bias For example:
If you were to set up a booth to ask people about their grooming habits…
The people who respond are more likely to be those who take more time to primp in the morning than those who just throw on something and head out the door.
In Self-Selection Bias, a participants' decision to participate may be correlated with traits that affect the study, making the participants a non-representative sample.
Self-Selection Bias

9. Leading Question Bias If you have a survey that asks:
“Don’t you think that university students are paid too little?”
A)Yes they should earn more
B)No they should not earn more
C)No opinion
You are suggesting by the tone of the question what you believe the answer should be. That will bias your results (is it always bad?)

10. Social Desirability Bias
If you ask people in a survey about how often they shower, or how often they recycle, your data is going to be biased by the fact that nobody wants to admit to doing something that is considered socially undesirable.
Social Desirability Bias

11. Validity means precision in measuring exactly what one intends to measure.
HOW?
Make the questions unbiased…do not lead the person in the study
Make the questions as close to real-life as possible
Make sure the questions measure what you want them to measure.
Scientific Validity

12. Scientific Reliability
Reliability: extent to which a measure produces consistent results. Can the experiment be reproduced and produce the same results?
HOW?
Sample: selection from a larger population that is statistically representative of that population
Random sample: when every member of an entire population has the same chance of being selected
Scientific Reliability

13. Data analysis is a process of gathering, modeling, and transforming data with the goal of highlighting useful information, suggesting conclusions, and supporting decision making.
Analyzing Data

14. What if you were a real-estate agent and you were trying to convince people to move into a particular neighbourhood.
You could, with perfect honesty and “truthfulness” tell different people that the average income in the neighbourhood is:
a)$150,000
b)$35,000
c)$10,000
Manipulating Data

15. How? You would ask.
This particular neighborhood is lucky enough to be near a cliff… and the ONE home with an ocean view is a giant mansion on 50 acres that is owned by a Hollywood Star. With gates. And spikes. And security to keep out the riff raff of the rest of the neighbourhood of poor people and the few middle class that live nearby.
The $150,000 figure is the arithmetic mean of the incomes of all the families in the neighborhood.
The $35,000 figure is the median.
The $10,000 figure is the mode.

16. Explain Please….

17. What Are They? Mean (what we usually call the average)
Sum of values divided by the number of values
$150,000
Mode
Number that is repeated the most often
$10,000
Median
Middle Value
Write all the numbers down and pick number in the middle
$35,000
What Are They?

18. Credits