1. Sex and Gender Differences What are they?
PSY 345
Dr. Blakemore

2. Kinds of Bias or at least perspective
The idea that sex differences are large and important is sometimes called an alpha bias
The idea that they are small and insignificant is alternatively called a beta bias
You should just be aware that there are people on both sides of this issue
Our textbook author, Janet Hyde, is one of the most prominent scholars in the world on the “small and insignificant” side of the debate

3. What is a sex or gender difference?
What does it mean to say there is a gender difference in some attribute or behavior?
Like men are taller than women. . .
It is an average difference
Much overlap

4. Normal Distribution
When a large number of participants are measured on some trait or characteristic, the scores are often normally distributed.
A normal distribution of scores means that most of the scores cluster around the mean, and the farther one gets away from the mean, either higher than it or lower than it, the fewer scores there are.
Normal distributions are also symmetrical, that is there are the same number of people scoring at various points above and below the mean.
A good example of a normally distributed characteristic that shows a sex difference is height.

6. Males and Females
On many characteristics, the distributions of male and female scores overlap, and are normally distributed
For example, in the case of height

9. Cohen’s d statistic
Essentially d is a measure of the standardized effect size, or a measure of how far group means are apart in standard deviation units.
In sex and gender differences research there is a common convention that the female mean is subtracted from the male mean, so if males score higher d is positive, and if females score higher d is negative (not everyone does this, though)
How big is a big effect size?
d of .20 is small
d of .50 is moderate
d of .80 is large
The d statistic is very important in sex/gender differences

10. Reviewing a body of research
Before the 1970s, and sometimes still today, when psychologists summarized the findings in an area of sex differences research, they did so with a qualitative or narrative review.
in the late 1970s a new technique was developed called meta-analysis
Meta-analysis is often called a quantitative review
Meta-analysis is a statistical technique that permits a researcher to combine the results of many studies statistically

11. Meta-analysis, cont’d
The major strength of meta-analysis is that is allows for a way to statistically analyze several studies at the same time
Because meta-analysis uses effect sizes, it allows for much clearer information about how large a difference is likely to be
And when it’s smaller and when it’s bigger

12. Gender Differences
Look in the book for some examples of gender differences like activity level, empathy, helping behavior, etc.