Male vs. Female Survey Respondents: As Different As X and Y

Male and female brains are dramatically different anatomically, chemically, hormonally, and physiologically.

Experts have discovered that there are actual differences in the way men’s and women’s brains are structured, genetically affecting the way they react to events and stimuli. Masters of Healthcare’s 10 Big Differences Between Men’s and Women’s Brains illustrates some of the variants which cause fundamentally diverse ways of thinking, feeling, and behaving.

When it comes to analyzing your survey results, responses based on gender can have a significant impact on your data.

Gender-Based Driving Differences

A recent TeleNav Driving Behavior survey suggests both genders have similar views on abiding by and breaking the rules of the road but have very different perceptions on which gender rules the road.

When asked which gender is the better driver, 40% of male respondents indicated they think males are the better drivers with 2% indicating females are the better drivers and 58% thought that gender plays no role in driving ability.

Female respondents had a very different opinion: 4% of women indicated males are the better drivers with 7% of female respondents indicating that women are better drivers and 90% of females thought that gender plays no role in driving ability

Distinctions in Male and Female Attorneys

A study by The New Jersey Supreme Court Committee on Women in the Courts, shows 54% of respondents indicated that attorneys are treated about the same, regardless of their gender.

Perceptions differ among respondents when they are compared by gender: The percentage of male respondents who perceive that attorneys are treated the same was 80%, almost double the perceptions of 43% of the female respondents

How Gender Impacts Survey Results

When compared, survey responses from men and women do vary and will affect your data accordingly. SurveyGizmo’s Survey Report Filtering Tool lets you filter certain responses from being displayed in reports, allowing new levels of survey data segmentation to help you gather the insights you need.

Using the filter tool when analyzing your data is an easy way to segment your survey results in order to outline the similarities and differences between the two similar, but fundamentally different, markets.

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  • J.S.

    Neither of these examples demonstrate a difference in brain chemistry, hormones, physiology, etc.

    The first question is the equivalent of asking employed versus unemployed people if unemployed people are lazy.  Since there is a stereotype already existing in our culture (women are poor drivers, and people who don’t have jobs are lazy), of course there is a difference in perception between the stereotyped group and the not-stereotyped group.

    The second is no better.  Ask an average weight and a severely obese person if people are treated different because of their weight.  The average-weight person might see some variability based on weight, but they don’t encounter weight prejudice daily.  Because of this, I would expect the severely obese group and the average weight group to have very different response percentages.
    Unless you are also arguing that the difference in responses between the employed/unemployed and the average weight/severely obese is due to a difference in brain anatomy, chemistry, and hormones, you can’t argue that the above questions demonstrate an equivalent brain difference between men and women.This is not to say that there is no such difference between men and women, but your selected examples are extraneous to this argument.

  • J.S.

    Neither of these examples demonstrate a difference in brain chemistry, hormones, physiology, etc.

    The first question is the equivalent of asking employed versus unemployed people if unemployed people are lazy.  Since there is a stereotype already existing in our culture (women are poor drivers, and people who don’t have jobs are lazy), of course there is a difference in perception between the stereotyped group and the not-stereotyped group.

    The second is no better.  Ask an average weight and a severely obese person if people are treated different because of their weight.  The average-weight person might see some variability based on weight, but they don’t encounter weight prejudice daily.  Because of this, I would expect the severely obese group and the average weight group to have very different response percentages.
    Unless you are also arguing that the difference in responses between the employed/unemployed and the average weight/severely obese is due to a difference in brain anatomy, chemistry, and hormones, you can’t argue that the above questions demonstrate an equivalent brain difference between men and women.This is not to say that there is no such difference between men and women, but your selected examples are extraneous to this argument.