Drout Advertising
By: Damon Roberts
Tags: Data Science, Excel

Study of Advertisements Reinforcing Gender Stereotypes

Comparing the data between figures 2 and 3, we can see some expected trends. Younger respondents tend to have completed less education than older respondents. They also tend to earn less on average than older respondents. This can be due to a combination between less education completed and less time to build a higher-paying career. Figure 4 (below) also shows a correlation between age and amount spent on products annually. Similar to the trends shown in previous figures, younger respondents tend to spend less on products, possibly due to lower income available for beauty and hygiene products.

Table 3: Ad Perceptions by Gender and Age

Table 3 (above) shows the average number of ads for beauty or hygienic products respondents view or hear on a daily basis. It also displays the number of ads respondents feel subscribe to traditional gender-specific stereotypes. The youngest and oldest age groups reported experiencing the highest number of ads daily, around 53 and 59, respectively. Among those ads, respondents in the 19–28 group felt approximately 95% subscribed to traditional gender stereotypes, which was consistent with the average of the overall study as well. Respondents aged 29–48 felt 97–99% of ads they experienced also subscribed to stereotypes. The 49–58 group differed slightly from the other respondents in estimating the ratio was around 87.5%.

Interestingly, the 19–28 age group felt 6–6.5% of ads they viewed also utilized empowerment advertising in their products. The remaining respondents felt this number was only around 2%, suggesting a difference in perspective between generations of consumers. The Millennial base are individuals who were born between 1981 and 1997, making them around 20–30 years old for this study. Millennials are known for activism and promoting equality among groups, especially genders. The data from this study suggests Millennials may be more perceptive of messages of empowerment in advertising than the older groups.

Below, Table 4 shows the results from the question “To what extent do you agree that empowerment advertising, which explicitly communicates the unique differences in each individual, would help transform cultural gender stereotypes?” Overall, responses trended towards Strongly Agree or Somewhat Agree, with some differences between age groups. Younger respondents aged 19–28 felt they more strongly agreed with the idea of empowerment advertising helping to transform cultural stereotypes. Responses continued towards a more neutral response as the age of respondents increased. Of the respondents aged 49–58, 50% responded with Agree. No respondents indicated they Strongly Disagreed with the idea of empowerment advertising, and only one respondent indicated she Somewhat Disagreed.

Table 4: “To what extent do you agree that empowerment advertising, which explicitly communicates the unique differences in each individual, would help transform cultural gender stereotypes?”

The following charts break down the responses to questions regarding how much of a role advertising plays in reinforcing and transforming gender stereotypes. Participants were asked to rank the role advertisements play in reinforcing gender stereotypes; options available were “Drastic; Influential; Limited; Trivial; None”, from more to least intensity. 59% of respondents felt ads have an influential effect on reinforcing stereotypes, while another 33% felt ads have a more drastic influence. The remaining 8% of respondents felt ads have a limited or trivial role.

Participants were also asked how strongly they agree that empowerment advertising will help transform cultural gender stereotypes. Responses ranging from “Strongly Agree” to “Strongly Disagree” were collected, resulting in the distribution below. 30% of respondents strongly agree with the message, while 33% felt they agree somewhat. Another 29% felt they agree, although not as strongly as the other 63% of responses in agreement. 2% of responses disagreed with the message, while the remaining 6% felt neutral about empowerment advertising transforming gender stereotypes.

We can separate the qualitative and quantitative data into two groups for further analysis. The quantitative data includes Age, Annual Spending, Ad Frequency, Ads Enforcing Stereotypes, and Ads Encouraging Empowerment. The average reported age was around 29 years old, with a standard deviation of 11.8. Constructing a 95% confidence interval from this data, we can say there’s a 95% chance the average age of the entire population of interest is between 26.98 and 31.55. From 2018 census information, we know the median age in the USA was around 37.9. While this value is far outside even a 90% confidence interval (26.2, 32.3), the population of interest does not include all Americans as not everyone has a relationship with beauty product advertising.

The average amount spent on beauty products by participants to this survey was around $650. Constructing another 95% confidence interval from this sample, we can be reasonably certain the average spent by the population of interest will fall between $493.85 and $806. This is a relatively large range, especially considering the standard deviation of this sample was over $806 alone. We also know outliers exist from previous analysis. Therefore, it’s recommended to increase the sample size to at least 250 respondents before making meaningful claims about the average amount spent on products. This should provide a margin of error no greater than ±$100 from the sample mean.

Moving to ad frequency, we can claim with 95% confidence that the average number of ads seen by the general population is somewhere between 20.4 and 70.6. The average number of those ads which reinforce gender stereotypes should be within the range of 19.2 to 67.5. This is another instance of a large range of potential values, which again suggests an increased sample size should be used. Using a sample size of at least 266 respondents should decrease the margin of error from ±24 to ±15, providing a more accurate estimate. Finally, of the ads respondents reported viewing, an average of 5.4% supported a message of empowerment to break gender roles. Creating a confidence interval from the sample, we’re 95% confident the population average will fall between 4.2% and 6.6%.

Next, we’ll look at the qualitative data, which includes Gender, Level of Education Completed, Role in Reinforcing Stereotypes, and Agreement in how Empowerment Advertising Transforms Stereotypes. We can determine from the data that about 18.1% of respondents reported their gender as male, while the other 81.9% reported female. Building a confidence interval, we can say with 95% confidence that somewhere between 10.7% and 25.5% of the population of interest will identify as male. Conversely, we’re 95% confident women make up 74.5% to 89.3% of the population. While a margin of error of ±9.7% isn’t too drastic, a larger sample size of at least 230 would be preferable to bring it under ±5%.

41.9% of respondents to this survey reported a Bachelor Degree as their highest education completed. Creating a 95% confidence interval results in a margin of error of ±68.4%. This allows us to claim with 95% confidence that between 32.5% and 51.3% of the population has completed a bachelor degree as their highest level of education. Increasing the sample size to at least 375 would reduce the error to less than ±5% at 95% confidence. This should also address accuracy concerns for other data as mentioned above, reducing the error for each item to a reasonable value.

From the collected data, 33.3% of respondents felt advertisements have a drastic effect on reinforcing gender stereotypes. Assuming 95% confidence, we can assume between 24.3% and 42.6% of the population feel the same way. 59% of respondents felt advertising is influential, but not as drastically, in reinforcing these roles. Constructing another 95% confidence interval suggests 49.6% to 68.5% of the population will also fall into this category. 92.4% of respondents to this survey expressed some agreement that empowerment advertising will shape cultural gender stereotypes. At 95% confidence, we can assume between 87% and 97% of the population of interest agree with the idea as well.