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Innovate Birmingham Cohort 10 Data - Final Presentation
- 1. In the event of technical issues
- 2. It all starts Day 1 Tech and Soft Skills Development
- 3. Class Research Project Cohort 10 - ThinkData Analytics Bootcamp
- 4. Hours of work cleaning & analyzing to produce findings
- 5. Microsoft PowerBI Desktop Tableau Public
- 6. NOUN difference in size, degree, circumstances, etc.; lack of equality. RACE|GENDER|AGE
- 7. In my experience the differences in wages are directly related to knowledge in the field and commitment to progress. I find it very hard to believe that there's a significant difference in males vs females compensation. I don't think gender is the actual issue in 2020 Opportunity is where you look. People need to look harder for it. Pay is not based on any of these Knowing salaries of people who have worked for me, I can say that neither race nor gender play a role at all. Actual responses from respondents who disagree with inequality and shared their feedback.
- 8. I see more inequality in opportunities based on gender more than any other bias. In my previous employer, all of these were an issue. This is one of the great issues within the US Males make more than females in my profession at my work. It’s not always about pay. Discrimination also happened with mobility. Actual responses from respondents who agree with inequality and shared their feedback.
- 9. Let's meet Data Cohort 10
- 10. Demographics Overview of who are the respondents to the survey
- 11. Education Education levels and various information on the respondents
- 12. Inequality Research Wage and Promotion Inequality
- 13. Inequality Research Seniority Levels, Promotions, and Inequality Questions
- 14. Inequality Research Inequality Questions: Demographics and Education
- 15. Review & Support – All Teams Steve Rucinski, Sheldon Winks & Erik Giddens
- 16. Wage Comparison Study Cohort 10 - ThinkData Analytics Bootcamp
- 17. Demographics Locations, Age, Gender, Industry, Education, Salary and Benefits
- 18. Claudia Powell Data Cleaner for Demographics Mapping Visualizations in Power BI and Tableau
- 19. 315 Total Valid Responses from 20 States and DC
- 20. Valid responses include: VALID WORKPLACE LOCATION POSTAL CODES 3 ANSWERED INEQUALITY QUESTIONS
- 22. Brian Boyd Data Visualizations in Power BI
- 26. Aaron Barnes Data Visualizations in Power BI
- 27. What is your current industry and what type of business do you work for?
- 28. How do you classify your current employment?
- 30. Parker Morrow Analyzed respondents' compensation data utilizing Power BI
- 31. Source for Alabama Median Income: https://www.census.gov/quickfacts/fact/table/AL/PST045219# Source for United States Median Income: https://www.census.gov/library/stories/2019/09/us-median-household-income-not-significantly-different-from-2017.html
- 32. 145 39 106
- 36. Education Age, Race or Ethnicity, Gender, Salary, Promotions, and Years in Current Role as it relates to Education
- 37. Fatimah McCarther Data Visualizations in Power BI
- 38. Degree Persona Degree and Non Degree
- 40. Ian Griffin Analyzed respondents education level with data visualizations from Power BI
- 41. Education by Age
- 42. Age and Degrees
- 43. Jerrett Gunn Comparing salaries by Education using the data we received from our survey utilizing Power BI visualizations.
- 47. Joe Hill Data Visualizations in Power Bi
- 48. Salary Pattern of Three Highest Respondent Subgroups Greatest number of response are in this salary range 40k – 59,999 annually
- 49. Patterns of Salary by Race WHITE SUBGROUP BLACK SUBGROUP HISPANIC SUBGROUP
- 50. Subgroup Salary Calculation for Bachelor's and Master's Degree Holders. WHITE BLACK HISPANIC
- 51. Jeff Rose Data Cleaner Data Visualizations in Power Bi
- 55. Never been promoted • Filtered by never been promoted by racial subgroup • Then crossed with time in current role
- 56. Inequality Research Wage and Promotion Inequality
- 57. Joseph Chatman Inequality Study Promotions by Demographics
- 61. Bianka Jimenez Data Cleaner for all Inequality teams Data visualizations in Power Bi
- 63. 64% of female respondents earn in mid-range salaries. MALE FEMALE Salary Range Percentage
- 64. Industry vs Wage Fairness
- 65. Violeta Sanchez Yañez Promotion Fairness
- 66. Education Level and Years of Industry Experience: Effect on Promotion
- 67. Non-DegreeDegree 45% of both degree and non-degree holding respondents with 10+ years of industry experience have been promoted at least once
- 68. "Do you Feel that Promotion Decisions are Fair at your Company?" Degree, Never Promoted NonDegree, Never Promoted
- 69. Degree, Promoted at least Once NonDegree, Promoted at least Once
- 70. Inequality Research Seniority Levels, Promotions, and Inequality Questions
- 71. Michele Patrick Power Query Transformation Data visualization in Power BI
- 72. Seniority Level Comparisons Mid-Level Positions 34% Females 13% Males
- 76. Wade Kwon Data visualization in Power BI
- 77. Who’s been promoted? Full-timers.
- 78. There is inequality in wage based on ____. AGE GENDER RACE AGREE DISAGREE AGREE DISAGREE AGREE DISAGREE
- 79. There is inequality in wage based on … Age. … Gender. … Race. *CUMULATIVE AGE GENDER RACE
- 80. There is inequality in wage based on race. PEOPLE OF COLOR WHITE BLACK Native American or Alaska Native
- 81. AGREE AGE GENDER RACE DISAGREE I feel that my compensation is fair, relative to similar roles at my company. Inequality in wage based on: AGREE DISAGREE AGREE DISAGREE AGREE DISAGREE
- 82. AGREE AGE GENDER RACE DISAGREE I feel that my job performance is evaluated fairly. Inequality in wage based on: AGREE DISAGREE AGREE DISAGREE AGREE DISAGREE
- 83. Inequality Research Inequality Questions: Demographics and Education
- 84. Sam Sorrell Power Query in Excel Data Visualization in Tableau
- 90. Scott Lontine Power Query in Excel Data Visualization in Tableau
- 91. Is there Wage Inequality based on Age, Gender, or Race? DEGREE RESPONDENTS DISAGREE that there is wage inequality based on AGE, GENDER, or RACE. NON DEGREE RESPONDENTS DISAGREE that there is wage inequality based on AGE and RACE EVEN in their agreement/disagreement responses for GENDER.
- 92. DEGREE PERSONA RESPONSE TO THREE WAGE INEQUALITY QUESTIONS
- 93. The Non Degree Persona responses to all three wage inequality questions. NON DEGREE PERSONA RESPONSE TO THREE WAGE INEQUALITY QUESTIONS.
- 94. DEGREE AND NON DEGREE PERSONAS: BLACK OR AFRICAN AMERICAN AND WHITE
- 95. DEGREE AND NON DEGREE PERSONAS: BLACK OR AFRICAN AMERICAN AND WHITE
- 96. FEMALE response to inequality based on GENDER: • DEGREE FEMALES were ALMOST EQUAL in AGREEMENT/DISAGREEMENT • NON DEGREE FEMALES have a 16% difference in AGREEMENT/DISAGREEMENT • Could the attainment of a DEGREE eliminate the GENDER bias in wage levels?
- 97. MALE response to inequality based on GENDER: • DEGREE and NON DEGREE MALES responded OVERWHELMINGLY in DISAGREEMENT • Both responded STRONGLY DISAGREE as majority sentiment level • DEGREE MALES responded 2:1 in DISAGREEMENT/AGREEMENT • NON DEGREE MALES have a 17% difference in DISAGREEMENT/AGREEMENT
- 98. Thank You DATA ANALYTICS BOOTCAMP COHORT 10
Editor's Notes
- We are using one slide deck for the presentations today. In the event we experience any difficulty we have Adrian Drane and Taylor Abney on standpoint to jump in to the presentation and take over. Let's hope it doesn't happen, but in the event just know we are prepared to quickly make the transition.
- They start their new paths with tech and soft skills development starts on day 1 and quickly learn in the field of tech that skills development never stops.
- Every cohort we as a group develop a class research project. This allows candidates to truly experience a data research project from ground up. They work to determine what they want to study, they develop initial questions and then develop them into survey questions with responses. This study is then published via our social channels.
- They also figure out that no ones sees the hours of work cleaning, mining, analyzing not only to determine the findings, but then to produce a result that is digestible to all audiences.
- You will see a battery of skills from the development of talking points, modifying slides and using not only tools like powerquery, but also viz tools like PowerBI Desktop and Tableau Public. While discuss a very important subject of Next Slide – Inequality.
- Our survey was presented to measure not only the sentiments on inequality but also if they could find inequality within our sample. We asked a lot of important questions that again were developed by a team of very motivated newly trained analysts. There is more information here that we need more time, more sample and more than 30 minutes to dive into, but enough from me.
- Actual responses from respondents that we may want to intersperse in the inequality section
- Let me introduce our teams who have not only survived starting in person, moving to remote and editing a slide deck over close to 100 slides and 20 different and unique perspectives. I can not be more proud of what you will see today.
- Parker, Claudia, Brian and Aaron will give us an overview of who are the respondents to the survey
- Joe , Jeff , Fatimah , Jerrett and Ian Education levels and various salary and promotion information on the respondents
- Inequality is broken up into three research teams, First team - Joseph Violeta and Bianka will discuss findings on Wage and Promotion Inequality
- Second team Michele and Wade will discuss Seniority Levels, Promotions, and inequality questions
- Third and final presenting team Sam and Scott will address Inequality Questions Demographics and Education
- I would like specifically acknowledge our review team Steve, Sheldon and Erik who have focused on ensuring accuracy and consistency when combining the thoughts and slides of 20 individuals and leadership. With them presenting members could focus on the talking points, the visuals and know they were being covered by a group of committed individuals to cross check all their work. This not only requires a critical eye and thoughtfulness but an immense amount of patience.
- Enough from me. Let's get started with our review and findings of the Cohort 10 Wage comparison study.
- My name is Claudia Powell and I am a candidate in Innovate Birmingham's Data Analytics Bootcamp . My fellow candidates in Cohort 10 developed a wage comparison survey to learn real-world skills in data analysis and we would like to share our findings with you.
- We had 315 total valid responses to our survey. Respondents from 20 states participated.
- A valid response provided an authentic workplace postal code and answered the three inequality questions, Is there Inequality in wage based on Age, Is there Inequality in wage based on Race or Ethnicity, and Is there Inequality in wage based on Gender?
- Of those, 74% responses were from Alabama and 72% in Jefferson County. Now Brian is going to share some information about our respondents.
- Thank you Claudia, Hello my name is Brian Boyd, and I will be presenting the Gender, Age, Race, and Education portion of the demographics. Let’s look at WHO took our survey: We had a heavy Female to Male ratio, with nearly twice as many Female than Males respondents. Over 41% of those Females belonged to the 25-34 Age Range. While Male’s had a higher percentage than Females in Age Ranges 35-44 and up. Next Slide Please
- The Race/Ethnicity of our respondents comes next White, Black/African American, and Hispanic/Latino made up 95% our total. With a majority of our respondents being White with a little over 66% To give some Race to Gender info: There were exactly three times as many Black/African American Females than Males There were over twice as many Hispanic/Latino Females than Males There were about 1.6 times as many White Females than Males. Next Slide Please
- Lastly for education: A total of 72% of our respondents have some sort of degree. With Bachelor’s Degrees making up almost half of those. They go on to answer to a few types of businesses and a multitude of industries Now I will pass it along to Aaron to share this with you
- SPEAKER NOTES – GO HERE Here you will see we received responses from 28 distinct industries with our three biggest pools being in Heathcare, Education and Financial Services Our data also showed us that the majority of respondents come from for-profit businesses. With this level of diversity we can help to eliminate potential bias we could face if we were to target just one single industry
- From there we asked how our respondents considered their current positions in which over eighty percent responded as full time workers i then broke down the three main responses by gender to see potential diversity This shows us how the respondents are employed and if this could influence the later questions like a self employed respondent answering about the benefits they have *Next
- lastly we looked into their total experience in their field coupled with the time they have been employed in their current position the majority of our responses had ten years or more experience however time in their position had a majority for one to five years this allows us to see if the respondents have given time for their position to be established and have the experience in their field to make reasonable judgements in their response to our questions. With that i will now hand it off to parker to share compensation data from our survey
- The majority of our respondents had salaries above the state median but below the national median.
- For both men and women, the highest number of our respondents were mid-level employees and the fewest were in the C-suite.
- The highest number of both our male and female respondents had never received a promotion.
- The highest number of our female respondents had never received a bonus, while the highest number of our male respondents had received a bonus in the last twelve months.
- The vast majority of our respondents received some form of basic health insurance, with over 75% receiving health, dental, and vision. However, far fewer received family benefits of some sort. The majority received paid time off, but only a minority received family benefits apart from that.
- My name is Fatimah McCarther.
- I will be sharing the data collected from degree/non degreed personas and gender. Degree personas are respondents with an associate degree or higher. Non degreed persona respondents have a high school diploma/ged, some college or technical/ vocational school.
- Females represent approx. 67% of the grand total, 48% of that being degreed females. The males represent 33% of the grand total with approx. 22% of that number being degreed males. Next we will hear from my colleague Ian Griffin who will discuss degree/non degree personas and age...
- Hello, My name is Ian Griffin, and I am the youngest member of Cohort 10. I was given the task of finding the percentage of respondents by their different degree types and personas, as you can see here the respondents all have a diverse amount of different education levels, but I would like to focus strictly on 2 different subgroups the 25-34 year olds and the 18-24 year olds in our age brackets, the 25-34 year old age bracket had the highest amount of respondents and the most interesting being over 30% of our respondents with a degree had a master’s degree, and none of the 18-24 year old age bracket has a master’s degree, on the next slide
- We will see another very interesting point, in the 55-64 year old age bracket just under 85% of our respondents having degrees, and the same can be seen in the 25-34 year old respondents where just under 75% of them have a degree, thank you for listening attending, let me pass it off to my collegue Jerrett Gunn
- (slide 2) First we will look at the over all salary for all respondents and here we can see that the most common salary for all age ranges except respondents 55 and older is $40,000 to $59,999 a year
- As we break this view down into or main majority age range you can see that the overall common salary for this age range is still $40,000 to $59,999 and a large amount that makes up that salary range are respondents with a degree
- Here we see a side by side salary comparrison of Degree and Non-Degree Respondents. Here we can see thing like the most common salary for Respondents without a degree is $20,000 to $39,999 a year. Resondents Without a Degree Where %14 more likely to make $19,999 a year or less. Respondents with a degree had a significantly higher chance of making $60,000 a year or more
- Using a treemap I wanted to show the income Pattern of top three sub-groups based on response count which is white, black or African American and Hispanic so we could see a visual of income across subgroups. Please note in the lighter blue that salaries in the amount of 40 – 59999 by far had the greatest number of responses. In order to determine if there is a difference. I broke this pattern out further by each individual subgroup.
- The numbers comparable with national statistics. (according to what? Cite a reference on this slide or take out). But just a few things to point out, first off 40k range is the lighter blue, and in all three subgroups. The dark blue the 60k range is in the 2nd position because it was the second highest response count for the white subgroup, it came in 3rd for the black and African American subgroup, and tied for third in the Hispanic subgroup. Note the orange which is the majority of the Hispanic subgroup who responded to our survey is in the 20K salary range, which is third for the white sub group, 2nd for the black or African American subgroup. In order to dig deeper in the pattern, I looked at education through a degree filter.
- This Education breakdown by race shows only bachelor and master degrees, and the salaries on the right show % of that subgroup in their salary range. We see similar pay at mid to lower level salaries. We start to see a gap at higher income levels.
- Hello my name is Jeff Rose I was task with cleaning the gathered survey data for the education group and helped with setting up group meetings via Zoom and Teams. I will be comparing Promotions and Years in Current Role. With this comparison many questions arise. I want to highlight our overall survey data indicates most of the respondents have never been promoted and have been in their current role 1 to 5 yrs, we will come back to this observation.
- Like others, I have focused on the 3 most responding race or ethnicity subgroups, and also considered their Degree and Non-Degree Personas. If you look at the dark blue across the bottom this 53% white, 38% black or African American, 26% Hispanic or Latino respondents have never been promoted. Our Hispanic subgroup sample was small but worth noting that 48% of this subgroup have stated they have been promoted in the last 12 months.
- In considering what impacts promotion I decided to look at the years in current role. You’d expect someone to not be promoted in their first year typically. If you look at the purple bar you notice the majority of each subgroup, 47% of white, 51% of black or African American and 35% of Hispanic or Latino respondents have been in their current role for 1 to 5 years. Again, most respondents have been in their roles for 1 to 5 years.
- In an effort to compare promotion to years in role, I created a side by side comparison focusing on the 'Never been Promoted' in blue, located left and in their current role for 1 to 5 Years' in purple, the right.
- Since most of the respondents have never been promoted and have been in current role for 1 to 5 years , this lead to a deeper breakdown of years in current role filtered by never been promoted. I found that 41% of white, 64% of black or African American and 17% of Hispanic or Latino respondents have never been promoted in the 1 to 5 years in current role range.
- Finished and ready for final review
- [Joseph] Lets start at the bottom. This chart shows the respondents experience as it flows from years of experience by age range. Starting at left in the less than a year of experience category we found that 18 -24 years old they are the yellow band. Most of our 25 to 34 have one to ten years of experience which is easy to see by the light purple bands in the middle of the flow. And as expected 35 to 44, and 45-54 year olds represent the most experienced with ten years or more which is the purple band. As you heard Brian speak to earlier that 25-34 year olds make up the majority of our respondents, and if you look at the top chart, you will note that the 25 to 34 year old age range make up make up 40% of the non promoted respondents and a many have been promoted at least once, and in some cases more than once.
- I then looked at that age group when it comes Down experience by gender .We see that female respondents make up 60% of respondents with 10 years or more of experience and over 70% of all respondents with 5 years or more of experience which made me want to drill down into what promotions these experienced workers received by gender
- I wanted a side by side look Out of the 307 total female respondents, over 80% of them have actually received a promotion while about 50% of males have never been promoted.. with women being the only respondents with more than one promotion in 5 years. Based on these results we can see the 25-34 age group respondents have either never been promoted or have just received a promotion recently I’ll now turn it over to Bianca
- Good Afternoon, my name is Bianka Jimenez and I will be sharing a glimpse of industry representation of gender.
- Top 7 industries with representation from both male being the green and female respondents being in the blue, note that most of these industries are female dominant. *** As we all know in the tech industry – even with a higher number of female responses one industry was clearly dominated by male response. Note the male which is green in Information Technology. *** Since most of the respondents in the survey were females, the results show one story. Further research will be needed.
- Respondents who selected healthcare and pharmaceuticals as their industry, 76% were Female, 22% were Male. In this industry all genders - 43% responded that their salaries were in the 40k range., when looking at just the women who responded 64% of are in that range. 64% of the female respondents said to earn in the mid-range salaries, yet they felt fairly compensated.
- When asked if they felt there was wage inequality by gender in this industry, 95% of the female respondents stated they agreed, while only 5% of the male respondents also agreed. The question of why arises, and not just in this industry. Here is Violeta to give you more insight.
- Hello everyone, my name is Violeta Sanchez Yanez and I want to know if education level or years of experience affect promotion. And How do our respondents feel about the fairness of promotion decisions made in their company?
- We've heard a lot about promotions today and I wanted to take a different approach by dividing it into those never promoted or those promoted at least once. A majority of our respondents would be considered the highest qualified on paper. They have degrees and more than ten years experience. I found it interesting that in both sets of graphs, those deemed "highest qualified" have almost the same percentage between those promoted and not promoted.
- In this slide each pie chart shows the respondent's current industry experience. They are separated by Degreed on the left and Non Degree on the right. 45% of both degree and non-degree holding respondents with 10+ years of industry experience have been promoted at least once in their company. **I think it is worth noting that across these visuals there is really not a lot of dramatic differences when combining these three factors***
- We asked respondents, "Do you feel that promotion decisions are fair in your company?" Most (27%) respondents with a degree and ten plus years of experience either disagree that their wage is fair, or they don't have an opinion about it. Non-degree respondents with the same experience, however, mostly agree that their promotions have been fair despite never being promoted.
- In this slide, you can see that NonDegree and Degree respondents with ten plus years of experience are more likely to agree that promotions are fair IF they have been promoted at least once. Based on this data, it seems that neither degree nor experience in industry makes a huge difference in promotions. Nuances to consider when further evaluating how and WHY respondents feel about promotion fairness include time with the company, the Position level, and compensation. Even though they may not have had one promotion in the last five plus years, they may have gotten a raise. That concludes our presentation. Thank you for listening. I will now turn you over to our next team.
- Hello, my name is Michele Patrick. I wanted to take a look at whether there was inequality based on Seniority Levels.
- We asked our respondents to classify their current position which ranged from Entry Level to the C-Suite executives. As you can see from the chart, Mid-Level seniority group yields the highest number of responses. Of those responses, female respondents make up 34% of the subgroup while male respondents equate to a little over 13%. Next Slide
- *Mid-Level and Race Demographics With a high percentage of our respondents being either Black, White, Hispanic or Latino, I wanted to view the salary ranges across these three subgroups. What we see is that white respondents equate to over 75% of the grand total of our Mid Level subgroup. Looking at the two largest blue colummns 44% of that total report in the 40,000 to 79,000 range, while only 12% of black respondents report the same salary range as you can see in the purple. Next Slide
- Lets take a look at how just our Mid-Level Male respondents vary across race demographics Here we see that white male respondents make up a little over 82% of the total for salary ranges with 57% of those reporting between $60,000 to 150,000, while a mere 14% of our Mid-Level Black male respondents report between 19,999- 59,000 salary range. No Mid-level black males reported making 60,000 or even in the 100,000 or more pay range. Next Slide
- In comparison, 73% of our white female Mid-Level respondents make up the this subgroup with 51% of those reporting within the 40,000- 79,000 range Only 24% of our black female Mid-Level respondents reported, with a little over 16% of those falling within in the same 40,000- 79,000 pay scale. Based on this data from our respondents, we see that a wage gap does exist but the reason as to why is yet to determined. Thank You I will now past it to Wade to discuss his findings on age, gender and race inequality personas
- [WADE] Full-time workers make up the overwhelming majority of our respondents, as seen in the left column. Of those, a little more than half have earned promotions in their current job, as seen in the top three sections of the full-time column.
- [WADE] We asked our participants if they agreed with three statements: There is inequality in wage based on Age, based on Gender and based on Race. In looking at each of the three statements, the biggest gap between respondents who agreed and disagreed is in the bottom rows for Race. 40 percent agreed, while 60 percent disagreed.
- [WADE] Overall, 452 respondents – 56 percent – did not think there is inequality in wage based on any of those three categories. This is a cumulative total.
- [WADE] Our participants were asked if they agree with this statement: There is inequality in wage based on race. The left column shows that 40 percent agreed with the statement, while the right column shows 60 percent thought there was no inequality in wage based on race. Looking at the yellow sections atop both columns, we see a nearly 2-to-1 ratio between white respondents who disagree vs. those who agree. Looking at the two green sections at the bottom of the columns, we see the reverse with black respondents: a 2-to-1 ratio between agree and disagree.
- [WADE] Again, we see how our respondents felt about inequality in wage based on our 3 categories. We also asked whether respondents agreed with this statement: I feel my compensation is fair. Once again, we see that a huge majority agreed with that statement – shown in the blue bars – and only a few found that their compensation was not fair – shown in the green bars. The two main sentiments: Typically respondents felt there was no wage inequality based on demographics, and that they were being paid fairly.
- [WADE] Let’s look at how respondents feel about their job performance. We asked whether respondents agreed with this statement: I feel my job performance is evaluated fairly. The overwhelming majority in blue felt that they received a fair job performance review. The two main sentiments: Typically, respondents felt there was no wage inequality based on demographics, and that their job performances were being evaluated fairly.
- Hi I’m Samuel. I will be discussing the inequality questions in relation to their demographics.
- All views. With a total of 385 respondents, we separated the Age, Gender, and Race Inequality questions to get overall viewpoints. Almost half of our respondents Disagreed that there was Inequality in each category.
- Age by Age When comparing the Age Inequality views by age group, we see a decreasing amount of agreement as we go up in age range. Starting at approximately 40% going down to 0% with the 65 and over grouping.
- Gender by Gender The comparison of Male and Female respondents to the Inequality by Gender question shows that only about 1% more women believe there is wage inequality based on gender as compared to other women. While male respondents disagree by almost 58% in general and more men disagree than agree when compared to each other.
- Race by Race We have another comparison of Race Inequality views separated by Race/Ethnicity. With Black/African American respondents representing about 22% of the respondents, they were the only group who had a majority agreement there was race Inequality. All other race d white and Hispanic subgroups disagreed by 50% or more that there is inequality in wage based on race.
- State Maps The survey had a majority of respondents from the state of Alabama, so we mapped the responses to the three inequality questions based on the respondents' county. I wanted to look at a level of agreement across counties, and color each county based on the highest level of agreement" Green being they agree as a county, red being they disagree. While the respondents saw inequality in all areas, the most concentration was agreement in Gender inequality noted by the green being the primary color in the first map of this visual.
- Now we wanted to look at the three inequality questions that were covered in the previous section but through the view of the Degree/Non Degree Personas. Overall Degree respondents disagreed to all three questions and Non Degree respondents disagreed with both age and race, but were even with regards to gender. Degree respondents were also strong in their sentiment levels of agreement disagreement to the three questions This led us to the question does having a degree eliminate the belief of inequality based on age, gender, and race in the workplace which we will delve into in the next slides
- This is a combination of the three inequality questions and the Degree Persona's responses Now looking at this chart the sentiment levels are added to show strongly agree/disagree shown in dark green/red, somewhat agree/disagree in lightest green/red The Degree Persona respondents answered in similar percentages to each of the three questions with disagreement as the majority answer to the questions and strongly degree in dark red as the main sentiment level for the center and right charts.
- The Non Degree Persona respondents answered with more of the lighter shades of agreement disagreement than compared to the previous slide of the Degree responses and were overall closer in their spreads with gender in the middle being even in responses.
- Next we wanted to further breakdown the questions and look at specific demographics and how those respondents responded. For the question is there wage inequality based on race, we wanted to look at the responses from the top two race or ethnicities that responded to the survey: Black or African American and White We see that Degree Persona responses for both subcategories on the left have much larger spreads between agreement and disagreement when compared to the Non Degree on the right
- Now this is a look at the previous chart with the sentiment levels now displayed. In chart on the left representing the Degree respondents we can see that when answering is there wage inequality based on race, both Degree responses had strongly agree disagree as their majority sentiment level when compared to the chart on the left representing the Non Degree responses.
- For the question is there wage inequality based on gender, we wanted to look at the responses when separated by genders. First is the Female responses: The Degreed Females were almost equal in their agreement/disagreement. The Non Degreed Females had a 16% spread with more responses in the agreement category. By looking at the chart, we believe that the attainment of a degree may eliminate the gender bias in wage inequality that Female respondents may experience.
- Next we looked at the Male responses to the question: Regardless of degree status, Male respondents answered that they disagreed with the majority sentiment level of strongly disagree shown in dark red that there is inequality based on gender. * May Skip based on Timing* Degreed Male respondents had a 2:1 spread in their disagreement, whereas Non Degreed Male respondents had a 17% spread between disagreement and agreement.
- This wage comparison survey gave us many insights into current workforce beliefs and trends, but also the quest for more data to explore. On behalf of the Data Analytics Cohort, we thank you for joining us today and we will now take questions from the judges.