Income Less Than High School High School Grads Some College College Grads Total< 25K 49.6% 33.1% 24.1% 10.1% 23.2%25-34K 21.6% 21.3% 18.6% 8.2% 15.7%35-49K 15.8% 21.4% 22.3% 16.5% 19.4%50-69K 8.1% 14.3% 18.2% 20.4% 17.2%70-99K 3.2% 6.7% 10.8% 19.4% 12.3%100K+ 1.7% 3.2% 6% 25.4% 12%Total 100% 100% 100% 100% 100%STEP 2: Identify the independent variable and the dependent variable that could be tested based on this graph.STEP 3: Summarize the bivariate table by making at least 3 TRUE statements about the variables using the data (the percentages) provided.STEP 4: Use your sociological imagination to analyze the data. This should be a minimum of 2-3 sentences.STEP 5: What policy recommendations would you make based on the data? This should be a minimum of 2-3 sentences.

STEP 2: The independent variable in this case is the level of education (Less Than High School, High School Grads, Some College, College Grads) and the dependent variable is the income range (< 25K, 25-34K, 35-49K, 50-69K, 70-99K, 100K+).

STEP 3:

1. The highest percentage of individuals earning less than 25K are those with less than a high school education (49.6%).
2. College graduates have the highest percentage of individuals earning 100K+ (25.4%).
3. The income range with the least disparity across education levels is 35-49K, with percentages ranging from 15.8% to 22.3%.

STEP 4: The data suggests a strong correlation between education level and income. Those with higher education levels tend to earn higher incomes. This could be due to a variety of factors, including the types of jobs available to individuals with different education levels, the value placed on education in different industries, and systemic issues related to access to education and economic opportunity.

STEP 5: Based on this data, I would recommend policies that increase access to education, particularly higher education, as a means of increasing income potential. This could include policies that reduce the cost of college, provide financial aid or scholarships, or increase access to vocational and technical training programs. Additionally, policies that address wage disparities across industries and education levels could also be beneficial.

STEP 2: The independent variable in this case is the level of education (Less Than High School, High School Grads, Some College, College Grads) and the dependent variable is the income range (< 25K, 25-34K, 35-49K, 50-69K, 70-99K, 100K+).

STEP 3:

1. The highest percentage of individuals earning less than 25K are those with less than a high school education (49.6%).
2. College graduates have the highest percentage of individuals earning 100K+ (25.4%).
3. The income range with the least disparity across education levels is 35-49K, with percentages ranging from 15.8% to 22.3%.

STEP 4: The data suggests a strong correlation between education level and income. Those with higher education tend to earn more, while those with less education tend to earn less. This could be due to a variety of factors, including the types of jobs available to individuals with different education levels, societal values placed on education, and the skills and knowledge gained through higher education.

STEP 5: Based on this data, I would recommend policies that promote access to higher education. This could include financial aid programs, scholarships, and career counseling in high schools to help students understand the potential financial benefits of higher education. Additionally, programs that provide job skills training for those with less than a high school education could help increase income levels in this group.