Reference no: EM132093719

FAMILIES, RACE AND POVERTY IN 2000

Objectives: Practice accessing and interpreting data; examine relationship between race, poverty and household type; explore the family as a social institution.

In this exercise, we are interested in looking at how family types vary by race and ethnic group. We will be using the computer software WebCHIP and SSDAN American Community Survey data set for this analysis. We will be using the most recent data collected from the U.S. Census.

There are four parts to this exercise. You will answer questions on Parts I, II, & III by taking a quiz. You will answer Part IV by responding in a discussion forum with your peers.

PART I-RACE/ETHNIC DIFFERENCES IN FAMILY TYPE

Go to ssdan. Under "collections" find acs2010in then under "datasets" find housing. Create a Percent Down table with "HHType" as the row variable, and "RaceEth" as the column variable. Click Percent Down to generate a table. Use the % information produced to answer the following questions (using the online quiz).

1. Which race/ethnic group has the highest % of married couples (MrrdCpl)?

2. Which race/ethnic group has the lowest % of married couples (MrrdCpl)?

3. Which race/ethnic group has the highest % of female headed family households (FemFam)?

4. Which race/ethnic group has the lowest % of female headed family households (FemFam)?

5. Which group has the highest % of male-headed family households (MaleFam)?

6. Which group has the lowest % of male-headed family households (MaleFam)?

7. Give one reason why you think some groups have high percentages of married couples while others have low percentages.

PART II: POVERTY AND FAMILY/HOUSEHOLD TYPE

Let's test one possible explanation for the race¬/ethnic differences observed in Part I. This explanation suggests that the differences are partly attributable to diversity in socio¬economic status (SES).

If we use poverty status as the measure of SES, we can test the explanation. First we need to see how family type varies with poverty status.

Go to ssdan . Under "collections" find acs2010and select it. Then, under "datasets"find FamPovGeoand select it.

Create a Percent Down table with "FamType" as the row variable, and "PovLevel" as the column variable. Use the data generated to answer the following questions (using the online quiz).

1. What type of family group constitutes the majority of the poor?

2. What type of family group constitutes the majority of the near poor?

3. What type of family group constitutes the majority in the top two income levels?

4. What is one reason the poverty rate of a group can affect its marriage rate?

PART III RACE/ETHNICITY AND POVERTY

In order to demonstrate that family type varies among racial groups due to their different experiences with poverty, we now need to link poverty to race/ethnicity. How do poverty rates vary with race/¬ethnicity?

Stay in "FamPovGeo" under "acs2010". Create a Percent Down table with "PovLevel" as the row variable, and "RaceEth" as the column variable.

Use the % information produced to answer the following questions (using the online quiz):

1. Which is the poorest race/¬ethnic group?

2. Which is the richest race/¬ethnic group?

PART IV PUTTING IT ALL TOGETHER

After taking the multiple choice quiz answering the above questions, write a brief response (minimum 200 words) to the following questions:

1. What data did you find surprising or interesting in this exercise? Why?

2. Do the data from Parts II & III together provide some evidence that race/¬ethnic differences in poverty rates probably account in part for race/¬ethnic diversity in marriage rates? Explain.

3. What do the results of this exercise suggest the government should do if they want to strengthen American families?

4. Latinos have poverty rates almost as high as Blacks and yet their rates of married couples are much higher. Why do you think that is?

5. How accurate were you in interpreting the data presented in the tables that you generated (the results of your quiz should tell you how accurate you were!)? How often do you use data like the ones presented in this exercise to help understand the world around you? Why do you think that is?