Racial steering A subtle form of racial discrimination in...

Racial steering A subtle form of racial discrimination in housing is “racial steering.” Racial steering occurs when real estate agents show prospective buyers only homes in neighborhoods already dominated by that family’s race. This violates the Fair Housing Act of 1968. According to an article in Chance magazine (Vol. 14, no. 2 [2001]), tenants at a large apartment complex recently filed a lawsuit alleging racial steering. The complex is divided into two parts: Section A and Section B. The plaintiffs claimed that white potential renters were steered to Section A, while African-Americans were steered to Section B. The table describes the data that were presented in court to show the locations of recently rented apartments. Do you think there is evidence of racial steering? TABLE CAN'T COPY

Key Concepts

Statistical Analysis in Discrimination Cases

Statistical analysis in discrimination cases involves using housing data to identify and examine patterns that may indicate biased practices, such as whether different racial groups are shown homes in different neighborhoods. This analysis is critical in providing evidence in legal cases to support claims of racial discrimination in housing practices.

Housing Discrimination

Housing discrimination encompasses actions and policies that result in unequal treatment in buying, renting, or obtaining financing for housing based on characteristics like race. Practices such as racial steering represent a specific instance where minority groups are systematically disadvantaged in the housing market.

Racial Steering

Racial steering is a practice in the housing market where real estate agents guide potential buyers or renters towards neighborhoods predominantly inhabited by members of their own race, thereby limiting their exposure to more diverse housing options. It is a subtle form of discrimination that reinforces segregated communities and obstructs equal access to housing opportunities.

Fair Housing Act

The Fair Housing Act of 1968 is a key piece of civil rights legislation that prohibits discrimination in housing based on race, color, national origin, religion, sex, familial status, or disability. This law is intended to provide equal housing opportunities and is used to challenge practices such as racial steering that contribute to segregation and inequality.

Transcript

00:01 Now in this question we have been given a table what they're asking they're saying that the table describes the data that was presented in the court to show the locations of recently rendered apartments and do we think that there is evidence of racial steering? okay so let us try to look at the table in the table there is section a section b then white black and total.

00:43 White black okay what are the values 87 83 834 87 83 834 all right then we are going to have the totals this is going to be 170 this is going to be 42 this is going to be 95 this is going to be 117 and the addition of these is 212.

01:39 This is the grand token.

01:42 All right.

01:43 Now what we are trying to see here is independence, right? homogeneity or independence, sometimes i just feel like both of them are the same, but actually they're not.

01:56 So we want to see test if there is independence or not.

02:04 Okay.

02:05 So what do we need? we first need to find the expected values for each and every block.

02:11 How do we get the expected value? the expected value for every block is going to be the observed value.

02:17 That is this value, right? this is, oh, just a moment.

02:27 Forget about the observed value.

02:29 This is going to be, the expected value is going to be the row total, multiplied by the column total multiplied by the column total upon the grand total upon the grand total all right so if i draw this table again i'm not going to write the labels the labels are going to be the same right but let me just write these values so for example if i want an expected value for this for white people living in section b it is going to be 117 into 170 by 212 right 117 into 170 by 212 so if i use a calculator for this 117 into 170 divided by 212 this is 93 .82 this is 93 .82 93 .82.

03:42 Similarly for the first value for the first value we are going for 87 we are going to have 95 into 170 by 212 95 into 170 by 212.

03:54 95 into 170 by 212.

03:57 All right so 95 into 170 divided by 212 this is 76 .179.

04:10 Let me write this as 76 .18, 76 .18.

04:22 And i have calculated these values.

04:26 The rest of the values are going to be 18 .82 and 23 .18 .18 .82 and 23 .18 .82 and 23 .18.

04:41 Now what exactly is the kai square statistic what is going to be the kai square value the kai square is going to be summation of observed minus expected whole square upon expected okay and this is in the root right oh no this is not in the root just a moment not an entire thing.

05:18 This is in the root.

05:23 So let us try to find the values for one of them.

05:27 Let's say this is 76 .18.

05:31 This is the expected.

05:32 What is the observed? observed is 87.

05:34 So this is going to be 87 minus 76 .18...

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