Need help ASAP!!! 4. As a class, combine your samples to fill in the observed table. Then, calculate the expectedcounts. Note: all force levels other than "hands" (including push to wall/ground, handcuffs,draw/point weapon, pepper spray, baton) are all considered "higher level" force, The NYPD dịd notinclude police shootings in this dataset.YOWtutal XCölumn tota ltable totalExpectedObservedForceBlackHispanicWhiteTotalForceBlackHispanicWhiteTotalNone 300 |78615PNone57 39Higher 2Y 20HandsHandsOnlyOnlyHigherLevelLevelTotalTotal5. Do the data provide convincing evidence of an association between race of suspects and thelevels of force used by police officers? Use a = 0.05.STATE: Hypotheses:Significance level:PLAN:Name of procedure: chi-square test for independenceCheck conditions:DO:Specific Formula:Work:Picture:Test statistic:P-value:CONCLUDE:Lesson provided by Stats Medic (statsmedic.com) & Skew The Script (skewthescript.org)Made available under a Creative Commons Atribution-NonCommercial-ShareAlike 4.0 License(https://creativecommons.org/licenses/by-no-sal4.0) Was "Stop and Frisk" Biased?Today, we'll analyze 2011 data from New York's "Stop and Frisk" program. The program allowedpolice officers to stop people on the street and search them for weapons or contraband. Theprogram was controversial. Critics alleged that it led to heightened police discrimination of people ofcolor. We will explore that claim using a chi-square test for independence.Open the following links:The program data (may take some time to load): tinyurl.com/stop-and-frisk-dataRandom number generator: random.org/integersNYPD precinct map: tinyurl.com/nypd-precinctsThe data we're using contains every stop made by NYPD police officers in 2011 (more than half amillion stops in total). Each row represents a single stop. The second tab in the spreadsheetcontains a data key and further information. Note: These data were reported by the police officerswho made the stops.1. Use the random number generator to obtain 10 random integers between the values 2 and632722 (the number of dataset rows). Find the dataset row numbers that correspond with your 10random integers and record the following information for each selected stop:RaceForceLevel2. For one of your selected stops, look at all the variables listed: race, gender, and age of suspectalong with the suspected crime and whether an arrest was actually made. If you'd like, use theprecinct number and precinct map (linked above) to see the general area in which this stop tookplace. Write a two-sentence description of this stop, as if you're writing a news brief for an article:3. Often, police interactions are portrayed at an individual level in the news media, with vivid detailsgiven about the people involved and the interactions themselves. We are about to conduct astatistical analysis of many interactions, focusing solely on the relationship between race and forcelevel used. What are the strengths and weaknesses of each type of analysis (individual &statistical)?Lesson provided by Stats Medic (statsmedic.com) & Skew The Script (skewthescript.org)Made available under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License(https://creativecommons.org/licenses/by-nc-sa/4.0)

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4. As a class, combine your samples to fill in the observed table. Then, calculate the expected counts. Note: all force levels other than "hands" (including push to wall/ground, handcuffs, draw/point weapon, pepper spray, baton) are all considered "higher level" force, The NYPD did not include police shootings in this dataset. YOWtatal XColUmn tota table total Expected Observed Force Black Hispanic White Total Force Black Hispanic White Total None 300 (86 58 None Hands |57 39 Hands Only Only Higher 28 Level 20 Higher Level Total Total 5. Do the data provide convincing evidence of an association between race of suspects and the levels of force used by police officers? Use a = 0.05. STATE: Hypotheses: Significance level: PLAN: Name of procedure: chi-square test for independence Check conditions: DO: Specific Formula: Work: Picture: Test statistic: P-value: CONCLUDE:

4. As a class, combine your samples to fill in the observed table. Then, calculate the expected counts. Note: all force levels other than "hands" (including push to wall/ground, handcuffs, draw/point weapon, pepper spray, baton) are all considered "higher level" force, The NYPD did not include police shootings in this dataset. YOWtatal XColUmn tota table total Expected Observed Force Black Hispanic White Total Force Black Hispanic White Total None 300 (86 58 None Hands |57 39 Hands Only Only Higher 28 Level 20 Higher Level Total Total 5. Do the data provide convincing evidence of an association between race of suspects and the levels of force used by police officers? Use a = 0.05. STATE: Hypotheses: Significance level: PLAN: Name of procedure: chi-square test for independence Check conditions: DO: Specific Formula: Work: Picture: Test statistic: P-value: CONCLUDE:

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Statements and Logic

Logic is the analysis of general patterns of thoughts without regard to any specific sense of context.

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Need help ASAP!!!

4. As a class, combine your samples to fill in the observed table. Then, calculate the expected
counts. Note: all force levels other than "hands" (including push to wall/ground, handcuffs,
draw/point weapon, pepper spray, baton) are all considered "higher level" force, The NYPD dịd not
include police shootings in this dataset.
YOWtutal XCölumn tota l
table total
Expected
Observed
Force
Black
Hispanic
White
Total
Force
Black
Hispanic
White
Total
None 300 |78615P
None
57 39
Higher 2Y 20
Hands
Hands
Only
Only
Higher
Level
Level
Total
Total
5. Do the data provide convincing evidence of an association between race of suspects and the
levels of force used by police officers? Use a = 0.05.
STATE: Hypotheses:
Significance level:
PLAN:
Name of procedure: chi-square test for independence
Check conditions:
DO:
Specific Formula:
Work:
Picture:
Test statistic:
P-value:
CONCLUDE:
Lesson provided by Stats Medic (statsmedic.com) & Skew The Script (skewthescript.org)
Made available under a Creative Commons Atribution-NonCommercial-ShareAlike 4.0 License
(https://creativecommons.org/licenses/by-no-sal4.0)

Was "Stop and Frisk" Biased?
Today, we'll analyze 2011 data from New York's "Stop and Frisk" program. The program allowed
police officers to stop people on the street and search them for weapons or contraband. The
program was controversial. Critics alleged that it led to heightened police discrimination of people of
color. We will explore that claim using a chi-square test for independence.
Open the following links:
The program data (may take some time to load): tinyurl.com/stop-and-frisk-data
Random number generator: random.org/integers
NYPD precinct map: tinyurl.com/nypd-precincts
The data we're using contains every stop made by NYPD police officers in 2011 (more than half a
million stops in total). Each row represents a single stop. The second tab in the spreadsheet
contains a data key and further information. Note: These data were reported by the police officers
who made the stops.
1. Use the random number generator to obtain 10 random integers between the values 2 and
632722 (the number of dataset rows). Find the dataset row numbers that correspond with your 10
random integers and record the following information for each selected stop:
Race
Force
Level
2. For one of your selected stops, look at all the variables listed: race, gender, and age of suspect
along with the suspected crime and whether an arrest was actually made. If you'd like, use the
precinct number and precinct map (linked above) to see the general area in which this stop took
place. Write a two-sentence description of this stop, as if you're writing a news brief for an article:
3. Often, police interactions are portrayed at an individual level in the news media, with vivid details
given about the people involved and the interactions themselves. We are about to conduct a
statistical analysis of many interactions, focusing solely on the relationship between race and force
level used. What are the strengths and weaknesses of each type of analysis (individual &
statistical)?
Lesson provided by Stats Medic (statsmedic.com) & Skew The Script (skewthescript.org)
Made available under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License
(https://creativecommons.org/licenses/by-nc-sa/4.0)

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