Q2) In the following table (A), FBI 2012 data for violent crimes is reported by sex of offenders and the sex of victims. a) What is the independent variable? sex of offender b) How many errors of prediction will be made if the independent variable is ignored? 5940-5360 = 580. c) How many fewer errors will be made if the independent variable is taken into account?

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I had a question on how to calculate the E1 and E2 in lambda and how to answer Q2. parts b and c. I'm confused on which is which and how to calculate each. 

Q2) In the following table (A), FBI 2012 data for violent crimes is reported by sex of offenders and the
sex of victims.
a) What is the independent variable?
sex of offender
b) How many errors of prediction will be made if the independent variable is ignored?
5940 - 5360 - 580
c) How many fewer errors will be made if the independent variable is taken into account?
d) Calculate lambda. Interpret the result.
e) Calculate Lambda for Table B comparing sex of victim vs race (Table B). Interpret the result.
f) Which relationship is stronger: the one for sex of offenders/victims or race of offenders/victims?
Table A
Sex of Victim
Male
Female
Total
Sex of Offender
Male
1600
3760
5360
Female
140
440
580
Total
1740
4200
5940
Transcribed Image Text:Q2) In the following table (A), FBI 2012 data for violent crimes is reported by sex of offenders and the sex of victims. a) What is the independent variable? sex of offender b) How many errors of prediction will be made if the independent variable is ignored? 5940 - 5360 - 580 c) How many fewer errors will be made if the independent variable is taken into account? d) Calculate lambda. Interpret the result. e) Calculate Lambda for Table B comparing sex of victim vs race (Table B). Interpret the result. f) Which relationship is stronger: the one for sex of offenders/victims or race of offenders/victims? Table A Sex of Victim Male Female Total Sex of Offender Male 1600 3760 5360 Female 140 440 580 Total 1740 4200 5940
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