You must fully interpret your results. There is a relationship doesn t cut it. Use the text and, especially, the SPSS Manual for guidance.
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1 POLI 30D SPRING 2015 LAST ASSIGNMENT TRUMPETS PLEASE!!!!! Due Thursday, December 10 (or sooner), by 7PM hrough TurnIIn I had his all se up in my mind. You would use regression analysis o follow up on your previous wo compuer assignmens and rees he same hypohesis linking income wih views abou defici reducion. I was hen going o have you es i separaely for males and females. Unforunaely, I already did ha in one of he odd numbered exercises. You will cover ha in secion. This will, of necessiy, be somewha differen. These daa come from he Congressional Disric Daa File (see back of SPSS Manual for codebook). Alhough his is no a random sample, inerpre i as such when inerpreing your resuls ( value significance). READ CAREFULLY: YOU DO NOT RUN THE SPSS CODE TO DO THIS EXERCISE!!!!!!! You acually don even have access o hese daa. Bu we do wan you o undersand how his is done so he code is lised. Your TAs have indicaed ha you seem o be dwelling on geing he oupu, bu no doing much inerpreing. So, here s he deal. The oupu ha is needed for each of your secions (see below*) has been run by me and can be found on he TED websie for his class. I will also lis he code you would have used (in blue) for each ask. You don run his, jus ry o undersand i (and expand your SPSS knowledge). You mus fully inerpre your resuls. There is a relaionship doesn cu i. Use he ex and, especially, he SPSS Manual for guidance. *Maya and Lauren: 2008 resuls Liesel and Clara: 2010 resuls Yin: 2012 resuls
2 Hypohesis: The more a Republican candidae spends han his/her Democraic counerpar, he higher he wo-pary voe for he Republican candidae. To es his hypohesis, we will compare: TASK 1: The difference in spending in a paricular elecion cycle beween he Republican and Democraic candidaes (in hundred housands of $). A difference of 2.5 means he Republican candidae spen $250,000 more han he Democraic candidae. Look a p. 151 of your SPSS Manual. The following is he SPSS synax for hese 3 cycles (original daa are in single dollar unis, hus he need o divide by 100,000 o ge any slope value--$1 exra shouldn affec anyhing). A posiive number indicaes ha he Republican candidae spen more han he Democraic one, a negaive number ha he/she spen less. You can look a oher examples of he COMPUTE command in Secion 3.2 of he Manual: COMPUTE DIFF$08=(RH$08-DH$08)/ COMPUTE DIFF$10=(RH$10-DH$10)/ COMPUTE DIFF$12=(RH$12-DH$12)/ Wih he Republican percenage of he wo-pary voe. As here are hird pary candidaes in many house races bu no ohers (and much of he difference is based upon differing sae ballo requiremens), he Republican percenage of he wo-pary voe was calculaed. This amouns o a concepual sandardizaion. COMPUTE REP2P08=RHV08/(RHV08+DHV08). COMPUTE REP2P10=RHV10/(RHV10+DHV10). COMPUTE REP2P08=RHV12/(RHV12+DHV12). A regression was run for each year, wih he Republican percenage of he wo-pary voe as he dependen variable, he spending difference as he independen variable. Here is he code for each year. For your given year: REGRESSION VARIABLES=DIFF$08 REP2P08/DEPENDENT=REP2P08/METHOD=ENTER. REGRESSION VARIABLES=DIFF$10 REP2P10/DEPENDENT=REP2P10/METHOD=ENTER. REGRESSION VARIABLES=DIFF$12 REP2P12/DEPENDENT=REP2P12/METHOD=ENTER. Inerpre he R-square value (use he non-adjused one) Inerpre he slope (he unsandardized bea). Sar wih For every addiional $100,000 difference in spending by he Republican candidae Inerpre he significance value ( ). Is he hypohesis confirmed or disconfirmed? If he Republican ouspen he Democra by $500,000, wha would be your predicion for he percenage of he wo pary voe won by he Republican candidae? If he Republican was ouspen by he Democra by $600,000, wha would be your predicion for he percenage of he wo pary voe won by he Republican candidae?
3 You will now invesigae wo mehods of conrolling for a hird variable: TASK 2: I reran he original regression, bu for he following ypes of disrics separaely. One would use he /SELECT= subcommand for each of he regressions (see example, p. 97 or he boom of p. 100 if using he GUI). A Republican incumben ran (caegory 2 of INC08, INC10, INC12) REGRESSION VARIABLES=DIFF$08 REP2P08/DEPENDENT=REP2P08/METHOD=ENTER /SELECT INC08 EQ 2. REGRESSION VARIABLES=DIFF$10 REP2P10/DEPENDENT=REP2P10/METHOD=ENTER /SELECT INC10 EQ 2. REGRESSION VARIABLES=DIFF$12 REP2P12/DEPENDENT=REP2P12/METHOD=ENTER /SELECT INC12 EQ 2. I was an open sea (no incumben running-caegory 3 or 4: > 3-- of INC08,INC10, INC12) For your given year: REGRESSION VARIABLES=DIFF$08 REP2P08/DEPENDENT=REP2P08/METHOD=ENTER /SELECT INC08 GE 3. REGRESSION VARIABLES=DIFF$10 REP2P10/DEPENDENT=REP2P10/METHOD=ENTER /SELECT INC10 GE 3. REGRESSION VARIABLES=DIFF$12 REP2P12/DEPENDENT=REP2P12/METHOD=ENTER /SELECT INC12 GE 3. For disrics in which a Republican incumben ran: Inerpre he R-squared value Inerpre he slope. Inerpre he significance value ( ). For disrics in which no incumben ran: Inerpre he R-squared value Inerpre he slope. Inerpre he significance value ( ). Is he hypohesis confirmed beer for one ype of disric? Use boh he R- and - values as evidence. Wha does his ell you abou he condiional imporance of money in poliics? Noe: because of differen sample sizes for each subgroup compared o all disrics, he R- squares and -values will no always align he same way. One is descripive, bu one is inferenial and herefore sensiive o sample size (jus as percenage poin differences and chi-square significance).
4 TASK 3: I ran he same regression ha I did in Task 1, bu his ime added a surrogae measure of disric parisanship (Republican presidenial voe %) as a second independen variable (see p. 96 for an example). For 2010, he 2008 presidenial voe was used. I wasn oo concerned abou hird pary voing here, so I didn compue a difference. REGRESSION VARIABLES=DIFF$08 REP2P08 OBAMA08/DEPENDENT=REP2P08/METHOD=ENTER. REGRESSION VARIABLES=DIFF$10 REP2P10 OBAMA08/DEPENDENT=REP2P10/METHOD=ENTER. REGRESSION VARIABLES=DIFF$12 REP2P12 OBAMA2012/DEPENDENT=REP2P12/METHOD=ENTER. How much does adding he presidenial voe add o our explanaion of he variance of Republican 2- pary voe (compare R-square values from his ask and Task 1)? Inerpre he individual slopes (unsandardized) Using he sandardized beas, which variable (presidenial voe or spending difference) is more imporan in predicing he Republican congressional percenage of he wo-pary voe? Noe: unsandardized and sandardized beas migh no show he same in comparison. The former is based on differen unis of measuremen ( for every $100,000 difference in spending / for every exra percen of he voe received by candidae/presiden Obama. ) The laer sandardizes hese and akes away he uni of measuremen ( for every one sandardized uni of spending difference..
5 2008 TASK 1 COMPUTE DIFF$08=(RH$08-DH$08)/ COMPUTE REP2P08=RHV08/(RHV08+DHV08). REGRESSION VARIABLES=DIFF$08 REP2P08/DEPENDENT=REP2P08/METHOD=ENTER. Summary R R Adjused R Sd. Error of he Esimae a a. Predicors: (Consan), DIFF$08 Coefficiens a Unsandardized Coefficiens Coefficiens 1 (Consan) DIFF$ a. Dependen Variable: REP2P08
6 TASK 2: REGRESSION VARIABLES=DIFF$08 REP2P08/DEPENDENT=REP2P08/METHOD=ENTER /SELECT INC08 EQ 2. R Summary INC08 = 2 Adjused R Sd. Error of he (Seleced) R Esimae a a. Predicors: (Consan), DIFF$08 Coefficiens a,b Unsandardized Coefficiens Coefficiens 1 (Consan) DIFF$ a. Dependen Variable: REP2P08 b. Selecing only cases for which INC08 = 2 REGRESSION VARIABLES=DIFF$08 REP2P08/DEPENDENT=REP2P08/METHOD=ENTER/SELECT INC08 GE 3. R Summary INC08 >= 3 Adjused R Sd. Error of he (Seleced) R Esimae a a. Predicors: (Consan), DIFF$08 Coefficiens a,b Unsandardized Coefficiens Coefficiens 1 (Consan) DIFF$ a. Dependen Variable: REP2P08 b. Selecing only cases for which INC08 >= 3
7 TASK 3: REGRESSION VARIABLES=DIFF$08 REP2P08 OBAMA08/DEPENDENT=REP2P08/METHOD=ENTER. Summary R R Adjused R Sd. Error of he Esimae a a. Predicors: (Consan), OBAMA08, DIFF$08 Coefficiens a Unsandardized Coefficiens Coefficiens 1 (Consan) DIFF$ OBAMA a. Dependen Variable: REP2P08
8 2010 TASK 1 COMPUTE DIFF$10=(RH$10-DH$10)/ COMPUTE REP2P10=RHV10/(RHV10+DHV10). REGRESSION VARIABLES=DIFF$10 REP2P10/DEPENDENT=REP2P10/METHOD=ENTER. Summary R R Adjused R Sd. Error of he Esimae a a. Predicors: (Consan), DIFF$10 Coefficiens a Unsandardized Coefficiens Coefficiens 1 (Consan) DIFF$ a. Dependen Variable: REP2P10
9 TASK 2: REGRESSION VARIABLES=DIFF$10 REP2P10/DEPENDENT=REP2P10/METHOD=ENTER/SELECT INC10 EQ 2. R Summary INC10 = 2 Adjused R Sd. Error of he (Seleced) R Esimae a a. Predicors: (Consan), DIFF$10 Coefficiens a,b Unsandardized Coefficiens Coefficiens 1 (Consan) DIFF$ a. Dependen Variable: REP2P10 b. Selecing only cases for which INC10 = 2 REGRESSION VARIABLES=DIFF$10 REP2P10/DEPENDENT=REP2P10/METHOD=ENTER/SELECT INC10 GE 3. R Summary INC10 >= 3 Adjused R Sd. Error of he (Seleced) R Esimae a a. Predicors: (Consan), DIFF$10 Coefficiens a,b Unsandardized Coefficiens Coefficiens 1 (Consan) DIFF$ a. Dependen Variable: REP2P10 b. Selecing only cases for which INC10 >= 3
10 TASK 3: Summary R R Adjused R Sd. Error of he Esimae a a. Predicors: (Consan), OBAMA08, DIFF$10 Coefficiens a Unsandardized Coefficiens Coefficiens 1 (Consan) DIFF$ OBAMA a. Dependen Variable: REP2P10
11 2012 TASK 1 COMPUTE DIFF$12=(RH$12-DH$12)/ COMPUTE REP2P12=RHV12/(RHV12+DHV12). REGRESSION VARIABLES=DIFF$12 REP2P12/DEPENDENT=REP2P12/METHOD=ENTER. Summary R R Adjused R Sd. Error of he Esimae a a. Predicors: (Consan), DIFF$12 Coefficiens a Unsandardized Coefficiens Coefficiens 1 (Consan) DIFF$ Dependen Variable: REP2P12
12 TASK 2: REGRESSION VARIABLES=DIFF$12 REP2P12/DEPENDENT=REP2P12/METHOD=ENTER/SELECT INC12 EQ 2. R Summary INC12 = 2 Adjused R Sd. Error of he (Seleced) R Esimae a a. Predicors: (Consan), DIFF$12 Coefficiens a,b Unsandardized Coefficiens Coefficiens 1 (Consan) DIFF$ a. Dependen Variable: REP2P12 b. Selecing only cases for which INC12 = 2 REGRESSION VARIABLES=DIFF$12 REP2P12/DEPENDENT=REP2P12/METHOD=ENTER/SELECT INC12 GE 3. R Summary INC12 >= 3 Adjused R Sd. Error of he (Seleced) R Esimae a a. Predicors: (Consan), DIFF$12 Coefficiens a,b Unsandardized Coefficiens Coefficiens 1 (Consan) DIFF$ a. Dependen Variable: REP2P12 b. Selecing only cases for which INC12 >= 3
13 TASK 3: Summary R R Adjused R Sd. Error of he Esimae a a. Predicors: (Consan), OBAMA2012, DIFF$12 Coefficiens a Unsandardized Coefficiens Coefficiens 1 (Consan) DIFF$ OBAMA a. Dependen Variable: REP2P12
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