!!! 2!

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2016/5/17 (Tue) SPSS (mugiyama@l.u-tokyo.ac.jp)!

!!! 2!

3!

4!

!!! 5!

(Population)! (Sample) 6!

case, observation, individual! variable!!! 1 1 4 2 5 2 1 5 3 4 3 2 3 3 1 4 2 1 4 8 7!

(1) (2) (3) (4) categorical variable continuous variable! *! * 8!

2 9!

! α β A B 10!

! (%) 10 8 6 4 2 男性女性 0 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 年齢 49 = 31.1( ) 29.4( )! 2014 11!

12!

Stata!! SPSS GUI!! R!!! 13!

SPSS? Statistical Package for Social Science! IBM! Base! SPSS Advanced, Regression, Categories! 14!

SPSS 1. sav csv! 2.! 3.! 4.! 5.! 6. 4. 5.! 7.! 8. SPSS! 15!

SPSS 16!

SPSS 17!

SPSS 18!

SPSS 19!

ctrl + R COMMAND /SUBCOMMAND... 1 1 EXECUTE. 20!

21!

! 3!! 22!

! RECODE! COMPUTE! IF! 23!

RECODE (1) RECODE x1 (values = value). /* */ RECODE x1 (values = value) INTO n1. /* */ CROSSTABS x1 by n1. SYNTAX ELSE THRU HIGHEST LOWEST COPY SYSMIS 1 THRU 4 1 4 24!

RECODE (2) /* */ * attitude. RECODE attitude (1 = 4)(2 = 3)(3 = 2)(4 = 1). * age agegroup. RECODE age (20 THRU 34 = 1)(35 THRU 49 = 2)(50 THRU 64 = 3)(65 THRU HIGHEST = 4) INTO agegroup. * sex RECODE sex (1 = 1)(2 = 0)(ELSE = SYSMIS) INTO male. RECODE sex (1 = 0)(2 = 1)(ELSE = SYSMIS) INTO female. 25!

COMPUTE (1) COMPUTE n1 = expression. /* +-*/ */ SYNTAX SYNTAX SUM EXP MEAN LN MAX ABS MIN TRUNC SQRT 26!

COMPUTE (2) /* */ * income lnincome. COMPUTE lnincome = ln(income). * item1, item2,, item5 numitem. COMPUTE numitem = item1 + item2 + item3 + item4 + item5. * COMPUTE numitem = SUM(item1 TO item5). *, 1 numitem. 27!

IF(1) IF (logical expression) n1 = value or variable. SYNTAX EQ or = NE or ~= LT or < LE or <= GT or > GE or >= AND or & OR or NOT 28!

IF(2) /* */ *marriage children lifestage. IF (marriage = 0) lifestage = 1. IF (marriage = 1 & children = 0) lifestage = 2. IF (marriage = 1 & children >= 1 & children ~= 9) lifestage = 3. IF (marriage = 9 children = 9) lifestage = 9. EXECUTE. 29!

!! VARIABLE LABELS! VALUE LABELS! 30!

VARIABLE LABELS VARIABLE LABELS x1 name. /* */ * agegroup. VARIABLE LABELS agegroup. /* */ *. 31!

VALUE LABELS VALUE LABELS x1 1 valuename1 2 valuename2. /* */ * agegroup. VALUE LABELS agegroup 1 20-34 2 35-49 3 50-64 4 65. 32!

!! SELECT IF! FILTER SPSS 33!

SELECT IF SELECT IF (logical expression). /* */ *60. SELECT IF (age < 60). *60 income. TEMPORARY SELECT IF (age < 60). FREQUENCIES income /statistics = DEFAULT. /* */ * IF. *TEMPORARY SELECT. 34!

FILTER FILTER BY x1. /* */ fil1. COMPUTE fil1 = (sex = 1 AND educ = 3). FILTER BY f1. FILTER OFF. /* / *x1 1 (0 ). *FILTER OFF. fil1. 35!

q24 1 = 1 2 = 2! q22f 1 (f)! (1) (2) (3) (4) (5)!! 36!

37!

1!! 2! 38!

(frequency table)! % % 134 33.5 33.5 109 27.3 60.8 53 13.3 74.1 85 21.3 95.4 19 4.8 100.0 400 100.0 A 39!

(%) 40! 35! 30! 25! 20! 15! 10! 5! 0! 33.5! N = 400 27.3! 13.3! 21.3! 4.8! A 40!

Mean!!! x = 1 n nx i=1 x i Variance!!! Var(x) = 1 n Standard deviation nx (x i x) 2 i=1 Sd(x) = p Var(x) Median Mode! Maximum, minimum 41!

400 2.37 1.27 1 2 A 1.! 2.!! 1.! 2.! 42!

FREQUENCIES (1) FREQUENCIES x1 x2 x3 /STATISTICS = DEFAULT /HISTOGRAM /BARCHART. SYNTAX SYNTAX DEFAULT VARIANCE STDDEV MEAN MAXIMUM MEDIAN MINIMUM MODE ALL 43!

FREQUENCIES (2) /* */ * attitude. FREQUENCIES attitude /STATISTICS = MEAN STDDEV /HISTOGRAM. 44!

missing value 3! 1. Don t Know Not Answer! 2.! 3. Not applicable! 2. 3. 1.!! MISSING VALUES x1 (9). 45!

46!

X Y!!!! 47!

X Y X Y!!! 48!

X = 1 X = 2 Y!! 49!

!!! Total! 71! 78! 28! 61! 16! 254! (28.0)! (30.7)! (11.0)! (24.0)! (6.3)! (100.0)! 63! 31! 25! 24! 3! 146! (43.2)! (21.2)! (17.1)! (16.4)! (2.1)! (100.0)! Total 134! 109! 53! 85! 19! 400! Pearson s χ 2 = 18.07 (p < 0.01)! %! (33.5)! (27.3)! (13.3)! (21.3)! (4.8)! (100.0)! A 50!

!!! Total! 71! 78! 28! 61! 16! 254! (28.0)! (30.7)! (11.0)! (24.0)! (6.3)! (100.0)! 63! 31! 25! 24! 3! 146! (43.2)! (21.2)! (17.1)! (16.4)! (2.1)! (100.0)! Total 134! 109! 53! 85! 19! 400! Pearson s χ 2 = 18.07 (p < 0.01)! %! (33.5)! (27.3)! (13.3)! (21.3)! (4.8)! (100.0)! A 51!

(%) 50 40 30 20 10 0 43.2 28 感じない 30.7 21.2 あまり感じない 17.1 11 どちらともいえない非独居 (N = 146) 24 16.4 独居 (N = 254) (%) 0 20 40 60 80 100 6.3 2.1 すこし感じるとても感じる独居 (N = 254) 28 30.7 11 24 6.3 非独居 (N = 146) 43.2 21.2 17.1 16.4 2.1 感じないあまり感じないどちらともいえないすこし感じるとても感じる 52!

CROSSTABS(1) CROSSTABS x BY y /CELLS = COUNT ROW /STATISTICS = CHISQ. /* */ *x y. *. 53!

CROSSTABS(2) CELLS SYNTAX SYNTAX SYNTAX COUNT TOTAL % ARESID ROW % EXPECTED COLUMN % RESID ALL SYNTAX CHISQ PHI RISK CORR GAMMA ALL STATISTICS 2 Cramer V 2 2 Pearson Spearman Goodman=Kruskal γ 54!

N! 2.50! 1.29! (254)! 2.13! 1.20! (146)! Total! 2.37! 1.27! (400)! F = 7.99 (df = 1, p < 0.01)! A 2.6 2.4 2.2 2 1.8 1.6 1.4 1.2 1 同居 (N = 254) 非独居 (N = 146) 55!

MEANS (1) MEANS TABLES = x BY y /CELLS = MEAN STDDEV COUNT /STATISTICS = ANOVA. /* */ *x y. *. 56!

MEANS (2) SYNTAX SYNTAX DEFAULT CELLS MEDIAN MEAN MIN STDDEV MAX COUNT VARIANCE SYNTAX ANOVA RISK STATISTICS 57!

Excel!! Excel!! 58!

59!

60! 2013! 2015! 2015! 2004! 2013 2 2! 2015!! 60!

61! 2005! 2007 JGSS! 2015! Wooldridge, Jeffrey M., 2013, Introductory Econometrics: A Modern Approach (Fifth International Edition), South-Western; Cengage Learning.! Long, J. Scott, 1997, Regression Models for Categorical and Limited Dependent Variables, Thousand Oaks; Sage.! 61!

62! 2014, SPSS! 2014Stata. 2008 R! 2013. 2015 (http://tsutawarudesign.web.fc2.com) 2015 (http://ppt.design4u.jp)! 62!

63! 1979! 2013! King, Gary, Robert O. Keohane, and Sidney Verba, 1991, Designing Social Inquiry: Scientific Inference in Qualitative Research, Prinston University Press. 2004! 2010! 63!

64! 2015 A!!! http://quansocres.blogspot.jp/! 64!