UJI BEDA MEAN DAN BEDA PROPORSI - WordPress.com

UJI BEDA MEAN DAN BEDA PROPORSI - WordPress.com

LOGO UJI BEDA MEAN DAN BEDA PROPORSI Uji Beda Mean Uji Normalitas PARAMETRIK 2 mean independen homogen >2 mean paired 2 mean independen >2 mean paired Varian Homogen heterogen Independen t test NONPARAMETRIK Paired t test ANOVA Jika TIDAK HOMOGEN

Mann-Whitney Wilcoxon Kruskal-Wallis Tahapan Uji hipotesis 1. Buat hipotesis statistik (H0) dan hipotesis alternatif (Ha) 2. Tentukan nilai (kesalahan tipe 1) 3. Tentukan uji statistik yg akan digunakan u/ menganalisis data 4. Lakukan perhitungan statistik (tentukan nilai probabilitas/ p value) 5. Buat keputusan menolak atau menerima H0. (p value : H0 ditolak dan p value > : H0 gagal ditolak) ANOVA Prinsip: perbedaan variance antar BETWEEN dan WITHIN dg menggunakan mean sum square Asumsi: berdistribusi NORMAL & varian HOMOGEN ??? Semakin besar variance BETWEEN BEDA ANTAR KELOMPOK Semakin besar variance WITHIN BEDA ANTAR INDIVIDU ANOVA Var DEPENDEN var INDEP Descriptives BBAYI

N SD SMP SMA Total 47 84 58 189 Mean 2400.43 2915.17 3428.38 2944.66 Std. Deviation 695.899 555.331 655.324 729.022 Std. Error 101.507 60.592 86.048 53.029 95% Confidence Interval for Mean Lower Bound Upper Bound 2196.10 2604.75 2794.65

3035.68 3256.07 3600.69 2840.05 3049.26 Minimum 709 1588 1729 709 Maximum 3940 4153 4990 4990 Test of Homogeneity of Variances BBAYI Levene Statistic 1.300 df1 2 df2 186 Sig. .275 Variasi nilai BB bayi adalah homogen (p>0,05) antar ketiga kelompok pendidikan ibu asumsi terpenuhi

ANOVA BBAYI Between Groups Within Groups Total Sum of Squares 27565146 72351907 99917053 df 2 186 188 Mean Square 13782572.92 388988.746 F 35.432 Sig. .000 Ada perbedaan mean BB bayi Antar kel pendidikan ibu (p<0,05) tp tidak menjelaskan antar kelompok yang mana ANOVA Ksimpulan: ada perbedaan rata-rata BB bayi antar kelompok pendidikan ibu POST HOC

ANOVA Multiple Comparisons Dependent Variable: BBAYI Tukey HSD (I) DIDIK SD SMP SMA Scheffe SD SMP SMA LSD SD SMP SMA Bonferroni SD SMP SMA (J) DIDIK SMP SMA SD SMA SD SMP SMP

SMA SD SMA SD SMP SMP SMA SD SMA SD SMP SMP SMA SD SMA SD SMP Mean Difference (I-J) -514.74* -1027.95* 514.74* -513.21* 1027.95* 513.21* -514.74* -1027.95* 514.74* -513.21* 1027.95* 513.21* -514.74* -1027.95* 514.74* -513.21*

1027.95* 513.21* -514.74* -1027.95* 514.74* -513.21* 1027.95* 513.21* Std. Error 113.610 122.405 113.610 106.478 122.405 106.478 113.610 122.405 113.610 106.478 122.405 106.478 113.610 122.405 113.610 106.478 122.405 106.478 113.610 122.405 113.610 106.478 122.405 106.478 *. The mean difference is significant at the .05 level.

Sig. .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 95% Confidence Interval Lower Bound Upper Bound -783.16 -246.32 -1317.15 -738.76 246.32 783.16 -764.78 -261.65

738.76 1317.15 261.65 764.78 -795.08 -234.40 -1330.00 -725.91 234.40 795.08 -775.96 -250.47 725.91 1330.00 250.47 775.96 -738.87 -290.61 -1269.43 -786.47 290.61 738.87 -723.27 -303.15 786.47 1269.43 303.15 723.27 -789.20 -240.28 -1323.66 -732.24 240.28 789.20 -770.44 -255.98 732.24

1323.66 255.98 770.44 Ada perbedaan mean BB bayi antara kel ibu SD dg SMP; antar kel ibu SMP dg SMA & antar kel ibu SD dg SMA CHI SQUARE Dasar dari uji Chi Square adalah membandingkan frekuensi yang diamati (Observed = O) dengan frekuensi yang diharapkan (Expected = E) Perbedaan antara pengamatan dengan diharapkan (O-E) dianalisa apakah perbedaan itu cukup berarti (bermakna) atau hanya karena faktor variasi sampel saja (by chance). Chi-Square (X2) Uji beda proporsi Contoh: apakah terdapat perbedaan proporsi berat bayi lahir rendah antar kelompok status merokok ibu? apakah terdapat perbedaan proporsi berat bayi lahir rendah antar kelompok riwayat hipertensi ibu? apakah terdapat perbedaan proporsi berat bayi lahir rendah antar tingkat pendidikan ibu? Chi-Square Chi-Square Tests ROKOK * BBLR Crosstabulation BBLR

ROKOK Tidak Ya Total Count % within ROKOK Count % within ROKOK Count % within ROKOK Tidak 86 74.8% 44 59.5% 130 68.8% Ya 29 25.2% 30 40.5% 59 31.2% Total 115 100.0% 74 100.0% 189 100.0%

Pearson Chi-Square a Continuity Correction Likelihood Ratio Fisher's Exact Test Linear-by-Linear Association N of Valid Cases Value 4.924b 4.236 4.867 4.898 df 1 1 1 1 Asymp. Sig. (2-sided) .026 .040 .027 Exact Sig. (2-sided) Exact Sig. (1-sided) .036 .020

.027 189 a. Computed only for a 2x2 table b. 0 cells (.0%) have expected count less than 5. The minimum expected count is 23.10. 25,2% dari 115 ibu yg TIDAK merokok, 29 di antaranya melahirkan bayi dg BBLR 40,5% dari 74 ibu yg MEROKOK, 30 di antaranya melahirkan bayi dg BBLR Penentuan uji statistik perhatikan footnote Expected<5 20% sel 20% sel Tabel 2x2 Tabel >2x2 CC Pearson TIDAK BOLEH jk expected<1 Fisher Collaps Alternatif: LR Chi Square 1. Pearson chi Square: digunakan bila asumsi chi square

terpenuhi (tidak boleh ada nilai expected < 1 dan nilai Expected < 5 lebih dari 20%), jika nilai expectasi yang terlalu kecil, akan mengakibatkan nilai Chi Square >> sehingga peluang menolak Ho semakin besar 2. Continuity Corection: digunakan khusus untuk tabel 2x2 3. Likelihood Ratio: digunakan bila sampel penelitian kecil dan mengantiipasi bila tabel tidak bisa di kolaps berdasarkan pertimbangan substansi 4. Fisher Exact test : digunakan apabila asumsi chi square tidak terpenuhi pada tabel 2x2 5. Linier-by linier: menguji koefisien korelasi pearson Ho: p bblr|rokok = p bblr|tidak = 0,05 Uji Chi- Square dg CC p=0,04 Keputusan: p < maka Ho ditolak Kesimpulan: terdapat perbedaan bermakna proporsi BBLR antara kelompok ibu yg MEROKOK (40,5%) & TIDAK merokok (25,2%)

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