SOALl
PT Un~klenger
yang memproduksi mie instant selama ini menjual mie dalam 2 rasa yaitu KARl
AYAM dan GORENG PEDAS. Untuk mengetahui apakah ada perbedaan omset penjualan
kedua rasa tersebut di Malang Raya, Manajer Penjualan PT Unit~nger mengambil sampel amset penjualan dari 2 kota Malang Raya yaitu
Malang dan Batu. dengan pengamatan yang
dilakukan selama 14 han, diperoleh data Ilasil sbb :
Harl ke |
KARIAYAM |
GORENG PEDAS |
KOTA |
1
|
250
|
302
|
BATU
|
2
|
255
|
312
|
BATU
|
3
|
254
|
295
|
MALANG
|
4
|
275
|
225
|
BATU
|
5
|
255
|
245
|
MALANG
|
6
|
275
|
280
|
MALANG
|
7
|
244
|
215
|
BATU
|
8
|
312
|
350
|
MALANG
|
9
|
210
|
205
|
MALANG
|
10
|
245
|
246
|
BATU
|
11
|
178
|
174
|
MALANG
|
12
|
295
|
297
|
BATU
|
13
|
425
|
420
|
MALANG
|
14
|
244
|
225
|
BATU
|
ASUMSI : Data berdistribusi Normal, gunakan aHa 0,05 Varians
diansumsikan sama
ON THE JOB :
1.
Tentukan formulasi HO dan H1
2.
Ekspor
hasil uji SPSS ke dalam MS Word
3.
Berikan kesimpulan
T-TEST GROUPS=KOTA(1 2)
/MISSING=ANALYSIS
/VARIABLES=KARIAYAM GODAS
/CRITERIA=CI(.95).
T-Test
Notes |
||
Output
Created |
19-APR-2016
16:13:49 |
|
Comments |
|
|
Input |
Active
Dataset |
DataSet2 |
Filter |
<none> |
|
Weight |
<none> |
|
Split
File |
<none> |
|
N of Rows
in Working Data File |
14 |
|
Missing
Value Handling |
Definition
of Missing |
User
defined missing values are treated as missing. |
Cases
Used |
Statistics
for each analysis are based on the cases with no missing or out-of-range data
for any variable in the analysis. |
|
Syntax |
T-TEST
GROUPS=KOTA(1 2) /MISSING=ANALYSIS /VARIABLES=KARIAYAM GODAS /CRITERIA=CI(.95). |
|
Resources |
Processor
Time |
00:00:00.05 |
Elapsed
Time |
00:00:00.08 |
Group Statistics |
|||||
|
KOTA |
N |
Mean |
Std.
Deviation |
Std.
Error Mean |
KARIAYAM |
BATU |
7 |
258.2857 |
19.54238 |
7.38633 |
MALANG |
7 |
272.7143 |
79.90351 |
30.20069 |
|
GODAS |
BATU |
7 |
260.2857 |
41.84780 |
15.81698 |
MALANG |
7 |
281.2857 |
84.45850 |
31.92231 |
Independent Samples Test |
|
|||||
|
Levene's
Test for Equality of Variances |
t-test
for Equality of Means |
|
|||
F |
Sig. |
t |
df |
|||
KARIAYAM |
Equal
variances assumed |
3.865 |
.073 |
-.464 |
12 |
|
Equal
variances not assumed |
|
|
-.464 |
6.715 |
|
|
GODAS |
Equal
variances assumed |
1.810 |
.203 |
-.589 |
12 |
|
Equal
variances not assumed |
|
|
-.589 |
8.779 |
|
Independent Samples Test |
|
||||
|
t-test
for Equality of Means |
|
|||
Sig.
(2-tailed) |
Mean
Difference |
Std.
Error Difference |
|||
KARIAYAM |
Equal
variances assumed |
.651 |
-14.42857 |
31.09083 |
|
Equal
variances not assumed |
.657 |
-14.42857 |
31.09083 |
|
|
GODAS |
Equal
variances assumed |
.566 |
-21.00000 |
35.62599 |
|
Equal
variances not assumed |
.570 |
-21.00000 |
35.62599 |
|
Independent Samples Test |
|||
|
t-test
for Equality of Means |
||
95%
Confidence Interval of the Difference |
|||
Lower |
Upper |
||
KARIAYAM |
Equal
variances assumed |
-82.16966 |
53.31252 |
Equal
variances not assumed |
-88.58341 |
59.72627 |
|
GODAS |
Equal
variances assumed |
-98.62236 |
56.62236 |
Equal
variances not assumed |
-101.90251 |
59.90251 |
Independent
samplety test
H0
= tidak ada perbedaan omset
H1 = ada perbedaan omset
Alfa
= 0.05
H0
ditolak jika pval < alfa
Tinggi
0.073
> sisa tk kepercayaan
0.073
> 0.05
Berat
0.203
> sisa tk kepercayaan
0.203
> 0.05
Kesimpulan
statistic :
Karena
p value tinggi badan = 0.073 >
alfa maka h0 diterima yang berarti
tidak ada perbedaan omset penjualan
Karena
p value berat badan = 0.203 > alfa maka h0 diterima yang berarti tidak ada perbedaan omset
penjualan
Kesimpulan
penelitian :
Tidak
ada perbedaan omset penjualan antara mie instan rasa kari ayam dan rasa goring
pedas
SOAL 2
Hasan adalah seorang sales di sebuah perusahaan roti.
Menurut data yang didapat Hasan mampu menjual
roti rasa durian sebanyak 320 buah. Manajer penjualan menganggap penjualan Hasan
berbeda dengan rekan-rekannya karena Hasan adalah pna dan berpendidikan SMA. Benarkah pernyataan seperti itu?
Data mentah sbb .
Pendidikan
|
Gender
|
Kacang
|
Durian
|
Coklat |
Susu |
Nanas
|
1 |
0 |
250 |
300 |
298 |
325 |
100 |
1 |
1 |
234 |
320 |
254 |
312 |
150 |
1 |
1 |
220 |
324 |
315 |
450 |
60 |
1 |
0 |
245 |
315 |
387 |
500 |
94 |
1 |
1 |
281 |
400 |
200 |
268 |
65 |
1 |
0 |
220 |
420 |
145 |
351 |
102 |
2 |
1 |
256 |
398 |
256 |
245 |
94 |
2 |
1 |
238 |
375 |
200 |
221 |
95 |
2 |
1 |
210 |
364 |
214 |
621 |
64 |
2 |
1 |
310 |
325 |
269 |
235 |
120 |
2 |
0 |
287 |
410 |
254 |
214 |
113 |
2 |
0 |
254 |
425 |
225 |
230 |
111 |
Variabel
Vtew
Name
|
label |
Value
|
Pendidikan
|
Tk. Pendidikan |
1 = SMA |
|
|
2= SMP |
Gender
|
Jenis Kelamll |
1 =
Pria |
|
|
O=Wanka |
Kacang
|
Jenis
Roti yang di Jual |
|
Durian
|
|
|
Coklat |
|
|
Susu
|
|
|
Nanas
|
|
|
ASUMSI
: Data berdistribusi Normal, gunakan aHa 0,05
ON THE JOB:
1.
Tentukan formulasi HO dan H1
2.
Ekspo<
hasil uji SPSS ke dalam MS Word
3.
Berikan kesimpulan
GLM KACANG DURIAN COKLAT SUSU NANAS BY PENDIDIKAN GENDER
/METHOD=SSTYPE(3)
/INTERCEPT=INCLUDE
/POSTHOC=PENDIDIKAN(TUKEY)
/PLOT=PROFILE(PENDIDIKAN*GENDER)
/EMMEANS=TABLES(PENDIDIKAN)
/EMMEANS=TABLES(GENDER)
/EMMEANS=TABLES(PENDIDIKAN*GENDER)
/PRINT=DESCRIPTIVE
/CRITERIA=ALPHA(.05)
/DESIGN= PENDIDIKAN GENDER PENDIDIKAN*GENDER.
General Linear Model
Notes |
||
Output
Created |
19-APR-2016
17:44:37 |
|
Comments |
|
|
Input |
Active
Dataset |
DataSet0 |
Filter |
<none> |
|
Weight |
<none> |
|
Split
File |
<none> |
|
N of Rows
in Working Data File |
12 |
|
Missing
Value Handling |
Definition
of Missing |
User-defined
missing values are treated as missing. |
Cases
Used |
Statistics
are based on all cases with valid data for all variables in the model. |
|
Syntax |
GLM
KACANG DURIAN COKLAT SUSU NANAS BY PENDIDIKAN GENDER /METHOD=SSTYPE(3) /INTERCEPT=INCLUDE /POSTHOC=PENDIDIKAN(TUKEY) /PLOT=PROFILE(PENDIDIKAN*GENDER) /EMMEANS=TABLES(PENDIDIKAN) /EMMEANS=TABLES(GENDER) /EMMEANS=TABLES(PENDIDIKAN*GENDER) /PRINT=DESCRIPTIVE /CRITERIA=ALPHA(.05) /DESIGN= PENDIDIKAN GENDER
PENDIDIKAN*GENDER. |
|
Resources |
Processor
Time |
00:00:01,02 |
Elapsed
Time |
00:00:00,97 |
Between-Subjects Factors |
|||
|
Value
Label |
N |
|
PENDIDIKAN |
1 |
SMA |
6 |
2 |
SMP |
6 |
|
GENDER |
0 |
WANITA |
5 |
1 |
PRIA |
7 |
Descriptive Statistics |
|||||
|
PENDIDIKAN |
GENDER |
Mean |
Std.
Deviation |
N |
KACANG |
SMA |
WANITA |
238,33 |
16,073 |
3 |
PRIA |
245,00 |
31,953 |
3 |
||
Total |
241,67 |
22,914 |
6 |
||
SMP |
WANITA |
270,50 |
23,335 |
2 |
|
PRIA |
228,50 |
64,112 |
4 |
||
Total |
242,50 |
55,186 |
6 |
||
Total |
WANITA |
251,20 |
23,994 |
5 |
|
PRIA |
235,57 |
49,732 |
7 |
||
Total |
242,08 |
40,289 |
12 |
||
DURIAN |
SMA |
WANITA |
345,00 |
65,383 |
3 |
PRIA |
348,00 |
45,078 |
3 |
||
Total |
346,50 |
50,254 |
6 |
||
SMP |
WANITA |
417,50 |
10,607 |
2 |
|
PRIA |
365,50 |
30,490 |
4 |
||
Total |
382,83 |
36,074 |
6 |
||
Total |
WANITA |
374,00 |
61,176 |
5 |
|
PRIA |
358,00 |
35,067 |
7 |
||
Total |
364,67 |
45,820 |
12 |
||
COKLAT |
SMA |
WANITA |
276,67 |
122,402 |
3 |
PRIA |
256,33 |
57,535 |
3 |
||
Total |
266,50 |
86,262 |
6 |
||
SMP |
WANITA |
239,50 |
20,506 |
2 |
|
PRIA |
234,75 |
32,979 |
4 |
||
Total |
236,33 |
27,252 |
6 |
||
Total |
WANITA |
261,80 |
89,503 |
5 |
|
PRIA |
244,00 |
42,194 |
7 |
||
Total |
251,42 |
62,993 |
12 |
||
SUSU |
SMA |
WANITA |
392,00 |
94,430 |
3 |
PRIA |
343,33 |
94,960 |
3 |
||
Total |
367,67 |
88,793 |
6 |
||
SMP |
WANITA |
222,00 |
11,314 |
2 |
|
PRIA |
330,50 |
193,917 |
4 |
||
Total |
294,33 |
160,397 |
6 |
||
Total |
WANITA |
324,00 |
114,719 |
5 |
|
PRIA |
336,00 |
147,833 |
7 |
||
Total |
331,00 |
129,401 |
12 |
||
NANAS |
SMA |
WANITA |
98,67 |
4,163 |
3 |
PRIA |
91,67 |
50,580 |
3 |
||
Total |
95,17 |
32,326 |
6 |
||
SMP |
WANITA |
112,00 |
1,414 |
2 |
|
PRIA |
93,25 |
22,911 |
4 |
||
Total |
99,50 |
20,226 |
6 |
||
Total |
WANITA |
104,00 |
7,906 |
5 |
|
PRIA |
92,57 |
33,406 |
7 |
||
Total |
97,33 |
25,808 |
12 |
Multivariate Testsa |
|||||
Effect |
Value |
F |
Hypothesis
df |
Error
df |
|
Intercept |
Pillai's
Trace |
,999 |
1238,492b |
5,000 |
4,000 |
Wilks'
Lambda |
,001 |
1238,492b |
5,000 |
4,000 |
|
Hotelling's
Trace |
1548,115 |
1238,492b |
5,000 |
4,000 |
|
Roy's
Largest Root |
1548,115 |
1238,492b |
5,000 |
4,000 |
|
PENDIDIKAN |
Pillai's
Trace |
,508 |
,828b |
5,000 |
4,000 |
Wilks'
Lambda |
,492 |
,828b |
5,000 |
4,000 |
|
Hotelling's
Trace |
1,034 |
,828b |
5,000 |
4,000 |
|
Roy's
Largest Root |
1,034 |
,828b |
5,000 |
4,000 |
|
GENDER |
Pillai's
Trace |
,605 |
1,224b |
5,000 |
4,000 |
Wilks'
Lambda |
,395 |
1,224b |
5,000 |
4,000 |
|
Hotelling's
Trace |
1,530 |
1,224b |
5,000 |
4,000 |
|
Roy's
Largest Root |
1,530 |
1,224b |
5,000 |
4,000 |
|
PENDIDIKAN
* GENDER |
Pillai's
Trace |
,465 |
,695b |
5,000 |
4,000 |
Wilks'
Lambda |
,535 |
,695b |
5,000 |
4,000 |
|
Hotelling's
Trace |
,869 |
,695b |
5,000 |
4,000 |
|
Roy's
Largest Root |
,869 |
,695b |
5,000 |
4,000 |
Multivariate Testsa |
||
Effect |
Sig. |
|
Intercept |
Pillai's
Trace |
,000 |
Wilks'
Lambda |
,000 |
|
Hotelling's
Trace |
,000 |
|
Roy's
Largest Root |
,000 |
|
PENDIDIKAN |
Pillai's
Trace |
,589 |
Wilks'
Lambda |
,589 |
|
Hotelling's
Trace |
,589 |
|
Roy's
Largest Root |
,589 |
|
GENDER |
Pillai's
Trace |
,435 |
Wilks'
Lambda |
,435 |
|
Hotelling's
Trace |
,435 |
|
Roy's
Largest Root |
,435 |
|
PENDIDIKAN
* GENDER |
Pillai's
Trace |
,655 |
Wilks'
Lambda |
,655 |
|
Hotelling's
Trace |
,655 |
|
Roy's
Largest Root |
,655 |
a.
Design: Intercept + PENDIDIKAN + GENDER + PENDIDIKAN * GENDER |
b. Exact
statistic |
Tests of Between-Subjects Effects |
||||||
Source |
Dependent
Variable |
Type
III Sum of Squares |
df |
Mean
Square |
F |
Sig. |
Corrected
Model |
KACANG |
2420,750a |
3 |
806,917 |
,418 |
,745 |
DURIAN |
7579,167b |
3 |
2526,389 |
1,303 |
,339 |
|
COKLAT |
3380,333c |
3 |
1126,778 |
,224 |
,877 |
|
SUSU |
35382,333d |
3 |
11794,111 |
,634 |
,614 |
|
NANAS |
598,583e |
3 |
199,528 |
,237 |
,868 |
|
Intercept |
KACANG |
681161,490 |
1 |
681161,490 |
353,067 |
,000 |
DURIAN |
1537818,353 |
1 |
1537818,353 |
792,920 |
,000 |
|
COKLAT |
716154,750 |
1 |
716154,750 |
142,276 |
,000 |
|
SUSU |
1170716,255 |
1 |
1170716,255 |
62,938 |
,000 |
|
NANAS |
110460,828 |
1 |
110460,828 |
131,343 |
,000 |
|
PENDIDIKAN |
KACANG |
173,255 |
1 |
173,255 |
,090 |
,772 |
DURIAN |
5717,647 |
1 |
5717,647 |
2,948 |
,124 |
|
COKLAT |
2436,397 |
1 |
2436,397 |
,484 |
,506 |
|
SUSU |
23596,255 |
1 |
23596,255 |
1,269 |
,293 |
|
NANAS |
157,064 |
1 |
157,064 |
,187 |
,677 |
|
GENDER |
KACANG |
881,255 |
1 |
881,255 |
,457 |
,518 |
DURIAN |
1694,824 |
1 |
1694,824 |
,874 |
,377 |
|
COKLAT |
444,123 |
1 |
444,123 |
,088 |
,774 |
|
SUSU |
2527,078 |
1 |
2527,078 |
,136 |
,722 |
|
NANAS |
468,044 |
1 |
468,044 |
,557 |
,477 |
|
PENDIDIKAN
* GENDER |
KACANG |
1671,843 |
1 |
1671,843 |
,867 |
,379 |
DURIAN |
2135,294 |
1 |
2135,294 |
1,101 |
,325 |
|
COKLAT |
171,417 |
1 |
171,417 |
,034 |
,858 |
|
SUSU |
17436,255 |
1 |
17436,255 |
,937 |
,361 |
|
NANAS |
97,456 |
1 |
97,456 |
,116 |
,742 |
|
Error |
KACANG |
15434,167 |
8 |
1929,271 |
|
|
DURIAN |
15515,500 |
8 |
1939,438 |
|
|
|
COKLAT |
40268,583 |
8 |
5033,573 |
|
|
|
SUSU |
148807,667 |
8 |
18600,958 |
|
|
|
NANAS |
6728,083 |
8 |
841,010 |
|
|
|
Total |
KACANG |
721107,000 |
12 |
|
|
|
DURIAN |
1618876,000 |
12 |
|
|
|
|
COKLAT |
802173,000 |
12 |
|
|
|
|
SUSU |
1498922,000 |
12 |
|
|
|
|
NANAS |
121012,000 |
12 |
|
|
|
|
Corrected
Total |
KACANG |
17854,917 |
11 |
|
|
|
DURIAN |
23094,667 |
11 |
|
|
|
|
COKLAT |
43648,917 |
11 |
|
|
|
|
SUSU |
184190,000 |
11 |
|
|
|
|
NANAS |
7326,667 |
11 |
|
|
|
a. R
Squared = ,136 (Adjusted R Squared = -,189) |
b. R
Squared = ,328 (Adjusted R Squared = ,076) |
c. R
Squared = ,077 (Adjusted R Squared = -,269) |
d. R
Squared = ,192 (Adjusted R Squared = -,111) |
e. R
Squared = ,082 (Adjusted R Squared = -,263) |
Estimated Marginal Means
1. PENDIDIKAN |
|||||
Dependent
Variable |
PENDIDIKAN |
Mean |
Std.
Error |
95%
Confidence Interval |
|
Lower
Bound |
Upper
Bound |
||||
KACANG |
SMA |
241,667 |
17,932 |
200,316 |
283,017 |
SMP |
249,500 |
19,019 |
205,641 |
293,359 |
|
DURIAN |
SMA |
346,500 |
17,979 |
305,041 |
387,959 |
SMP |
391,500 |
19,069 |
347,526 |
435,474 |
|
COKLAT |
SMA |
266,500 |
28,964 |
199,708 |
333,292 |
SMP |
237,125 |
30,721 |
166,282 |
307,968 |
|
SUSU |
SMA |
367,667 |
55,679 |
239,270 |
496,063 |
SMP |
276,250 |
59,057 |
140,065 |
412,435 |
|
NANAS |
SMA |
95,167 |
11,839 |
67,865 |
122,468 |
SMP |
102,625 |
12,557 |
73,667 |
131,583 |
2. GENDER |
|||||
Dependent
Variable |
GENDER |
Mean |
Std.
Error |
95%
Confidence Interval |
|
Lower
Bound |
Upper
Bound |
||||
KACANG |
WANITA |
254,417 |
20,048 |
208,185 |
300,648 |
PRIA |
236,750 |
16,774 |
198,070 |
275,430 |
|
DURIAN |
WANITA |
381,250 |
20,101 |
334,897 |
427,603 |
PRIA |
356,750 |
16,818 |
317,968 |
395,532 |
|
COKLAT |
WANITA |
258,083 |
32,383 |
183,408 |
332,759 |
PRIA |
245,542 |
27,094 |
183,064 |
308,020 |
|
SUSU |
WANITA |
307,000 |
62,251 |
163,449 |
450,551 |
PRIA |
336,917 |
52,083 |
216,813 |
457,020 |
|
NANAS |
WANITA |
105,333 |
13,237 |
74,809 |
135,857 |
PRIA |
92,458 |
11,075 |
66,920 |
117,996 |
3. PENDIDIKAN * GENDER |
|||||
Dependent
Variable |
PENDIDIKAN |
GENDER |
Mean |
Std.
Error |
95%
Confidence Interval |
Lower
Bound |
|||||
KACANG |
SMA |
WANITA |
238,333 |
25,359 |
179,855 |
PRIA |
245,000 |
25,359 |
186,522 |
||
SMP |
WANITA |
270,500 |
31,059 |
198,879 |
|
PRIA |
228,500 |
21,962 |
177,856 |
||
DURIAN |
SMA |
WANITA |
345,000 |
25,426 |
286,368 |
PRIA |
348,000 |
25,426 |
289,368 |
||
SMP |
WANITA |
417,500 |
31,140 |
345,690 |
|
PRIA |
365,500 |
22,020 |
314,723 |
||
COKLAT |
SMA |
WANITA |
276,667 |
40,962 |
182,209 |
PRIA |
256,333 |
40,962 |
161,876 |
||
SMP |
WANITA |
239,500 |
50,168 |
123,813 |
|
PRIA |
234,750 |
35,474 |
152,947 |
||
SUSU |
SMA |
WANITA |
392,000 |
78,742 |
210,420 |
PRIA |
343,333 |
78,742 |
161,754 |
||
SMP |
WANITA |
222,000 |
96,439 |
-,389 |
|
PRIA |
330,500 |
68,193 |
173,247 |
||
NANAS |
SMA |
WANITA |
98,667 |
16,743 |
60,057 |
PRIA |
91,667 |
16,743 |
53,057 |
||
SMP |
WANITA |
112,000 |
20,506 |
64,713 |
|
PRIA |
93,250 |
14,500 |
59,813 |
3. PENDIDIKAN * GENDER |
|||
Dependent
Variable |
PENDIDIKAN |
GENDER |
95%
Confidence Interval |
Upper
Bound |
|||
KACANG |
SMA |
WANITA |
296,812 |
PRIA |
303,478 |
||
SMP |
WANITA |
342,121 |
|
PRIA |
279,144 |
||
DURIAN |
SMA |
WANITA |
403,632 |
PRIA |
406,632 |
||
SMP |
WANITA |
489,310 |
|
PRIA |
416,277 |
||
COKLAT |
SMA |
WANITA |
371,124 |
PRIA |
350,791 |
||
SMP |
WANITA |
355,187 |
|
PRIA |
316,553 |
||
SUSU |
SMA |
WANITA |
573,580 |
PRIA |
524,913 |
||
SMP |
WANITA |
444,389 |
|
PRIA |
487,753 |
||
NANAS |
SMA |
WANITA |
137,277 |
PRIA |
130,277 |
||
SMP |
WANITA |
159,287 |
|
PRIA |
126,687 |
Profile Plots
KACANG
DURIAN
COKLAT
SUSU
NANAS
SAVE OUTFILE='C:\Users\richa\Documents\TWO WAY ANOVA (1).sav'
/COMPRESSED.
H0 = TIDAK ADA PERBEDAAN
H1 = ADA PERBEDAAN
- Two-way
anova
- P
value semua jenis roti > alfa maka H0 diterima yang berarti tidak ada
perbedaan antara tingkat pendidikan dan jenis gender untuk semua penjualan
roti
SOAL3
Seorang
manajer ingil mengetahui apakah ada perbedaan tingkat stress pada 16 karyawannya dengan menempatkan 8 orang pada ruangan
di lantai bawah (lantai1) dan 8 orang berikutnya di ruang Lantai alas (Lantai
9), berdasarkan kuesioner diperoleh data sebagai berikut :
|
Score Stress |
Lokasl
Lont.1 |
1. |
67 |
Bawah
|
2. |
65 |
Bawah
|
3. |
74 |
Bawah
|
4. |
81 |
Bawah
|
5. |
74 |
Bawah
|
6. |
62 |
Bawah
|
7. |
74 |
Bawah |
8. |
76 |
Bawah |
9. |
82 |
Atas |
10. |
78 |
Alas |
11. |
85 |
Alas |
12. |
68 |
Alas |
13. |
84 |
Alas |
14. |
82 |
Alas |
15. |
91 |
Alas |
16. |
86 |
Alas |
Keterangan
: .75 Stress
< 75 Nonnal
ASUMSI
: Data berdistribusi normal, gunakan alfa 0.05
ON THE JOB:
1. Tentukan formulasi HO dan H1
2. Ekspor hasil uji SPSS kedalam
MsWord
3. Berikan kesimpulan
DATASET ACTIVATE DataSet5.
T-TEST PAIRS=ATAS WITH BAWAH (PAIRED)
/CRITERIA=CI(.9500)
/MISSING=ANALYSIS.
T-Test
Notes |
||
Output
Created |
19-APR-2016
18:28:52 |
|
Comments |
|
|
Input |
Active
Dataset |
DataSet5 |
Filter |
<none> |
|
Weight |
<none> |
|
Split
File |
<none> |
|
N of Rows
in Working Data File |
8 |
|
Missing
Value Handling |
Definition
of Missing |
User
defined missing values are treated as missing. |
Cases
Used |
Statistics
for each analysis are based on the cases with no missing or out-of-range data
for any variable in the analysis. |
|
Syntax |
T-TEST
PAIRS=ATAS WITH BAWAH (PAIRED) /CRITERIA=CI(.9500) /MISSING=ANALYSIS. |
|
Resources |
Processor
Time |
00:00:00.02 |
Elapsed
Time |
00:00:00.13 |
[DataSet5]
Paired Samples Statistics |
|||||
|
Mean |
N |
Std.
Deviation |
Std.
Error Mean |
|
Pair 1 |
ATAS |
71.6250 |
8 |
6.34570 |
2.24354 |
BAWAH |
82.0000 |
8 |
6.78233 |
2.39792 |
Paired Samples Correlations |
||||
|
N |
Correlation |
Sig. |
|
Pair 1 |
ATAS
& BAWAH |
8 |
-.179 |
.671 |
Paired Samples Test |
|||||
|
Paired
Differences |
||||
Mean |
Std.
Deviation |
Std.
Error Mean |
95%
Confidence Interval of the Difference |
||
Lower |
|||||
Pair 1 |
ATAS -
BAWAH |
-10.37500 |
10.08446 |
3.56540 |
-18.80582 |
Paired Samples Test |
|||||
|
Paired
Differences |
t |
df |
Sig.
(2-tailed) |
|
95%
Confidence Interval of the Difference |
|||||
Upper |
|||||
Pair 1 |
ATAS -
BAWAH |
-1.94418 |
-2.910 |
7 |
.023 |
Paired
sample test
H0
= tidak ada perbedaan tingkat stress
H1
= ada perbedaan tingkat stress
Alfa
= 0.05
H0
ditolak jika pval < alfa
0.023
< sisa tk kepercayaan
0.023
< 0.05
Kesimpulan
statistic :
Karena
p value = 0.023 < alfa maka H0
ditolak yang berarti ada perbedaan tingkat stress antara karyawan lantai bawah
dengan karyawan lantai atas
Kesimpulan
penelitian :
Perbedaan
tingkat stress pada karyawan dikarenakan perbedaan penempatan ruang kerja
SOAL4
Seorang Mahasiswa membuat Karya Tulis Ifmiah
dengan judul ~ Hubungan Biaya Promosi dan Biaya Distribusi dengan Volume
Penjualan ". Pada Rumah Makan Takasimura di kota Malang.
Variabel bebas :
a. Variabel Xl : 8iaya Promosi
b. Variabel X2 : Biaya Distribusi
c. Variabel terikat : Volume Penjualan (Y)
Berikut Dala yang diperoleh :
Xl |
X2 |
Y |
500 |
840 |
1090 |
640 |
980 |
1300 |
720 |
1060 |
1420 |
890 |
1230 |
1675 |
1010 |
1350 |
1855 |
1120 |
1460 |
2020 |
1250 |
1590 |
2215 |
1302 |
1642 |
2293 |
1580 |
1920 |
2710 |
1720 |
2100 |
2960 |
1900 |
2240 |
3190 |
2010 |
2350 |
3355 |
2090 |
2430 |
3475 |
2201 |
2541 |
3642 |
2490 |
2750 |
3995 |
2969 |
2901 |
4386 |
Asumsi : Data berdistribusi normal gunakan alfa 0.05
ON THE JOB:
1. Tentukan formulasi HO dan H1
2. Apakah ada korelasi antar variabel ? Jika iya tentukan persamaan regresinya
3. Expo'
hasil uji SPSS dalam word
4. Berikan Kesimpulan
DATASET ACTIVATE DataSet3.
NEW FILE.
DATASET NAME DataSet5 WINDOW=FRONT.
DATASET ACTIVATE DataSet4.
CORRELATIONS
/VARIABLES=BIAYAPROMOSI BIAYAADMINISTRASI VOLUMEPENJUALAN
/PRINT=TWOTAIL NOSIG
/STATISTICS DESCRIPTIVES
/MISSING=PAIRWISE.
Correlations
Notes |
||
Output
Created |
19-APR-2016
18:00:31 |
|
Comments |
|
|
Input |
Active
Dataset |
DataSet4 |
Filter |
<none> |
|
Weight |
<none> |
|
Split
File |
<none> |
|
N of Rows
in Working Data File |
16 |
|
Missing
Value Handling |
Definition
of Missing |
User-defined
missing values are treated as missing. |
Cases
Used |
Statistics
for each pair of variables are based on all the cases with valid data for
that pair. |
|
Syntax |
CORRELATIONS /VARIABLES=BIAYAPROMOSI BIAYAADMINISTRASI
VOLUMEPENJUALAN /PRINT=TWOTAIL NOSIG /STATISTICS DESCRIPTIVES /MISSING=PAIRWISE. |
|
Resources |
Processor
Time |
00:00:00.05 |
Elapsed
Time |
00:00:00.22 |
Descriptive Statistics |
|||
|
Mean |
Std.
Deviation |
N |
BIAYAPROMOSI |
1524.5000 |
714.10373 |
16 |
BIAYAADMINISTRASI |
1836.5000 |
657.95289 |
16 |
VOLUMEPENJUALAN |
2598.8125 |
1013.21391 |
16 |
Correlations |
||||
|
BIAYAPROMOSI |
BIAYAADMINISTRASI |
VOLUMEPENJUALAN |
|
BIAYAPROMOSI |
Pearson
Correlation |
1 |
.992** |
.997** |
Sig.
(2-tailed) |
|
.000 |
.000 |
|
N |
16 |
16 |
16 |
|
BIAYAADMINISTRASI |
Pearson
Correlation |
.992** |
1 |
.999** |
Sig.
(2-tailed) |
.000 |
|
.000 |
|
N |
16 |
16 |
16 |
|
VOLUMEPENJUALAN |
Pearson
Correlation |
.997** |
.999** |
1 |
Sig.
(2-tailed) |
.000 |
.000 |
|
|
N |
16 |
16 |
16 |
**.
Correlation is significant at the 0.01 level (2-tailed). |
NONPAR CORR
/VARIABLES=BIAYAPROMOSI BIAYAADMINISTRASI VOLUMEPENJUALAN
/PRINT=BOTH TWOTAIL NOSIG
/MISSING=PAIRWISE.
Nonparametric Correlations
Notes |
||
Output
Created |
19-APR-2016
18:00:32 |
|
Comments |
|
|
Input |
Active
Dataset |
DataSet4 |
Filter |
<none> |
|
Weight |
<none> |
|
Split
File |
<none> |
|
N of Rows
in Working Data File |
16 |
|
Missing
Value Handling |
Definition
of Missing |
User-defined
missing values are treated as missing. |
Cases
Used |
Statistics
for each pair of variables are based on all the cases with valid data for
that pair. |
|
Syntax |
NONPAR
CORR /VARIABLES=BIAYAPROMOSI BIAYAADMINISTRASI
VOLUMEPENJUALAN /PRINT=BOTH TWOTAIL NOSIG /MISSING=PAIRWISE. |
|
Resources |
Processor
Time |
00:00:00.02 |
Elapsed
Time |
00:00:00.05 |
|
Number of
Cases Allowed |
142987
casesa |
a. Based
on availability of workspace memory |
Correlations |
||||
|
BIAYAPROMOSI |
BIAYAADMINISTRASI |
||
Kendall's
tau_b |
BIAYAPROMOSI |
Correlation
Coefficient |
1.000 |
1.000** |
Sig. (2-tailed) |
. |
. |
||
N |
16 |
16 |
||
BIAYAADMINISTRASI |
Correlation
Coefficient |
1.000** |
1.000 |
|
Sig.
(2-tailed) |
. |
. |
||
N |
16 |
16 |
||
VOLUMEPENJUALAN |
Correlation
Coefficient |
1.000** |
1.000** |
|
Sig.
(2-tailed) |
. |
. |
||
N |
16 |
16 |
||
Spearman's
rho |
BIAYAPROMOSI |
Correlation
Coefficient |
1.000 |
1.000** |
Sig.
(2-tailed) |
. |
. |
||
N |
16 |
16 |
||
BIAYAADMINISTRASI |
Correlation
Coefficient |
1.000** |
1.000 |
|
Sig.
(2-tailed) |
. |
. |
||
N |
16 |
16 |
||
VOLUMEPENJUALAN |
Correlation
Coefficient |
1.000** |
1.000** |
|
Sig. (2-tailed) |
. |
. |
||
N |
16 |
16 |
Correlations |
|||
|
VOLUMEPENJUALAN |
||
Kendall's
tau_b |
BIAYAPROMOSI |
Correlation
Coefficient |
1.000** |
Sig.
(2-tailed) |
. |
||
N |
16 |
||
BIAYAADMINISTRASI |
Correlation
Coefficient |
1.000** |
|
Sig.
(2-tailed) |
. |
||
N |
16 |
||
VOLUMEPENJUALAN |
Correlation
Coefficient |
1.000 |
|
Sig.
(2-tailed) |
. |
||
N |
16 |
||
Spearman's
rho |
BIAYAPROMOSI |
Correlation
Coefficient |
1.000** |
Sig.
(2-tailed) |
. |
||
N |
16 |
||
BIAYAADMINISTRASI |
Correlation
Coefficient |
1.000** |
|
Sig.
(2-tailed) |
. |
||
N |
16 |
||
VOLUMEPENJUALAN |
Correlation
Coefficient |
1.000 |
|
Sig.
(2-tailed) |
. |
||
N |
16 |
**.
Correlation is significant at the 0.01 level (2-tailed). |
CORRELATIONS
/VARIABLES=BIAYAPROMOSI BIAYAADMINISTRASI VOLUMEPENJUALAN
/PRINT=TWOTAIL NOSIG
/STATISTICS DESCRIPTIVES
/MISSING=PAIRWISE.
Correlations
Notes |
||
Output
Created |
19-APR-2016
18:23:21 |
|
Comments |
|
|
Input |
Active
Dataset |
DataSet4 |
Filter |
<none> |
|
Weight |
<none> |
|
Split
File |
<none> |
|
N of Rows
in Working Data File |
16 |
|
Missing
Value Handling |
Definition
of Missing |
User-defined
missing values are treated as missing. |
Cases
Used |
Statistics
for each pair of variables are based on all the cases with valid data for
that pair. |
|
Syntax |
CORRELATIONS /VARIABLES=BIAYAPROMOSI BIAYAADMINISTRASI
VOLUMEPENJUALAN /PRINT=TWOTAIL NOSIG /STATISTICS DESCRIPTIVES /MISSING=PAIRWISE. |
|
Resources |
Processor
Time |
00:00:00.03 |
Elapsed
Time |
00:00:00.27 |
Descriptive Statistics |
|||
|
Mean |
Std.
Deviation |
N |
BIAYAPROMOSI |
1524.5000 |
714.10373 |
16 |
BIAYAADMINISTRASI |
1836.5000 |
657.95289 |
16 |
VOLUMEPENJUALAN |
2598.8125 |
1013.21391 |
16 |
Correlations |
||||
|
BIAYAPROMOSI |
BIAYAADMINISTRASI |
VOLUMEPENJUALAN |
|
BIAYAPROMOSI |
Pearson
Correlation |
1 |
.992** |
.997** |
Sig.
(2-tailed) |
|
.000 |
.000 |
|
N |
16 |
16 |
16 |
|
BIAYAADMINISTRASI |
Pearson
Correlation |
.992** |
1 |
.999** |
Sig.
(2-tailed) |
.000 |
|
.000 |
|
N |
16 |
16 |
16 |
|
VOLUMEPENJUALAN |
Pearson
Correlation |
.997** |
.999** |
1 |
Sig.
(2-tailed) |
.000 |
.000 |
|
|
N |
16 |
16 |
16 |
**.
Correlation is significant at the 0.01 level (2-tailed). |
NONPAR CORR
/VARIABLES=BIAYAPROMOSI BIAYAADMINISTRASI VOLUMEPENJUALAN
/PRINT=BOTH TWOTAIL NOSIG
/MISSING=PAIRWISE.
Nonparametric Correlations
Notes |
||
Output
Created |
19-APR-2016
18:23:21 |
|
Comments |
|
|
Input |
Active
Dataset |
DataSet4 |
Filter |
<none> |
|
Weight |
<none> |
|
Split
File |
<none> |
|
N of Rows
in Working Data File |
16 |
|
Missing
Value Handling |
Definition
of Missing |
User-defined
missing values are treated as missing. |
Cases
Used |
Statistics
for each pair of variables are based on all the cases with valid data for
that pair. |
|
Syntax |
NONPAR
CORR /VARIABLES=BIAYAPROMOSI BIAYAADMINISTRASI
VOLUMEPENJUALAN /PRINT=BOTH TWOTAIL NOSIG /MISSING=PAIRWISE. |
|
Resources |
Processor
Time |
00:00:00.03 |
Elapsed
Time |
00:00:00.10 |
|
Number of
Cases Allowed |
142987
casesa |
a. Based
on availability of workspace memory |
Correlations |
||||
|
BIAYAPROMOSI |
BIAYAADMINISTRASI |
||
Kendall's
tau_b |
BIAYAPROMOSI |
Correlation
Coefficient |
1.000 |
1.000** |
Sig. (2-tailed) |
. |
. |
||
N |
16 |
16 |
||
BIAYAADMINISTRASI |
Correlation
Coefficient |
1.000** |
1.000 |
|
Sig.
(2-tailed) |
. |
. |
||
N |
16 |
16 |
||
VOLUMEPENJUALAN |
Correlation
Coefficient |
1.000** |
1.000** |
|
Sig.
(2-tailed) |
. |
. |
||
N |
16 |
16 |
||
Spearman's
rho |
BIAYAPROMOSI |
Correlation
Coefficient |
1.000 |
1.000** |
Sig.
(2-tailed) |
. |
. |
||
N |
16 |
16 |
||
BIAYAADMINISTRASI |
Correlation
Coefficient |
1.000** |
1.000 |
|
Sig.
(2-tailed) |
. |
. |
||
N |
16 |
16 |
||
VOLUMEPENJUALAN |
Correlation
Coefficient |
1.000** |
1.000** |
|
Sig. (2-tailed) |
. |
. |
||
N |
16 |
16 |
Correlations |
|||
|
VOLUMEPENJUALAN |
||
Kendall's
tau_b |
BIAYAPROMOSI |
Correlation
Coefficient |
1.000** |
Sig.
(2-tailed) |
. |
||
N |
16 |
||
BIAYAADMINISTRASI |
Correlation
Coefficient |
1.000** |
|
Sig.
(2-tailed) |
. |
||
N |
16 |
||
VOLUMEPENJUALAN |
Correlation
Coefficient |
1.000 |
|
Sig.
(2-tailed) |
. |
||
N |
16 |
||
Spearman's
rho |
BIAYAPROMOSI |
Correlation
Coefficient |
1.000** |
Sig.
(2-tailed) |
. |
||
N |
16 |
||
BIAYAADMINISTRASI |
Correlation
Coefficient |
1.000** |
|
Sig.
(2-tailed) |
. |
||
N |
16 |
||
VOLUMEPENJUALAN |
Correlation
Coefficient |
1.000 |
|
Sig.
(2-tailed) |
. |
||
N |
16 |
**.
Correlation is significant at the 0.01 level (2-tailed). |
REGRESSION
/MISSING LISTWISE
/STATISTICS COEFF OUTS R ANOVA
/CRITERIA=PIN(.05) POUT(.10)
/NOORIGIN
/DEPENDENT BIAYAPROMOSI
/METHOD=ENTER BIAYAADMINISTRASI VOLUMEPENJUALAN
/SCATTERPLOT=(*SRESID ,*ZPRED)
/RESIDUALS NORMPROB(ZRESID).
Regression
Notes |
||
Output
Created |
19-APR-2016
18:24:48 |
|
Comments |
|
|
Input |
Active
Dataset |
DataSet4 |
Filter |
<none> |
|
Weight |
<none> |
|
Split
File |
<none> |
|
N of Rows
in Working Data File |
16 |
|
Missing
Value Handling |
Definition
of Missing |
User-defined
missing values are treated as missing. |
Cases
Used |
Statistics
are based on cases with no missing values for any variable used. |
|
Syntax |
REGRESSION /MISSING LISTWISE /STATISTICS COEFF OUTS R ANOVA /CRITERIA=PIN(.05) POUT(.10) /NOORIGIN /DEPENDENT BIAYAPROMOSI /METHOD=ENTER BIAYAADMINISTRASI
VOLUMEPENJUALAN /SCATTERPLOT=(*SRESID ,*ZPRED) /RESIDUALS NORMPROB(ZRESID). |
|
Resources |
Processor
Time |
00:00:05.26 |
Elapsed
Time |
00:00:09.32 |
|
Memory
Required |
1644
bytes |
|
Additional
Memory Required for Residual Plots |
560 bytes |
Variables Entered/Removeda |
|||
Model |
Variables
Entered |
Variables
Removed |
Method |
1 |
VOLUMEPENJUALAN,
BIAYAADMINISTRASIb |
. |
Enter |
a.
Dependent Variable: BIAYAPROMOSI |
b. All
requested variables entered. |
Model Summaryb |
||||
Model |
R |
R
Square |
Adjusted
R Square |
Std.
Error of the Estimate |
1 |
1.000a |
1.000 |
1.000 |
.26109 |
a.
Predictors: (Constant), VOLUMEPENJUALAN, BIAYAADMINISTRASI |
b.
Dependent Variable: BIAYAPROMOSI |
ANOVAa |
||||||
Model |
Sum
of Squares |
df |
Mean
Square |
F |
Sig. |
|
1 |
Regression |
7649161.114 |
2 |
3824580.557 |
56106094.070 |
.000b |
Residual |
.886 |
13 |
.068 |
|
|
|
Total |
7649162.000 |
15 |
|
|
|
a.
Dependent Variable: BIAYAPROMOSI |
b.
Predictors: (Constant), VOLUMEPENJUALAN, BIAYAADMINISTRASI |
Coefficientsa |
||||||
Model |
Unstandardized
Coefficients |
Standardized
Coefficients |
t |
Sig. |
||
B |
Std.
Error |
Beta |
||||
1 |
(Constant) |
-.418 |
.390 |
|
-1.073 |
.303 |
BIAYAADMINISTRASI |
-1.995 |
.002 |
-1.838 |
-874.771 |
.000 |
|
VOLUMEPENJUALAN |
1.996 |
.001 |
2.833 |
1348.193 |
.000 |
a.
Dependent Variable: BIAYAPROMOSI |
Residuals Statisticsa |
|||||
|
Minimum |
Maximum |
Mean |
Std.
Deviation |
N |
Predicted
Value |
500.0616 |
2969.0608 |
1524.5000 |
714.10369 |
16 |
Std.
Predicted Value |
-1.435 |
2.023 |
.000 |
1.000 |
16 |
Standard
Error of Predicted Value |
.069 |
.255 |
.105 |
.044 |
16 |
Adjusted
Predicted Value |
500.0805 |
2970.4019 |
1524.5873 |
714.28335 |
16 |
Residual |
-.82543 |
.34184 |
.00000 |
.24306 |
16 |
Std.
Residual |
-3.161 |
1.309 |
.000 |
.931 |
16 |
Stud.
Residual |
-3.517 |
1.458 |
-.061 |
1.068 |
16 |
Deleted
Residual |
-1.40195 |
.42396 |
-.08727 |
.46048 |
16 |
Stud.
Deleted Residual |
-15.348 |
1.532 |
-.801 |
3.918 |
16 |
Mahal.
Distance |
.108 |
13.413 |
1.875 |
3.166 |
16 |
Cook's
Distance |
.000 |
9.195 |
.651 |
2.291 |
16 |
Centered
Leverage Value |
.007 |
.894 |
.125 |
.211 |
16 |
a.
Dependent Variable: BIAYAPROMOSI |
Charts
Korelasi
regresi
H0 :
Tidak ada hubungan (Korelasi) antara biaya promosi, biaya distribusi dan
volume penjualan H1 :
Terdapat hubungan (Korelasi) antara biaya promosi, biaya distribusi dan
volume penjualan Jika
Angka Korelasi berkisar ke angka 0 berarti tidak ada korelasi dan jika ke
angka 1 berarti korelasinya sempurna. Tingkat
kepercayaan 95 % Tingkat
Signifikansi 5 % Jika P
value > 0,05 maka H0 diterima Jika P
value < 0,05 maka H0 di tolak ( jadi α = 0,05) KENDALL Kesimpulan
: P Value (0,00)< α (0,05), yang berarti H0 di tolak , berarti terdapat
hubungan antara biaya promosi, biaya distribusi dan volume penjualan SPEARMAN Kesimpulan
: P Value (0,00)< α (0,05), yang berarti H0 di tolak , berarti terdapat
hubungan antara biaya promosi, biaya distribusi dan volume penjualan Persamaan
regresi |
Y
= -1.995x-0.418
SOAL5
Suatu penelaian
ingin menyelidiki Ilasil penyuluhan yang menggunakan 4 metode. Metode I, II,
III. IV . Sampel diambil dan para mahasiswa, kemudian peniiaian dikelompokkan
menjadi 3 yaitu : nilai A, B, C. Apakah ada perbedaan metode penyuluhan berdasarkan hasil <Sari ketiga kategori nilai tersebut ?
Metod. |
Nliol |
|
|
Penyuluhan |
|
|
|
|
A |
B |
C; |
1 |
10 |
8 |
2 |
II |
8 |
6 |
6 |
III |
3 |
2 |
15 |
Keterangan :
Metode I : Demonstrasi
Metode II : Diskusi
Metode III : Ceramah
a = 0,05
ON THE JOB:
1. Tentukan formulasi HO dan H1
2. Ekspor hasil uji SPSS kedalam Ms.word
3. Berikan kesimpulan
HASIL:
ONEWAY Nilai BY Metode
/POLYNOMIAL=1
/STATISTICS DESCRIPTIVES HOMOGENEITY
/PLOT MEANS
/MISSING ANALYSIS
/POSTHOC=DUNCAN LSD ALPHA(0.05).
Oneway
Notes |
||
Output
Created |
19-APR-2016
16:58:42 |
|
Comments |
|
|
Input |
Active
Dataset |
DataSet0 |
Filter |
<none> |
|
Weight |
<none> |
|
Split
File |
<none> |
|
N of Rows
in Working Data File |
9 |
|
Missing
Value Handling |
Definition
of Missing |
User-defined
missing values are treated as missing. |
Cases
Used |
Statistics
for each analysis are based on cases with no missing data for any variable in
the analysis. |
|
Syntax |
ONEWAY
Nilai BY Metode /POLYNOMIAL=1 /STATISTICS DESCRIPTIVES HOMOGENEITY /PLOT MEANS /MISSING ANALYSIS /POSTHOC=DUNCAN LSD ALPHA(0.05). |
|
Resources |
Processor
Time |
00:00:01.62 |
Elapsed
Time |
00:00:01.75 |
[DataSet0]
Descriptives |
|||||||
Nilai |
|||||||
|
N |
Mean |
Std.
Deviation |
Std.
Error |
95%
Confidence Interval for Mean |
Minimum |
|
Lower
Bound |
Upper
Bound |
||||||
I |
3 |
6.67 |
4.163 |
2.404 |
-3.68 |
17.01 |
2 |
II |
3 |
6.67 |
1.155 |
.667 |
3.80 |
9.54 |
6 |
III |
3 |
6.67 |
7.234 |
4.177 |
-11.30 |
24.64 |
2 |
Total |
9 |
6.67 |
4.213 |
1.404 |
3.43 |
9.91 |
2 |
Descriptives |
|
|
Nilai |
|
|
|
Maximum |
|
I |
10 |
|
II |
8 |
|
III |
15 |
|
Total |
15 |
|
Test of Homogeneity of Variances |
|||
Nilai |
|||
Levene
Statistic |
df1 |
df2 |
Sig. |
5.449 |
2 |
6 |
.045 |
ANOVA |
||||||
Nilai |
||||||
|
Sum
of Squares |
Df |
Mean
Square |
F |
||
Between
Groups |
(Combined) |
.000 |
2 |
.000 |
.000 |
|
Linear
Term |
Contrast |
.000 |
1 |
.000 |
.000 |
|
Deviation |
.000 |
1 |
.000 |
.000 |
||
Within
Groups |
142.000 |
6 |
23.667 |
|
||
Total |
142.000 |
8 |
|
|
ANOVA |
|||
Nilai |
|||
|
Sig. |
||
Between
Groups |
(Combined) |
1.000 |
|
Linear
Term |
Contrast |
1.000 |
|
Deviation |
1.000 |
||
Within
Groups |
|
||
Total |
|
Post Hoc Tests
Multiple Comparisons |
|||||||
Dependent
Variable: Nilai |
|||||||
|
(I)
Metode |
(J)
Metode |
Mean
Difference (I-J) |
Std.
Error |
Sig. |
95%
Confidence Interval |
|
Lower
Bound |
Upper
Bound |
||||||
LSD |
I |
II |
.000 |
3.972 |
1.000 |
-9.72 |
9.72 |
III |
.000 |
3.972 |
1.000 |
-9.72 |
9.72 |
||
II |
I |
.000 |
3.972 |
1.000 |
-9.72 |
9.72 |
|
III |
.000 |
3.972 |
1.000 |
-9.72 |
9.72 |
||
III |
I |
.000 |
3.972 |
1.000 |
-9.72 |
9.72 |
|
II |
.000 |
3.972 |
1.000 |
-9.72 |
9.72 |
Homogeneous Subsets
Nilai |
|||
|
Metode |
N |
Subset
for alpha = 0.05 |
1 |
|||
Duncana |
I |
3 |
6.67 |
II |
3 |
6.67 |
|
III |
3 |
6.67 |
|
Sig. |
|
1.000 |
Means for
groups in homogeneous subsets are displayed. |
a. Uses
Harmonic Mean Sample Size = 3.000. |
Means Plots
Kesimpulan:
One
way anova
H0
= ada perbedaan metode penyuluhan
H1=
tidak ada perbedaan penyuluhan
P
val = 0,045
α = 0,05
0,045
< 0,05
Jadi,
dapat disimpulkan bahwa P val < α, H0 ditolak yang berarti ada perbedaan metode
penyuluhan berdasarkan hasil dari ketiga kategori nilai tersebut.
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