Overview

Dataset statistics

Number of variables10
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory918.0 KiB
Average record size in memory94.0 B

Variable types

Numeric6
Categorical4

Dataset

Description의지보조기기사 국가시험 응시자의 성적 현황을 분석할 수 있는 정보(연도, 직종, 회차, 일련번호, 과목명, 과목별 점수, 총점, 합격여부, 성별, 연령대)를 제공합니다.
URLhttps://www.data.go.kr/data/15083523/fileData.do

Alerts

직종 has constant value ""Constant
연도 is highly overall correlated with 회차 and 1 other fieldsHigh correlation
회차 is highly overall correlated with 연도 and 1 other fieldsHigh correlation
일련번호 is highly overall correlated with 연도 and 1 other fieldsHigh correlation
과목별점수 is highly overall correlated with 총점High correlation
총점 is highly overall correlated with 과목별점수 and 1 other fieldsHigh correlation
합격여부 is highly overall correlated with 총점High correlation
과목별점수 has 2250 (22.5%) zerosZeros
총점 has 801 (8.0%) zerosZeros

Reproduction

Analysis started2023-12-12 14:19:55.744817
Analysis finished2023-12-12 14:20:01.105002
Duration5.36 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2008.7211
Minimum2000
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T23:20:01.176652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2000
5-th percentile2000
Q12001
median2009
Q32015
95-th percentile2021
Maximum2022
Range22
Interquartile range (IQR)14

Descriptive statistics

Standard deviation7.4952073
Coefficient of variation (CV)0.003731333
Kurtosis-1.3006691
Mean2008.7211
Median Absolute Deviation (MAD)8
Skewness0.25237475
Sum20087211
Variance56.178133
MonotonicityNot monotonic
2023-12-12T23:20:01.311756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
2000 2485
24.9%
2013 635
 
6.3%
2001 620
 
6.2%
2002 527
 
5.3%
2009 461
 
4.6%
2022 424
 
4.2%
2011 415
 
4.2%
2010 408
 
4.1%
2012 382
 
3.8%
2020 362
 
3.6%
Other values (12) 3281
32.8%
ValueCountFrequency (%)
2000 2485
24.9%
2001 620
 
6.2%
2002 527
 
5.3%
2004 145
 
1.5%
2005 178
 
1.8%
2006 287
 
2.9%
2007 316
 
3.2%
2008 327
 
3.3%
2009 461
 
4.6%
2010 408
 
4.1%
ValueCountFrequency (%)
2022 424
4.2%
2021 362
3.6%
2020 362
3.6%
2019 298
3.0%
2018 312
3.1%
2017 263
2.6%
2016 297
3.0%
2015 269
2.7%
2014 227
 
2.3%
2013 635
6.3%

직종
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
의지보조기기사
10000 

Length

Max length33
Median length33
Mean length33
Min length33

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row의지보조기기사
2nd row의지보조기기사
3rd row의지보조기기사
4th row의지보조기기사
5th row의지보조기기사

Common Values

ValueCountFrequency (%)
의지보조기기사 10000
100.0%

Length

2023-12-12T23:20:01.421095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:20:01.508093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
의지보조기기사 10000
100.0%

회차
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.396
Minimum1
Maximum23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T23:20:01.589087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median9
Q316
95-th percentile22
Maximum23
Range22
Interquartile range (IQR)14

Descriptive statistics

Standard deviation7.4916751
Coefficient of variation (CV)0.79732601
Kurtosis-1.2425187
Mean9.396
Median Absolute Deviation (MAD)7
Skewness0.36754145
Sum93960
Variance56.125197
MonotonicityNot monotonic
2023-12-12T23:20:01.701913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
1 2485
24.9%
2 620
 
6.2%
3 527
 
5.3%
9 461
 
4.6%
23 424
 
4.2%
11 415
 
4.2%
10 408
 
4.1%
12 382
 
3.8%
21 362
 
3.6%
22 362
 
3.6%
Other values (13) 3554
35.5%
ValueCountFrequency (%)
1 2485
24.9%
2 620
 
6.2%
3 527
 
5.3%
4 145
 
1.5%
5 178
 
1.8%
6 287
 
2.9%
7 316
 
3.2%
8 327
 
3.3%
9 461
 
4.6%
10 408
 
4.1%
ValueCountFrequency (%)
23 424
4.2%
22 362
3.6%
21 362
3.6%
20 298
3.0%
19 312
3.1%
18 263
2.6%
17 297
3.0%
16 269
2.7%
15 227
2.3%
14 303
3.0%

일련번호
Real number (ℝ)

HIGH CORRELATION 

Distinct3825
Distinct (%)38.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2027.9615
Minimum1
Maximum4043
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T23:20:01.840252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile210.95
Q11029
median2022.5
Q33021
95-th percentile3853
Maximum4043
Range4042
Interquartile range (IQR)1992

Descriptive statistics

Standard deviation1161.5574
Coefficient of variation (CV)0.57277096
Kurtosis-1.1829653
Mean2027.9615
Median Absolute Deviation (MAD)996.5
Skewness0.00071384253
Sum20279615
Variance1349215.7
MonotonicityNot monotonic
2023-12-12T23:20:01.981195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3670 7
 
0.1%
2993 7
 
0.1%
953 7
 
0.1%
2309 7
 
0.1%
1233 7
 
0.1%
638 7
 
0.1%
2953 7
 
0.1%
867 6
 
0.1%
2542 6
 
0.1%
2732 6
 
0.1%
Other values (3815) 9933
99.3%
ValueCountFrequency (%)
1 1
 
< 0.1%
2 4
< 0.1%
3 4
< 0.1%
4 4
< 0.1%
5 1
 
< 0.1%
6 4
< 0.1%
7 4
< 0.1%
8 1
 
< 0.1%
9 4
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
4043 5
0.1%
4042 5
0.1%
4041 3
< 0.1%
4040 3
< 0.1%
4039 2
 
< 0.1%
4037 3
< 0.1%
4036 3
< 0.1%
4035 4
< 0.1%
4034 1
 
< 0.1%
4033 2
 
< 0.1%

과목명
Categorical

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
해부·생리학
1292 
보조기학
1257 
운동·생체역학
1257 
재활의학
1246 
재활공학·재료학
1242 
Other values (5)
3706 

Length

Max length14
Median length8
Mean length6.6863
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row보조기학
2nd row운동·생체역학
3rd row보건의료 관계 법규
4th row운동·생체역학
5th row의지학

Common Values

ValueCountFrequency (%)
해부·생리학 1292
12.9%
보조기학 1257
12.6%
운동·생체역학 1257
12.6%
재활의학 1246
12.5%
재활공학·재료학 1242
12.4%
보건의료 관계 법규 1241
12.4%
의지학 1236
12.4%
의지보조기기사 주관식 실기 628
6.3%
의지보조기기사 객관식 실기 305
 
3.0%
실기시험 296
 
3.0%

Length

2023-12-12T23:20:02.118043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:20:02.232026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해부·생리학 1292
9.0%
보조기학 1257
8.8%
운동·생체역학 1257
8.8%
재활의학 1246
8.7%
재활공학·재료학 1242
8.7%
보건의료 1241
8.6%
관계 1241
8.6%
법규 1241
8.6%
의지학 1236
8.6%
의지보조기기사 933
6.5%
Other values (4) 2162
15.1%

과목별점수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct100
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.009
Minimum0
Maximum100
Zeros2250
Zeros (%)22.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T23:20:02.701768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median14
Q324
95-th percentile52
Maximum100
Range100
Interquartile range (IQR)18

Descriptive statistics

Standard deviation18.894539
Coefficient of variation (CV)1.049172
Kurtosis4.7229325
Mean18.009
Median Absolute Deviation (MAD)9
Skewness1.9708323
Sum180090
Variance357.00362
MonotonicityNot monotonic
2023-12-12T23:20:02.847926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2250
22.5%
12 379
 
3.8%
14 367
 
3.7%
13 365
 
3.6%
15 360
 
3.6%
11 356
 
3.6%
10 349
 
3.5%
16 345
 
3.5%
17 307
 
3.1%
9 284
 
2.8%
Other values (90) 4638
46.4%
ValueCountFrequency (%)
0 2250
22.5%
1 5
 
0.1%
2 14
 
0.1%
3 31
 
0.3%
4 71
 
0.7%
5 96
 
1.0%
6 145
 
1.5%
7 204
 
2.0%
8 265
 
2.6%
9 284
 
2.8%
ValueCountFrequency (%)
100 25
0.2%
98 4
 
< 0.1%
97 1
 
< 0.1%
96 10
 
0.1%
95 23
0.2%
94 15
0.1%
93 7
 
0.1%
92 12
 
0.1%
91 15
0.1%
90 30
0.3%

총점
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct289
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean143.3508
Minimum0
Maximum329
Zeros801
Zeros (%)8.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T23:20:02.995687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q194
median127
Q3227
95-th percentile282
Maximum329
Range329
Interquartile range (IQR)133

Descriptive statistics

Standard deviation84.537533
Coefficient of variation (CV)0.58972488
Kurtosis-0.8604182
Mean143.3508
Median Absolute Deviation (MAD)46
Skewness0.18233122
Sum1433508
Variance7146.5945
MonotonicityNot monotonic
2023-12-12T23:20:03.148374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 801
 
8.0%
95.0 157
 
1.6%
90.0 142
 
1.4%
100.0 140
 
1.4%
28.0 114
 
1.1%
117.0 107
 
1.1%
139.0 104
 
1.0%
29.0 104
 
1.0%
124.0 101
 
1.0%
85.0 100
 
1.0%
Other values (279) 8130
81.3%
ValueCountFrequency (%)
0.0 801
8.0%
9.0 4
 
< 0.1%
13.0 3
 
< 0.1%
15.0 2
 
< 0.1%
16.0 6
 
0.1%
17.0 2
 
< 0.1%
17.5 2
 
< 0.1%
18.0 3
 
< 0.1%
19.0 7
 
0.1%
20.0 5
 
0.1%
ValueCountFrequency (%)
329.0 2
 
< 0.1%
328.0 4
< 0.1%
324.0 2
 
< 0.1%
320.0 5
0.1%
319.0 2
 
< 0.1%
318.0 2
 
< 0.1%
317.0 5
0.1%
313.0 4
< 0.1%
312.0 9
0.1%
311.0 5
0.1%

합격여부
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
불합격
5132 
합격
4082 
결시
779 
응시결격
 
7

Length

Max length4
Median length3
Mean length2.5146
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row불합격
2nd row합격
3rd row합격
4th row합격
5th row합격

Common Values

ValueCountFrequency (%)
불합격 5132
51.3%
합격 4082
40.8%
결시 779
 
7.8%
응시결격 7
 
0.1%

Length

2023-12-12T23:20:03.489646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:20:03.627259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
불합격 5132
51.3%
합격 4082
40.8%
결시 779
 
7.8%
응시결격 7
 
0.1%

성별
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
남
6412 
여
3588 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row여
2nd row남
3rd row여
4th row남
5th row남

Common Values

ValueCountFrequency (%)
남 6412
64.1%
여 3588
35.9%

Length

2023-12-12T23:20:03.746770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:20:03.841856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남 6412
64.1%
여 3588
35.9%

연령대
Real number (ℝ)

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.519
Minimum10
Maximum70
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T23:20:03.934598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile20
Q120
median20
Q320
95-th percentile40
Maximum70
Range60
Interquartile range (IQR)0

Descriptive statistics

Standard deviation7.2049865
Coefficient of variation (CV)0.30634748
Kurtosis5.9224729
Mean23.519
Median Absolute Deviation (MAD)0
Skewness2.3485338
Sum235190
Variance51.91183
MonotonicityNot monotonic
2023-12-12T23:20:04.052478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
20 7548
75.5%
30 1644
 
16.4%
40 567
 
5.7%
50 169
 
1.7%
60 60
 
0.6%
10 11
 
0.1%
70 1
 
< 0.1%
ValueCountFrequency (%)
10 11
 
0.1%
20 7548
75.5%
30 1644
 
16.4%
40 567
 
5.7%
50 169
 
1.7%
60 60
 
0.6%
70 1
 
< 0.1%
ValueCountFrequency (%)
70 1
 
< 0.1%
60 60
 
0.6%
50 169
 
1.7%
40 567
 
5.7%
30 1644
 
16.4%
20 7548
75.5%
10 11
 
0.1%

Interactions

2023-12-12T23:20:00.042780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:57.077444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:57.615039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:58.159070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:58.763577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:59.366088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:00.151193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:57.177534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:57.711919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:58.251601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:58.845511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:59.469055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:00.261183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:57.267092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:57.787056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:58.350351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:58.949304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:59.563684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:00.468453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:57.367817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:57.888355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:58.471004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:59.071676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:59.694471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:00.558008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:57.450484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:57.966235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:58.570488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:59.161628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:59.810134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:20:00.686164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:57.531861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:58.062186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:58.660063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:59.255274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:19:59.921582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:20:04.161028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도회차일련번호과목명과목별점수총점합격여부성별연령대
연도1.0000.9970.9380.2470.4600.6340.2280.2710.368
회차0.9971.0000.9760.4120.4180.6100.2100.1700.310
일련번호0.9380.9761.0000.4430.4560.7200.2990.2340.363
과목명0.2470.4120.4431.0000.7840.2090.0660.0430.070
과목별점수0.4600.4180.4560.7841.0000.6860.4710.1770.270
총점0.6340.6100.7200.2090.6861.0000.8100.2570.341
합격여부0.2280.2100.2990.0660.4710.8101.0000.1780.170
성별0.2710.1700.2340.0430.1770.2570.1781.0000.282
연령대0.3680.3100.3630.0700.2700.3410.1700.2821.000
2023-12-12T23:20:04.282011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
성별과목명합격여부
성별1.0000.0330.118
과목명0.0331.0000.039
합격여부0.1180.0391.000
2023-12-12T23:20:04.371235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도회차일련번호과목별점수총점연령대과목명합격여부성별
연도1.0001.0000.9920.2690.352-0.3290.1370.1330.130
회차1.0001.0000.9920.2680.351-0.3290.1370.1300.128
일련번호0.9920.9921.0000.2830.367-0.3630.1490.1830.179
과목별점수0.2690.2680.2831.0000.671-0.3130.3450.2870.130
총점0.3520.3510.3670.6711.000-0.3640.0660.6370.197
연령대-0.329-0.329-0.363-0.313-0.3641.0000.0350.1180.302
과목명0.1370.1370.1490.3450.0660.0351.0000.0390.033
합격여부0.1330.1300.1830.2870.6370.1180.0391.0000.118
성별0.1300.1280.1790.1300.1970.3020.0330.1181.000

Missing values

2023-12-12T23:20:00.849428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:20:01.024232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

연도직종회차일련번호과목명과목별점수총점합격여부성별연령대
187452011의지보조기기사112344보조기학37133.0불합격여20
110882002의지보조기기사31387운동·생체역학095.0합격남30
50302000의지보조기기사1629보건의료 관계 법규11179.0합격여20
128242005의지보조기기사51604운동·생체역학12250.0합격남20
90522001의지보조기기사21132의지학090.0합격남30
268962018의지보조기기사193363운동·생체역학881.0불합격남20
7262000의지보조기기사191보건의료 관계 법규030.0합격남30
27982000의지보조기기사1350보건의료 관계 법규11156.0불합격남20
176932010의지보조기기사102212보건의료 관계 법규11128.0불합격남20
116092002의지보조기기사31452보조기학065.0합격남40
연도직종회차일련번호과목명과목별점수총점합격여부성별연령대
281892019의지보조기기사203524보건의료 관계 법규13217.0합격남20
246712015의지보조기기사163084실기시험70263.0합격남20
310132021의지보조기기사223877보건의료 관계 법규12241.0합격남20
175332010의지보조기기사102192보건의료 관계 법규10117.0불합격남20
309022021의지보조기기사223863재활의학16198.0합격여20
131682006의지보조기기사61647운동·생체역학12285.0합격남20
112352002의지보조기기사31405해부·생리학045.0불합격남30
263212017의지보조기기사183291보조기학41254.0합격여20
44382000의지보조기기사1555보건의료 관계 법규11156.0불합격여20
95622001의지보조기기사21196재활공학·재료학085.0합격남30