====== Data examination ====== Here we are looking at several variables, instead of each of IV and DV. This is called multiple regression. We will discuss it later. Download example file: \\ {{:elemapi.sav}} \\ {{:elemapi.sps}} \\ display labels. ^ __Data Label description__ ^^^ | | | Variable Labels | | Variable | Position | Label | | snum | 1 | school number | | dnum | 2 | district number | | api00 | 3 | api 2000 | | api99 | 4 | api 1999 | | growth | 5 | growth 1999 to 2000 | | meals | 6 | pct free meals | | ell | 7 | english language learners | | yr_rnd | 8 | year round school | | mobility | 9 | pct 1st year in school | | acs_k3 | 10 | avg class size k-3 | | acs_46 | 11 | avg class size 4-6 | | not_hsg | 12 | parent not hsg | | hsg | 13 | parent hsg | | some_col | 14 | parent some college | | col_grad | 15 | parent college grad | | grad_sch | 16 | parent grad school | | avg_ed | 17 | avg parent ed | | full | 18 | pct full credential | | emer | 19 | pct emer credential | | enroll | 20 | number of students | | mealcat | 21 | Percentage free meals in 3 categories | 우리가 관심이 있는 데이터는 2000년의 수학능력 (api00) % 무료급식 % 풀타임 교원 k-3까지의 평균 클래스사이즈 이에 대한 부분적 자료 먼저 살펴보기 위해서는 list /variables api00 acs_k3 meals full /cases from 1 to 10. api00 acs_k3 meals full 693 16 67 76.00 570 15 92 79.00 546 17 97 68.00 571 20 90 87.00 478 18 89 87.00 858 20 . 100.00 918 19 . 100.00 831 20 . 96.00 860 20 . 100.00 737 21 29 96.00 Number of cases read: 10 Number of cases listed: 10 descriptive /var = all . ^ __Descriptive Statistics__ ^^^^^^ | | N | Minimum | Maximum | Mean | Std. Deviation | | school number | 400 | 58 | 6072 | 2866.81 | 1543.811 | | district number | 400 | 41 | 796 | 457.74 | 184.823 | | api 2000 | 400 | 369 | 940 | 647.62 | 142.249 | | api 1999 | 400 | 333 | 917 | 610.21 | 147.136 | | growth 1999 to 2000 | 400 | -69 | 134 | 37.41 | 25.247 | | pct free meals | 315 | 6 | 100 | 71.99 | 24.386 | | english language learners | 400 | 0 | 91 | 31.45 | 24.839 | | year round school | 400 | 0 | 1 | .23 | .421 | | pct 1st year in school | 399 | 2 | 47 | 18.25 | 7.485 | | avg class size k-3 | 398 | @red:-21 | 25 | 18.55 | 5.005 | | avg class size 4-6 | 397 | 20 | 50 | 29.69 | 3.841 | | parent not hsg | 400 | 0 | 100 | 21.25 | 20.676 | | parent hsg | 400 | 0 | 100 | 26.02 | 16.333 | | parent some college | 400 | 0 | 67 | 19.71 | 11.337 | | parent college grad | 400 | 0 | 100 | 19.70 | 16.471 | | parent grad school | 400 | 0 | 67 | 8.64 | 12.131 | | avg parent ed | 381 | 1.00 | 4.62 | 2.6685 | .76379 | | pct full credential | 400 | .42 | 100.00 | 66.0568 | 40.29793 | | pct emer credential | 400 | 0 | 59 | 12.66 | 11.746 | | number of students | 400 | 130 | 1570 | 483.47 | 226.448 | | Percentage free meals in 3 categories | 400 | 1 | 3 | 2.02 | .819 | examine /variables=acs_k3 /plot histogram stem boxplot . ^ __Descriptives__ ^^^^^ | | | | Statistic | Std. Error | | avg class size k-3 | Mean | | 18.55 | .251 | | | 95% Confidence Interval for Mean | Lower Bound | 18.05 | | | | | Upper Bound | 19.04 | | | | 5% Trimmed Mean | | 19.13 | | | | Median | | 19.00 | | | | Variance | | 25.049 | | | | Std. Deviation | | 5.005 | | | | Minimum | | -21 | | | | Maximum | | 25 | | | | Range | | 46 | | | | Interquartile Range | | 2 | | | | Skewness | | -7.106 | .122 | | | Kurtosis | | 53.014 | .244 | [{{ :reg.histogram.jpg |Histogram}}] avg class size k-3 Stem-and-Leaf Plot Frequency Stem & Leaf 8.00 Extremes (=<14.0) 1.00 15 . & .00 15 . 14.00 16 . 0000000 .00 16 . 20.00 17 . 0000000000 .00 17 . 64.00 18 . 00000000000000000000000000000000 .00 18 . 143.00 19 . 00000000000000000000000000000000000000000000000000000000000000000000000 .00 19 . 97.00 20 . 000000000000000000000000000000000000000000000000 .00 20 . 40.00 21 . 00000000000000000000 .00 21 . 7.00 22 . 000 .00 22 . 3.00 23 . 0 1.00 Extremes (>=25.0) Stem width: 1 Each leaf: 2 case(s) & denotes fractional leaves. [{{ :reg.Boxplot.jpg |Boxplot}}] frequencies /var acs_k3. ^ __avg class size k-3__ ^^^^^^ | | | Frequency | Percent | Valid Percent | Cumulative Percent | | Valid | @yellow:-21 | 3 | .8 | .8 | .8 | | | @yellow:-20 | 2 | .5 | .5 | 1.3 | | | @yellow:-19 | 1 | .3 | .3 | 1.5 | | | 14 | 2 | .5 | .5 | 2.0 | | | 15 | 1 | .3 | .3 | 2.3 | | | 16 | 14 | 3.5 | 3.5 | 5.8 | | | 17 | 20 | 5.0 | 5.0 | 10.8 | | | 18 | 64 | 16.0 | 16.1 | 26.9 | | | 19 | 143 | 35.8 | 35.9 | 62.8 | | | 20 | 97 | 24.3 | 24.4 | 87.2 | | | 21 | 40 | 10.0 | 10.1 | 97.2 | | | 22 | 7 | 1.8 | 1.8 | 99.0 | | | 23 | 3 | .8 | .8 | 99.7 | | | 25 | 1 | .3 | .3 | 100.0 | | | Total | 398 | 99.5 | 100.0 | | | Missing | System | 2 | .5 | | | | Total | | 400 | 100.0 | | | compute filtvar = (acs_k3 < 0). filter by filtvar. list cases /var snum dnum acs_k3. snum dnum acs_k3 600 140 -20 596 140 -19 611 140 -20 595 140 -21 592 140 -21 602 140 -21 Number of cases read: 6 Number of cases listed: 6 filter off. IF (acs_k3<0) racs_k3=ABS(acs_k3). IF (acs_k3>=0) racs_k3=acs_k3. EXECUTE. frequencies variables=full /format=notable /histogram . [{{ :reg.histogram02.jpg |Histogram for variable full }}] ^ __pct full credential__ ^^^^^^ | | | Frequency | Percent | Valid Percent | Cumulative Percent | | Valid | 0.42 | 1 | .3 | .3 | .3 | | | 0.45 | 1 | .3 | .3 | .5 | | | 0.46 | 1 | .3 | .3 | .8 | | | 0.47 | 1 | .3 | .3 | 1.0 | | | 0.48 | 1 | .3 | .3 | 1.3 | | | 0.5 | 3 | .8 | .8 | 2.0 | | | 0.51 | 1 | .3 | .3 | 2.3 | | | 0.52 | 1 | .3 | .3 | 2.5 | | | 0.53 | 1 | .3 | .3 | 2.8 | | | 0.54 | 1 | .3 | .3 | 3.0 | | | 0.56 | 2 | .5 | .5 | 3.5 | | | 0.57 | 2 | .5 | .5 | 4.0 | | | 0.58 | 1 | .3 | .3 | 4.3 | | | 0.59 | 3 | .8 | .8 | 5.0 | | | 0.6 | 1 | .3 | .3 | 5.3 | | | 0.61 | 4 | 1.0 | 1.0 | 6.3 | | | 0.62 | 2 | .5 | .5 | 6.8 | | | 0.63 | 1 | .3 | .3 | 7.0 | | | 0.64 | 3 | .8 | .8 | 7.8 | | | 0.65 | 3 | .8 | .8 | 8.5 | | | 0.66 | 2 | .5 | .5 | 9.0 | | | 0.67 | 6 | 1.5 | 1.5 | 10.5 | | | 0.68 | 2 | .5 | .5 | 11.0 | | | 0.69 | 3 | .8 | .8 | 11.8 | | | 0.7 | 1 | .3 | .3 | 12.0 | | | 0.71 | 1 | .3 | .3 | 12.3 | | | 0.72 | 2 | .5 | .5 | 12.8 | | | 0.73 | 6 | 1.5 | 1.5 | 14.3 | | | 0.75 | 4 | 1.0 | 1.0 | 15.3 | | | 0.76 | 2 | .5 | .5 | 15.8 | | | 0.77 | 2 | .5 | .5 | 16.3 | | | 0.79 | 3 | .8 | .8 | 17.0 | | | 0.8 | 5 | 1.3 | 1.3 | 18.3 | | | 0.81 | 8 | 2.0 | 2.0 | 20.3 | | | 0.82 | 2 | .5 | .5 | 20.8 | | | 0.83 | 2 | .5 | .5 | 21.3 | | | 0.84 | 2 | .5 | .5 | 21.8 | | | 0.85 | 3 | .8 | .8 | 22.5 | | | 0.86 | 2 | .5 | .5 | 23.0 | | | 0.9 | 3 | .8 | .8 | 23.8 | | | 0.92 | 1 | .3 | .3 | 24.0 | | | 0.93 | 1 | .3 | .3 | 24.3 | | | 0.94 | 2 | .5 | .5 | 24.8 | | | 0.95 | 2 | .5 | .5 | 25.3 | | | 0.96 | 1 | .3 | .3 | 25.5 | | | @red:1 | 2 | .5 | .5 | 26.0 | | | @yellow:37 | 1 | .3 | .3 | 26.3 | | | 41 | 1 | .3 | .3 | 26.5 | | | 44 | 2 | .5 | .5 | 27.0 | | | 45 | 2 | .5 | .5 | 27.5 | | | 46 | 1 | .3 | .3 | 27.8 | | | 48 | 1 | .3 | .3 | 28.0 | | | 53 | 1 | .3 | .3 | 28.3 | | | 57 | 1 | .3 | .3 | 28.5 | | | 58 | 3 | .8 | .8 | 29.3 | | | 59 | 1 | .3 | .3 | 29.5 | | | 61 | 1 | .3 | .3 | 29.8 | | | 63 | 2 | .5 | .5 | 30.3 | | | 64 | 1 | .3 | .3 | 30.5 | | | 65 | 1 | .3 | .3 | 30.8 | | | 68 | 2 | .5 | .5 | 31.3 | | | 69 | 3 | .8 | .8 | 32.0 | | | 70 | 1 | .3 | .3 | 32.3 | | | 71 | 3 | .8 | .8 | 33.0 | | | 72 | 1 | .3 | .3 | 33.3 | | | 73 | 2 | .5 | .5 | 33.8 | | | 74 | 1 | .3 | .3 | 34.0 | | | 75 | 4 | 1.0 | 1.0 | 35.0 | | | 76 | 4 | 1.0 | 1.0 | 36.0 | | | 77 | 2 | .5 | .5 | 36.5 | | | 78 | 4 | 1.0 | 1.0 | 37.5 | | | 79 | 3 | .8 | .8 | 38.3 | | | 80 | 10 | 2.5 | 2.5 | 40.8 | | | 81 | 4 | 1.0 | 1.0 | 41.8 | | | 82 | 3 | .8 | .8 | 42.5 | | | 83 | 9 | 2.3 | 2.3 | 44.8 | | | 84 | 4 | 1.0 | 1.0 | 45.8 | | | 85 | 8 | 2.0 | 2.0 | 47.8 | | | 86 | 5 | 1.3 | 1.3 | 49.0 | | | 87 | 12 | 3.0 | 3.0 | 52.0 | | | 88 | 6 | 1.5 | 1.5 | 53.5 | | | 89 | 5 | 1.3 | 1.3 | 54.8 | | | 90 | 9 | 2.3 | 2.3 | 57.0 | | | 91 | 8 | 2.0 | 2.0 | 59.0 | | | 92 | 7 | 1.8 | 1.8 | 60.8 | | | 93 | 12 | 3.0 | 3.0 | 63.8 | | | 94 | 10 | 2.5 | 2.5 | 66.3 | | | 95 | 17 | 4.3 | 4.3 | 70.5 | | | 96 | 17 | 4.3 | 4.3 | 74.8 | | | 97 | 11 | 2.8 | 2.8 | 77.5 | | | 98 | 9 | 2.3 | 2.3 | 79.8 | | | 100 | 81 | 20.3 | 20.3 | 100.0 | | | Total | 400 | 100.0 | 100.0 | | frequencies variables=full . IF (full <= 1) rfull=full * 100. IF (full > 1) rfull=full. EXECUTE.