Upload
others
View
0
Download
0
Embed Size (px)
Citation preview
.
2017 - 2018
– .
1
........................................................................................................................ 3
...................................................................................................................................... 3
............................................................................................... 3 ...................................................................................................... 4
................................................................................................ ......................... 6
............................................................................................................. 6 ........................................................................................................................ 8 .............................................................................................................. 9 ) ( ...................................................................................... 11 )( .............................................................................................................. 12
.................................................................................................................. 13
....................................................................................................................... 13 ......................................................................................................... 13 .................................................................................................................... 14 ................................................................................................................... 14
................................................................................................ ......................... 15
...................................................................................................................... 18
........................................................................................................................ 18
....................................................................................................................... 18 ................................................................................................. 21
– KOLMOGOROV – SMIRNOV TEST...................................... 23
..................................................................................................................... 24
: (T) ONE SAMPLE T-TEST ................................................................... 24 : )T( INDEPENDENT SAMPLES T-TEST ................................ ................ 30
................................................................................................ ................ 39
: )T( ................................................................................................. 39 DEPENDENT (PAIRED) SAMPLES T-TEST ............................................................................. 39
: ) ( ONE-WAY ANOVA ............................................................. 46 : WITHOUT INTERACTION TWO-WAY ANOVA ................................. 57 : WITH INTERACTION TWO-WAY ANOVA ......................................... 60 : ANOVA WITHIN GROUPS ................................ ................. 65 : MIXED ANOVA ............................................... 67
................................................................................................ ................. 70
............................................................................................................... 70
: Sign Test ...................................................................... 72 : Wilcoxon Test ................................. 73 : - Mann-Whitney Test ............................................................. 75
: – Kruskal-WallisTest ....................................... 79 : FriedmanTest ....................................................... 81
– .
2
................................................................................................ ................. 84
RELATIONSHIPS........................................................................................................ 84
CORRELATION ....................................................................................................... 84 Correlation Coefficient ..................................................................................... 84
TEST CHI-SQUARE ........................................................................................... 89
................................................................................................ ................ 93
LINEAR REGRESSION ....................................................................................... 93
SIMPLE LINEAR REGRESSION ....................................................................... 93 MULTIPLE LINEAR REGRESSION .................................................................. 100
– .
3
.
Population
.
Comprehensive Survey
.
Samples
.
Raw Data .
.
.
.
1.
)
(
2. .
.
.
– .
4
3. .
4.
5.
.
6. Continuous
.
7. Discrete
1.
.
2. .
3. .
4. .
5. . 6. --
– .
5
7.
8.
.
– .
6
Probability Samples
.
)
... .
.
1.
2.
3.
Simple Random Sampling
Sampling units
N 1 N .
-Sampling with replacement .1n
n
-Sampling without replacement .1 1, ,
1n nn
( )
.
– .
7
1.
2. Outlier or Extreme Point) (
.
1.
.
3 :2
.
3 :2
2.
3.
– .
8
Systematic Sampling
”U”
1 U
”U”
100000
500 ”U” :
100000U 200
500= =
1 200 150
200
1503505507509501150500
1.
2. ) 5 (
1.
.
2.
U
.
"".
– .
9
Stratified Random Sampling
“Strata”
.
.
.
.
1.
2.
:
, 1, 2,i
iNn n iN
in iiNi n N
200 2000
2 380 120
200
– .
10
2000
300 200 400 950 150
250 .
1300 250 37.5 382000
n
1200 250 252000
n
1400 250 502000
n
1950 250 118.75 1192000
n
1150 250 18.75 192000
n
1. .
2.
3. .
4.
5.
6. .
– .
11
) (Multi-Stage Random Sampling) Cluster Sampling
“Cluster” “C”
“R”
.
1 2, , , Rn n n
1 2 Rn n n n .
.
“C” in
1 2 3 4, , ,n n n n
1 2 3 4n n n n n.
.
.
1. .
2.
3.
1. ( )
.
2. – –
.
– .
12
) Permanent (Fixed) Sampling
1. .
2. .
3. .
4. .
5. ( ) .
6.
” “”“.
– -.
.
– .
13
Non-Probability Samples
.
. .
.
Convenience Sampling
Purposive Sampling
Convenience Sampling
Unrestricted Samples
.
.
Accidental Sample
.
Purposive Sampling
– .
14
.
.
.
.
Judgmental Sampling
Quota Sampling.
Judgment Sampling
.
Quota Sampling
.
.
.
– .
15
.
.
. 60%40%
18 12
60% 40% 18 12 .
Snowball Sample
.
.
.
.
.
1. .
2. .
3. .
– .
16
1.
2.
1.
2. .
.
95% -99%
– .
17
0.95 0.96 0.97 0.98 0.99
10 10 10 10 10 10
20 20 20 20 20 20
30 28 29 29 29 29
40 37 37 37 38 38
50 45 45 46 46 47
60 53 53 54 55 56
70 60 61 62 63 64
80 67 68 69 70 72
90 74 75 76 78 80
100 80 81 83 85 88
200 132 136 141 147 154
300 169 176 184 194 207
400 197 206 217 231 250
500 218 230 243 261 286
600 235 248 265 285 316
700 249 264 282 306 341
800 260 277 297 324 363
900 270 288 310 339 383
1000 278 297 321 352 400
2000 323 349 382 427 499
3000 341 370 408 459 544
4000 351 382 422 477 570
5000 357 390 431 489 586
6000 362 395 437 497 598
7000 365 398 442 503 607
8000 367 401 445 507 613
9000 369 403 448 511 618
10000 370 405 450 514 623
100000 383 421 469 539 660
1000000 384 422 471 541 664
– .
18
Test of Hypotheses
.
.( )
Fundemental Definitions
The Statistical Hypothesis
.
.
The Null Hypothesis
( )
0H NH .
.
(Hypothesized value)0
0 0: 0 (Hypothezied Value) .
70
0 : 70 70
.
– .
19
The Alternative Hypothesis
Research hypothesis) ( 1H AH .
"
"
Statistically Significant .
.
.
1- ( )
1 0: 2- ( )
1 0: 3- ( )
1 0:
.( )
– .
20
Type-I and Type-II Errors
Type-I Error
.
(Level of Significance) " 1
(Confidence level).
1%-5%.
05.0
Type-II Error
.
" Baytuh "
" Beta"1 (Power of the test).
) 1.(
) 1 :(
) 1 (
The Statistical Test
ZT .
ZT *Z*T
– .
21
) (Probability Value) The Observed Significance level
" " (P-value)
( )
0H 1H .
. Sig. P-value .
1- 0H 1H.
2- ) .
3-
4- .
5- :value)-(Sig. or P :
0H value)-(Sig. or P
0H.
) P-value (0.05
0.050.10
.0.10
0H :
1H :
( )
.( ) .
.
– .
22
2
2mZn
Z=1.96 05.0Z=1.96 =0.05
38505.02
96.1 2
n
1nNnNncorrected
N=250
1521385250
250385correctedn
: http://www.surveysystem.com/sscalc.htm
12NNn
N 05.0 :
– .
23
– Kolmogorov – Smirnov Test
( )
.
.
– )Kolmogorov-Smirnov (
50-) Shapiro-Wilk (
50.
50 : 90 82 76 32 21 80 92 65 30 40 70 60 82 45 88 90 70 80 89 89 60 50 90 88 92 76 65 92 77 85 68 79 86 86 79 94 82 71 90 31 83 68 93 94 29 74 80 68 97 50
: –
0 05.. )Normal(. Analyze Descriptive Statistics Explore
SPSS
Tests of Normality
.160 50 .003 .866 50 .000Statistic df Sig. Statistic df Sig.
Kolmogorov-Smirnova Shapiro-Wilk
Lilliefors Significance Correctiona.
Sig.=.003
0 05..
– .
24
Parametric Tests
: (T) One Sample T-Test ) 1(
65, 72, 68, 82, 45, 92, 87, 85, 90, 60, 48, 60, 68, 72, 79, 68, 73, 69, 78, 84
: = 65 Analyze Compare Means One-Sample T Test
T SPSS
One-Sample Statistics
20 72.25 12.867 2.877scoresN Mean Std. Deviation
Std. ErrorMean
One-Sample Test
2.520 19 .021 7.250 1.23 13.27scorest df Sig. (2-tailed)
MeanDifference Lower Upper
95% ConfidenceInterval of the
Difference
Test Value = 65
t = 2.52Sig.(2-tailed)=0.0210.05 ( )
65
( ) 65.
65
(Sig.) 0 021 0 0105
2. . )T
2 (72 25x .
) 65 65
– .
25
/ =
=n
T T n
.
.
.
2.0
0.2 0.8 0.8
.
=7.25 =12.867
7 25 0 56312 867
. .
.
2 52 0 563
20. .
– .
26
) 2(
.100 .
.
( ) 100 .
100 .
SPSS
One-Sample Statistics
30 110.23 7.960 1.453N Mean Std. Deviation
Std. ErrorMean
One-Sample Test
7.042 29 .000 10.233 7.26 13.21t df Sig. (2-tailed)
MeanDifference Lower Upper
95% Confidence Intervalof the Difference
Test Value = 100
t = 7.042Sig.(2-tailed)=0.0000.05 ( )
( )
100 ( ) 100.
100
(Sig.) 000.0 110 23x .
) 100(
100.
= 10.233 =7.960
10 233 1 2867 960
. ..
7 042 1 286
30. .
– .
27
) 1(
.:
75 . 74 83 94 68 76 60 90 70 80 90 80 68 82 79 76 65 50 70 60 92 82 68 93 71 86 92 90 80 82 65
One-Sample Statistics N Mean Std. Deviation Std. Error Mean
30 77.2000 11.30578 2.06414
One-Sample Test
Test Value = 75
t df Sig. (2-tailed) Mean Difference
95% Confidence Interval of the
Difference
Lower Upper
1.066 29 .295 2.20000 -2.0216 6.4216
– .
28
) 2(
10 .
.5
.
1 - .
2 - Sig
One-Sample Statistics
10 5.7000 2.35938 .74610xN Mean Std. Deviation
Std. ErrorMean
One-Sample Test
.938 9 .373 .70000 -.9878 2.3878xt df Sig. (2-tailed)
MeanDifference Lower Upper
95% ConfidenceInterval of the
Difference
Test Value = 5
– .
29
)3(
70 .
20
.SPSS
.
N Mean Std. Deviation Std. Error Mean 20 76.35 6.938 1.551
Test Value = 70
t df Sig. (2-tailed) Mean Difference 4.093 19 0.001 6.350
– .
30
:) T (INDEPENDENT SAMPLES T-TEST
/ = 2
22
2
TT df
df 2 01 .
2 .
.( )
2 1
2 60.0 20 06 0 14. . 20 14 0 23. .
2 0 23.
– .
31
) 1(
.
.
( )
1 2
)
. Analyze Compare Means Independent Samples T Test
Group Statistics
21 85.90 8.496 1.85419 79.32 11.061 2.537
N Mean Std. DeviationStd. Error
Mean
Independent Samples Test
4.135 .049 2.125 38 .040 6.589 3.101 .311 12.867
2.097 33.704 .044 6.589 3.143 .200 12.978
Equal variances assumedEqual variances notassumed
F Sig.
Levene's Test forEquality of Variances
t df Sig. (2-tailed)Mean
DifferenceStd. ErrorDifference Lower Upper
95% Confidence Intervalof the Difference
t-test for Equality of Means
) Levene’s Test(Sig. = 0.049 .
t=2.097 Sig. = 0.044
5%.
(Sig.) 0 044 0 022
2. . )T
2 (1 2 6 589x x .
) (
.
– .
32
/ =
= 6.58 =9.795
6 58 0 6729 795
. ..
2
22
2 097 0 1152 097 33 704
. .. .
– .
33
) 1(
.
Group Statistics N Mean Std. Deviation Std. Error Mean
12 34.6667 5.39921 1.55862
13 28.0000 4.12311 1.14354
Independent Samples Test
Levene's Test for
Equality of Variances t-test for Equality of Means
F Sig. t df
Sig. (2-
tailed)
95% Confidence
Interval of the
Difference
Lower Upper
Equal variances
assumed
1.137 .297 3.487 23 .002 2.71141 10.62192
Equal variances
not assumed 3.449 20.567 .002 2.64135 10.69199
– .
34
)2(
.7
6. SPSS
.
1-
2-
3- ) 1.(
4- 95 % .
5- ) 4) (3.(
6-
– .
35
7 41.4286 13.45185 5.084326 45.0000 22.58318 9.21954
N Mean Std. DeviationStd. Error
Mean
2.638 .133 -.353 11 .731 -25.83335 18.69049-.339 7.895 .743 -27.90654 20.76369
Equal variances assumedEqual variances not assumed
F Sig.
Levene's Test forEquality of Variances
t df Sig. (2-tailed) Lower Upper
95% ConfidenceInterval of the
Difference
t-test for Equality of Means
– .
36
) 3(
.16
.
:
42 38 41 37 43 44 45 36
34 35 35 36 39 37 38 34
Group Statistics N Mean Std. Deviation Std. Error Mean
8 40.7500 3.37004 1.19149
8 36.0000 1.85164 .65465
Independent Samples Test
Levene's Test
for Equality of
Variances t-test for Equality of Means
F Sig. t df
Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference
95% Confidence Interval
of the Difference
Lower Upper
Equal
variances
assumed
4.342 .056 3.494 14 .004 4.75000 1.35949 1.83418 7.66582
Equal
variances
not
assumed
3.494 10.83 .005 4.75000 1.35949 1.75353 7.74647
– .
37
) 4(
CPA
CPA .
.
1 - .
2 -
3 - ) 2(
4- ) 3 (Sig
– .
38
Tests of Normality
.208 5 .200 .914 5 .494
.182 7 .200 .944 7 .675
Statistic df Sig. Statistic df Sig.
Kolmogorov-Smirnov Shapiro-Wilk
Group Statistics
5 69.4000 14.46720 6.46993
7 61.2857 13.57343 5.13028
N Mean Std. Deviation
Std. Error
Mean
Independent Samples Test
.031 .863 .994 10 .344 -10.06989 26.29847.983 8.398 .353 -10.77068 26.99925
Equal variances assumedEqual variances not assumed
F Sig.
Levene's Test forEquality of Variances
t df Sig. (2-tailed) Lower Upper
95% ConfidenceInterval of the
Difference
t-test for Equality of Means
Ranks
5 7.60
7 5.71
12Total
N Mean Rank
Test Statistics
12.000
40.000
-.896
.370
.432
Mann-Whitney U
Wilcoxon W
Z
Asymp. Sig. (2-tailed)
Exact Sig. [2*(1-tailed Sig.)]
– .
39
:) T ( DEPENDENT (PAIRED) SAMPLES T-TEST
.
.
.
iX
iY .
/ =
=n
T T n
2 2
22T
T df
1df n
– .
40
) 1(
0 05..
Before 96 110 90 94 107 93 89 120 103 92
After 90 96 85 87 104 85 76 103 95 84 Before 86 94 86 110 105 123 95 90 111 123
After 78 84 80 102 95 109 89 83 102 107
:
0 05. Analyze Compare Means Paired- Samples T Test
) T ( SPSS
Paired Samples Statistics
100.8500 20 12.11035 2.7079691.7000 20 10.13644 2.26658
x_beforey_after
Pair1
Mean N Std. DeviationStd. Error
Mean
Paired Samples Correlations
20 .957 .000x_before & y_afterPair 1N Correlation Sig.
Paired Samples Test
9.15000 3.78744 .84690 7.37742 10.92258 10.804 19 .000x_before - y_afterPair 1Mean Std. Deviation
Std. ErrorMean Lower Upper
95% ConfidenceInterval of the
Difference
Paired Differences
t df Sig. (2-tailed)
R = 0.957.
t = 10.804Sig. (2 tailed) = 0.000
– .
41
(Sig.) 0.000
)9.15 (
0 05..
= 9.15 = 3.787
9 15 0 2 4163 787
. . ..
0 0 2 41620
1 .8 4 .
2
22
10 804 0 86010 804 19
. ..
– .
42
) 2(
) (
( )-
.
.
) .
.(
.
( ) .
) (
) T ( SPSS
Paired Samples Statistics
30.45 20 4.019 .89934.20 20 6.066 1.356
- -
Pair 1Mean N Std. Deviation
Std. ErrorMean
Paired Samples Correlations
20 .771 .000 - & -
Pair 1N Correlation Sig.
Paired Samples Test
-3.750 3.919 .876 -5.584 -1.916 -4.280 19 .000 - - -
Pair 1Mean Std. Deviation
Std. ErrorMean Lower Upper
95% Confidence Intervalof the Difference
Paired Differences
t df Sig. (2-tailed)
– .
43
R =
0.771.
t = -4.280Sig. (2 tailed) = 0.000
.
(Sig.) 0.000
)-3.750 (
0 05..
= -3.750 = 3.919
3 750 0 9573 919
. ..
4 28 0 95720. .
2
22
4 28 0 4914 28 19
. ..
– .
44
)1(
12
.
. (2,1), (3,2), (2,0), (1,3), (2,1), (6,3), (5,3), (4,1), (5,2), (3,2), (2,3), (4,2)
Paired Samples Statistics
Mean N Std. Deviation Std. Error Mean
Pair 1 1.9167 12 .99620 .28758
3.2500 12 1.54479 .44594
Paired Samples Test
Paired Differences
t df
Sig. (2-
tailed) Mean
Std.
Deviation
95% Confidence Interval of
the Difference
Lower Upper
Pair
1
-
-1.33 1.55700 -2.32260 -.34406 -2.966 11 .013
– .
45
)2(
:
.
( ) .
( ) ( )
45 44 47 48 48 42 47 43 47 46
45 36 35 46 42 36 42 39 38 47
:
Paired Samples Statistics Mean N Std. Deviation Std. Error Mean
Pair 1 45.7000 10 2.11082 .66750
() 40.6000 10 4.42719 1.40000
Paired Samples Test
Paired Differences
t df
Sig. (2-
tailed) Mean
Std.
Deviation
95% Confidence Interval of
the Difference
Lower Upper
Pair
1
-
()
5.1 4.04008 2.20990 7.99010 3.992 9 .003
– .
46
:) ONE-WAY ANOVA ) 1(
:)ANOVA_1(
70 64 48 83 45 94 87 56 83 78 50 84 71 80
87
90
0 05.
Analyze Compare Means One-Way ANOVA
SPSS:
Levene's Test of Equality of Error Variancesa
Dependent Variable:
.322 2 13 .730F df1 df2 Sig.
Tests the null hypothesis that the error variance of thedependent variable is equal across groups.
Design: Intercept+a.
Tests of Between-Subjects Effects
Dependent Variable:
1849.093a 2 924.546 6.044 .014 .48279835.608 1 79835.608 521.891 .000 .9761849.093 2 924.546 6.044 .014 .4821988.657 13 152.974
89394.000 163837.750 15
SourceCorrected ModelIntercept
ErrorTotalCorrected Total
Type III Sumof Squares df Mean Square F Sig.
Partial EtaSquared
R Squared = .482 (Adjusted R Squared = .402)a.
– .
47
= 0.322Sig. = 0.73
F = 6.044Sig. = 0.014
0 05. .
= 0.482
. Post - Hoc One-Way ANOVA Scheffe .
Multiple Comparisons
Dependent Variable: Scheffe
22.30 8.297 .057 -.59 45.19-1.36 7.752 .985 -22.74 20.03
-22.30 8.297 .057 -45.19 .59-23.66* 7.242 .020 -43.64 -3.68
1.36 7.752 .985 -20.03 22.7423.66* 7.242 .020 3.68 43.64
(J) (I) Mean
Difference (I-J) Std. Error Sig. Lower Bound Upper Bound95% Confidence Interval
Based on observed means.The mean difference is significant at the .05 level.*.
Sig. =0.020
0 05..
) 23.66-.(
2 1849.093 0.482
3837.75between
total
SSSS
– .
48
)1(
:
: :
: .
..
1 - .
2 -
.
3 - )2(
4- ) 3 () 1.(
5-
– .
49
.401 11 .000 .650 11 .000
.307 11 .005 .765 11 .003
.195 11 .200 .968 11 .868
Statistic df Sig. Statistic df Sig.
Kolmogorov-Smirnov Shapiro-Wilk
3575822 2 1787910.939 57.824 .000
927593.6 30 30919.788
4503416 32
Between Groups
Within Groups
Total
Sum of
Squares df Mean Square F Sig.
Dependent Variable:
Scheffe
45.45455 .833 -147.6302 238.5393
719.90909 .000 526.8243 912.9939
-45.45455 .833 -238.5393 147.6302
674.45455 .000 481.3698 867.5393
-719.90909 .000 -912.9939 -526.8243
-674.45455 .000 -867.5393 -481.3698
(J) (I)
Mean
Difference
(I-J) Sig.
Lower
Bound Upper Bound
95% Confidence Interval
Test Statistics a,b
21.961
2
.000
Chi-Square
df
Asymp. Sig.
Kruskal Wallis Testa.
Grouping Variable: b.
11 21.05
11 23.95
11 6.00
33Total
N Mean Rank
– .
50
)2(
: : :
. :
.
1 - .
2 - .
3 - ) 2(
4 -
– .
51
5- ) 3 (Sig
Tests of Normality
.175 3 . 1.000 3 1.000
.175 3 . 1.000 3 1.000
.221 5 .200 .953 5 .758
Statistic df Sig. Statistic df Sig.
Kolmogorov-Smirnov Shapiro-Wilk
Test of Homogeneity of Variances
.857 2 8 .460
Levene
Statistic df1 df2 Sig.
ANOVA
4620.000 2 2310.000 7.605 .014
2430.000 8 303.750
7050.000 10
Between Groups
Within Groups
Total
Sum of Squares df Mean Square F Sig.
– .
52
Multiple Comparisons
Dependent Variable:
Scheffe
-55.00000 .015 -97.4957 -12.5043
-33.00000 .087 -71.0093 5.0093
22.00000 .281 -16.0093 60.0093
(J) (I) Mean Difference (I-J) Sig. Lower Bound Upper Bound
95% Confidence Interval
Ranks
3 2.17
3 9.00
5 6.50
11Total
N Mean Rank
Test Statisticsa
6.729
2
.035
Chi-Square
df
Asymp. Sig.
Kruskal Wallis Testa.
– .
53
)3(
) 24
8 .SPSS
.
.
– .
54
.
(Sheffe)
Levene's Test of Equality of Error Variances
F df1 df2 Sig. 0.946 2 21 0.404
F Sig. 1,898.583 2 949.292 13.121 0.000
1,519.375 21 72.351
3,417.958 23
Scheffe
Sig.
4.63 0.563
20.75 0.000
16.12 0.004
– .
55
)4(
.
) .(
"
( ) .
.
.
.
.
.
.
SPSS
Levene's Test of Equality of Error Variancesa
Dependent Variable:
2.804 2 27 .078F df1 df2 Sig.
Tests the null hypothesis that the error variance of thedependent variable is equal across groups.
Design: Intercept+a.
Tests of Between-Subjects Effects
Dependent Variable:
244.867a 2 122.433 41.425 .000 .75410453.333 1 10453.333 3536.842 .000 .992
244.867 2 122.433 41.425 .000 .75479.800 27 2.956
10778.000 30324.667 29
SourceCorrected ModelIntercept
ErrorTotalCorrected Total
Type III Sumof Squares df Mean Square F Sig.
Partial EtaSquared
R Squared = .754 (Adjusted R Squared = .736)a.
– .
56
= 2.804Sig. = 0.078 .
F = 41.425Sig. = 0.000
.
0 05. = .0.754
Scheffe .
Multiple Comparisons
Dependent Variable: Scheffe
6.70* .769 .000 4.71 8.695.10* .769 .000 3.11 7.09
-6.70* .769 .000 -8.69 -4.71-1.60 .769 .134 -3.59 .39-5.10* .769 .000 -7.09 -3.111.60 .769 .134 -.39 3.59
(J) (I) Mean
Difference (I-J) Std. Error Sig. Lower Bound Upper Bound95% Confidence Interval
Based on observed means.The mean difference is significant at the .05 level.*.
-
000.0 Sig. = 0 05..
)6.70.(
-
000.0 Sig. = 0 05..
)5.10.(
-
134Sig. =0. 0 05..
– .
57
:Without Interaction Two-Way ANOVA
) 1(
. 10 9 8 7 6 5 4 3 2 1
74 83 94 68 76 60 90 70 80 90 1 80 68 82 79 65 50 70 60 92 82 2 68 93 71 86 92 90 80 82 65 76 3
(
(05.0
:
Tests of Between-Subjects Effects
Dependent Variable:
1052.733a 11 95.703 .649 .766178795.200 1 178795.200 1212.597 .000
746.133 9 82.904 .562 .810306.600 2 153.300 1.040 .374
2654.067 18 147.448182502.000 30
3706.800 29
SourceCorrected ModelIntercept
ErrorTotalCorrected Total
Type III Sumof Squares df Mean Square F Sig.
R Squared = .284 (Adjusted R Squared = -.154)a.
:
:F = 0.562 )Sig. = 0.81 05.0 ( )
:
:F = 1.040 )Sig. = 0.374 05.0 ( )
2 2 2 *
**
, ,A B A BA B A B
Error A Error B Error A B
SS SS SSSS SS SS SS SS SS
– .
58
)1(
.SPSS
1 -
.
2 -
3 -
.
– .
59
Dependent Variable:
186.750 5 37.350 11.492 .005 .90546500.750 1 46500.750 14307.923 .000 1.000
118.500 2 59.250 18.231 .003 .85968.250 3 22.750 7.000 .022 .77819.500 6 3.250
46707.000 12206.250 11
SourceCorrected ModelIntercept
ErrorTotalCorrected Total
Type III Sumof Squares df Mean Square F Sig.
Partial EtaSquared
Multiple Comparisons
Dependent Variable: Scheffe
-7.5000 1.27475 .003 -11.5885 -3.4115-2.2500 1.27475 .285 -6.3385 1.83855.2500 1.27475 .018 1.1615 9.3385
(J) (I)
MeanDifference
(I-J) Std. Error Sig. Lower Bound Upper Bound95% Confidence Interval
Multiple Comparisons
Dependent Variable: Scheffe
4.0000 1.47196 .160 -1.5607 9.56076.0000 1.47196 .037 .4393 11.56071.0000 1.47196 .923 -4.5607 6.56072.0000 1.47196 .630 -3.5607 7.5607
-3.0000 1.47196 .335 -8.5607 2.5607-5.0000 1.47196 .075 -10.5607 .5607
(J) (I)
MeanDifference
(I-J) Std. Error Sig. Lower Bound Upper Bound95% Confidence Interval
– .
60
: With Interaction Two-Way ANOVA ) 1(
( ) .
: .
.
.
. :
) 1 2 ) (1 :2 :3 ( :
1 -
2 -
3 - Analyze General Linear Model Univariate
:
Between-Subjects Factors
1515101010
12123
Value Label N
Tests of Between-Subjects Effects
Dependent Variable:
3984.267a 5 796.853 13.344 .000 .73537878.533 1 37878.533 634.304 .000 .964
34.133 1 34.133 .572 .457 .0233678.867 2 1839.433 30.803 .000 .720
271.267 2 135.633 2.271 .125 .1591433.200 24 59.717
43296.000 305417.467 29
SourceCorrected ModelIntercept
* ErrorTotalCorrected Total
Type III Sumof Squares df Mean Square F Sig.
Partial EtaSquared
R Squared = .735 (Adjusted R Squared = .680)a.
– .
61
:Sig.=0.457
:Sig.=0.000
:Sig.=0.125
Multiple Comparisons
Dependent Variable: scoreTukey HSD
8.70* 3.456 .048 .07 17.3326.60* 3.456 .000 17.97 35.23-8.70* 3.456 .048 -17.33 -.0717.90* 3.456 .000 9.27 26.53
-26.60* 3.456 .000 -35.23 -17.97-17.90* 3.456 .000 -26.53 -9.27
(J) methodDicussListenNotesListenNotesDicuss
(I) methodNotes
Dicuss
Listen
MeanDifference (I-J) Std. Error Sig. Lower Bound Upper Bound
95% Confidence Interval
Based on observed means.The mean difference is significant at the .05 level.*.
Notes DISCUSS .
Notes Listen .
. .
.
gender method
.
.
– .
62
Estim
ated
Mar
gina
l Mea
ns
50
40
30
20
10
Estimated Marginal Means of
– .
63
) 2(
( )
)Example11.(
3B 2B 1B
2.3, 1.6 1.8, 2.2 2, 1.5 1A
1.7, 2.1 2.3, 1.5 2.3, 2.6 2A
2.3, 1.7 2.1, 1.8 1.5, 2 3A
1.9, 1.5 1.5, 2.1 2.1, 1.8 4A
05.0:
(
(
(
:
Tests of Between-Subjects Effects
Dependent Variable:
.835a 11 .076 .588 .80688.935 1 88.935 688.529 .000
.228 3 .076 .589 .634
.033 2 .016 .126 .883
.574 6 .096 .741 .6271.550 12 .129
91.320 242.385 23
SourceCorrected ModelIntercept
* ErrorTotalCorrected Total
Type III Sumof Squares df Mean Square F Sig.
R Squared = .350 (Adjusted R Squared = -.246)a.
:
F = 0.126 Sig. = 0.883 05.0 ( )
:
F = 0.589 Sig. = 0.634 05.0 ( )
:
– .
64
F = 0.741 )0.627Sig. = 05.0 ( )
0H
Post Hoc… Bonferroni
– .
65
: ANOVA Within Groups (Repeated Measures ANOVA)
) 1(
. .
.
.
1. ) 15 .(
2. )
15 .(
3. ) 15 .(
4. ) 15
.(
5. ) 15
.(
( )
( ) .
.
) .(
Analyze General Linear Model Repeated Measures
: Mauchly's Test of Sphericityb
Measure: MEASURE_1
.094 41.250 9 .000 .442 .484 .250Within Subjects Effectfactor1
Mauchly's WApprox.
Chi-Square df Sig.Greenhouse-
Geisser Huynh-Feldt Lower-bound
Epsilona
Tests the null hypothesis that the error covariance matrix of the orthonormalized transformed dependent variables is proportional to anidentity matrix.
May be used to adjust the degrees of freedom for the averaged tests of significance. Corrected tests are displayed in theTests of Within-Subjects Effects table.
a.
Design: Intercept Within Subjects Design: factor1
b.
– .
66
"Mauchly's Test of Sphericity" " Sphericity
Condition" F .Sig.=0.000 .
F " Epsilon".
Tests of Within-Subjects Effects
Measure: MEASURE_1
1547.660 4 386.915 207.754 .0001547.660 1.769 874.709 207.754 .0001547.660 1.938 798.734 207.754 .0001547.660 1.000 1547.660 207.754 .000
141.540 76 1.862141.540 33.617 4.210141.540 36.815 3.845141.540 19.000 7.449
Sphericity AssumedGreenhouse-GeisserHuynh-FeldtLower-boundSphericity AssumedGreenhouse-GeisserHuynh-FeldtLower-bound
Sourcefactor1
Error(factor1)
Type III Sumof Squares df Mean Square F Sig.
- Sphericity Assumed :
- Greenhouse-Geisser :
Greenhouse-Geisser Sig.
=0.000
Pairwise Comparisons
Measure: MEASURE_1
11.150* .634 .000 9.139 13.1616.250* .403 .000 4.971 7.529
10.250* .652 .000 8.179 12.3217.200* .408 .000 5.906 8.494
-11.150* .634 .000 -13.161 -9.139-4.900* .390 .000 -6.138 -3.662
-.900* .270 .035 -1.758 -.042-3.950* .407 .000 -5.242 -2.658-6.250* .403 .000 -7.529 -4.9714.900* .390 .000 3.662 6.1384.000* .363 .000 2.849 5.151
.950* .185 .001 .364 1.536-10.250* .652 .000 -12.321 -8.179
.900* .270 .035 .042 1.758-4.000* .363 .000 -5.151 -2.849-3.050* .387 .000 -4.279 -1.821-7.200* .408 .000 -8.494 -5.9063.950* .407 .000 2.658 5.242-.950* .185 .001 -1.536 -.364
3.050* .387 .000 1.821 4.279
(J) factor123451345124512351234
(I) factor11
2
3
4
5
MeanDifference (I-J) Std. Error Sig.a Lower Bound Upper Bound
95% Confidence Interval forDifferencea
Based on estimated marginal meansThe mean difference is significant at the .05 level.*.
Adjustment for multiple comparisons: Bonferroni.a.
– .
67
: Mixed ANOVA ) 1(
.
( )
.
..
Analyze General Linear Model Repeated Measures
:
Multivariate Testsb
.881 62.926a 2.000 17.000 .000 .881
.119 62.926a 2.000 17.000 .000 .8817.403 62.926a 2.000 17.000 .000 .8817.403 62.926a 2.000 17.000 .000 .881
.959 197.963a 2.000 17.000 .000 .959
.041 197.963a 2.000 17.000 .000 .95923.290 197.963a 2.000 17.000 .000 .95923.290 197.963a 2.000 17.000 .000 .959
Pillai's TraceWilks' LambdaHotelling's TraceRoy's Largest RootPillai's TraceWilks' LambdaHotelling's TraceRoy's Largest Root
Effect
*
Value F Hypothesis df Error df Sig.Partial EtaSquared
Exact statistica.
Design: Intercept+ Within Subjects Design:
b.
* Sig.=0.000.
Mauchly's Test of Sphericityb
Measure: MEASURE_1
.920 1.426 2 .490 .926 1.000 .500Within Subjects Effect Mauchly's W
Approx.Chi-Square df Sig.
Greenhouse-Geisser Huynh-Feldt Lower-bound
Epsilona
Tests the null hypothesis that the error covariance matrix of the orthonormalized transformed dependent variables is proportional to anidentity matrix.
May be used to adjust the degrees of freedom for the averaged tests of significance. Corrected tests are displayed in theTests of Within-Subjects Effects table.
a.
Design: Intercept+ Within Subjects Design:
b.
(Sig.=0.490) Sphericity Assumed
– .
68
Tests of Within-Subjects Effects
Measure: MEASURE_1
880.533 2 440.267 68.554 .000 .792880.533 1.851 475.702 68.554 .000 .792880.533 2.000 440.267 68.554 .000 .792880.533 1.000 880.533 68.554 .000 .792
2254.933 2 1127.467 175.557 .000 .9072254.933 1.851 1218.213 175.557 .000 .9072254.933 2.000 1127.467 175.557 .000 .9072254.933 1.000 2254.933 175.557 .000 .907231.200 36 6.422231.200 33.318 6.939231.200 36.000 6.422231.200 18.000 12.844
Sphericity AssumedGreenhouse-GeisserHuynh-FeldtLower-boundSphericity AssumedGreenhouse-GeisserHuynh-FeldtLower-boundSphericity AssumedGreenhouse-GeisserHuynh-FeldtLower-bound
Source
*
Error( )
Type III Sumof Squares df Mean Square F Sig.
Partial EtaSquared
Sig. =0.000
)Sig. =0.000(.
Sig. =0.000
.(Partial Eta Squared) 0.923
Tests of Between-Subjects Effects
Measure: MEASURE_1Transformed Variable: Average
11454.017 1 11454.017 1322.465 .000 .9871870.417 1 1870.417 215.956 .000 .923
155.900 18 8.661
SourceIntercept
Error
Type III Sumof Squares df Mean Square F Sig.
Partial EtaSquared
) (
( )
– .
69
321
Estim
ated
Mar
gina
l Mea
ns
35
30
25
20
15
10
5
Estimated Marginal Means of MEASURE_1
– .
70
Non-Parametric Tests
SPSS
"Sign Test"
"Wilcoxon Test"
– .
71
– "Mann Whitney Test"
– "Kruskal-Wallis Test"
.( )
"Friedman Test"
(Repeated Measures) .
– .
72
:Sign Test t
SPSS
) 1(
15
60
. 25 84 95 30 90 85 60 87 86 64 88 89 92 94 88
60
05..
60.
: Analyze Non-Parametric Tests Binomial Test
SPSS
Descriptive Statistics
14 78.36 22.775 25 95N Mean Std. Deviation Minimum Maximum
Binomial Test
<= 60 2 .14 .50 .013> 60 12 .86
14 1.00
Group 1Group 2Total
Category NObserved
Prop. Test Prop.Exact Sig.(2-tailed)
Sig.=0.013
60
05.60 .
) 60( 12 86% 60
– .
73
: Wilcoxon Test 10
)10 (1 )6 5
) - .(
.
SPSS
) 1(
12
(2,1), (3,2), (2,0), (1,3), (2,1), (6,3), (5,3), (4,1), (5,2), (3,2), (2,3), (4,2).
0 05.. Analyze Non-Parametric Tests 2 Related Samples…
SPSS
Ranks
2a 5.25 10.5010b 6.75 67.50
0c
12
Negative RanksPositive RanksTiesTotal
- N Mean Rank Sum of Ranks
> a.
< b.
= c.
Test Statisticsb
-2.266a
.023ZAsymp. Sig. (2-tailed)
-
Based on negative ranks.a.
Wilcoxon Signed Ranks Testb.
23Sig.=.0
0 05. 0 05.
( ) 6.75
( ) 5.25
.
– .
74
14 1
1prbTr
n n
:
1T :n :
prbr :0.4 :0.4 0.70.7 0.9
:0.9. 14 1
14 67 5 1
12 12 10 73
prbTr
n n.
.
– .
75
: - Mann-Whitney Test –
.
– ( ) t ( )
SPSS
) 1(
( ) ) .
. ( ) :
14 3
11 6
12 4
9 20
6 6
4 5
3 8
7 2 2
1
Analyze Non-Parametric Tests 2-Independent Samples…
– SPSS
Ranks
10 9.85 98.508 9.06 72.50
18Total
N Mean Rank Sum of Ranks
– .
76
Test Statisticsb
36.50072.500
-.312.755
.762a
Mann-Whitney UWilcoxon WZAsymp. Sig. (2-tailed)Exact Sig.[2*(1-tailed Sig.)]
Not corrected for ties.a.
Grouping Variable: b.
Sig=0.762
0 05. .
0 05.
1 2
1 2
2rb
MR MRr
n n
:
1MR :2MR :
1n :2n :
rbr
:0.4 :0.4 0.70.7 0.9
:0.9.
1 2
1 2
2
2 9 85 9 0610 8
0 088
rb
MR MRr
n n
. .
.
– .
77
) 2(
.
)Mann-Whitney_2(
40 29 44 27 33 32 26 25 31 27 29 28 34 31 31 23 38 37 33 28 42 22 35 31 24
0 05.
– SPSS Ranks
12 17.54 210.5013 8.81 114.5025Total
N Mean Rank Sum of Ranks
Test Statisticsb
23.500114.500
-2.972.003
.002a
Mann-Whitney UWilcoxon WZAsymp. Sig. (2-tailed)Exact Sig.[2*(1-tailed Sig.)]
Not corrected for ties.a.
Grouping Variable: b.
:Sig.=.002
0 05..
17.54 8.81
.
– .
78
1 2
1 2
2
2 17 54 8 8112 13
0 698
rb
MR MRr
n n
. .
.
– .
79
:– Kruskal-WallisTest - –
SPSS
) 1(
86 82 75 81 66 78 84 69 61 71 72 69 81 67 75 88 30 79 77 77
0 05. )Wallis-Kruskal(
Analyze Non-Parametric Tests k Independent Samples…
– .
80
- SPSS
Ranks
8 15.067 7.145 7.90
20Total
N Mean Rank
Test Statisticsa,b
8.0022
.018
Chi-SquaredfAsymp. Sig.
Kruskal Wallis Testa.
Grouping Variable: b.
8.002Sig.=.018
3
0 05.. .
15.06
)7.147.90 (.
2 1H
H kn k
:
H : -2(K :n :
2H ) :2( :0.0620 06 0 14. . :20 14 0 23. .2 0 23.
2 1
8 002 3 120 3
0 35
HH k
n k.
.
– .
81
: FriedmanTest
)
.
.
SPSS
) 1(
10 . .
8 7 9 8 8 8 8 5 9 8 7 8
0 05. Analyze Non-Parametric Tests k Related Samples…
SPSS
Ranks
3.172.172.672.00
Mean Rank
– .
82
Test Statisticsa
31.875
3.599
NChi-SquaredfAsymp. Sig.
Friedman Testa.
1.875Sig.=0.599
0 05.
.
2
1FF
n k
F :-2(K :n :
2Friedman ) :2(
:0.0620 06 0 14. . :20 14 0 23. .2 0 23.
2
11 875
12 4 10 05
FF
n k.
.
– .
83
) 2(
) (
10 7 11 13
8 13 6 10 7 15 11 9
11 11 9 14 9 12 8 11 7 8 7 12 8 14 5 10
11 10 10 13
0 05.
SPSS
Ranks
1.563.191.883.38
Mean Rank
Test Statisticsa
812.346
3.006
NChi-SquaredfAsymp. Sig.
Friedman Testa.
12.346Sig.=.006
0 05.. .
1.56
) 3.191.88 3.88 (
2 12 346 0 129
1 32 4 1FF . .
n k
– .
84
Relationships
CORRELATION
.
)
.
Dependent (Response) Variable :
Y.
Independent (Explanatory) Variable :
X .
X Y XY.
.
X, Y Scatter plot
X, Y
Correlation Coefficient Y, X r
1 1r 11
– .
85
1
r = 0 (
.
r 1 1 .
.X, Y
120 r.
31
2 4r.
34 1r
12 0r
21
43 r
431 r
:
1r
.8r
.6r
.4r
.2r
0r
.1r
.3r
.5r
– .
86
.7r .9r 1r
– .
87
) 1(
.
. 30
.
)correlation1(
1.
2. .( )
3. )
.(
4. )
.(
5.
.
Analyze – Correlate – Bivariate
Exercise IQ 0.614 Sig. =0.000
30 . 0 05..
SPSS Correlations
1 .897** .691** -.614** .614**.000 .000 .000 .000
30 30 30 30 30.897** 1 .696** -.562** .511**.000 .000 .001 .004
30 30 30 30 30.691** .696** 1 -.243 .421*.000 .000 .196 .021
30 30 30 30 30-.614** -.562** -.243 1 -.225.000 .001 .196 .231
30 30 30 30 30.614** .511** .421* -.225 1.000 .004 .021 .231
30 30 30 30 30
Pearson CorrelationSig. (2-tailed)NPearson CorrelationSig. (2-tailed)NPearson CorrelationSig. (2-tailed)NPearson CorrelationSig. (2-tailed)NPearson CorrelationSig. (2-tailed)N
exercise
esteem
satisfy
stress
iq
exercise esteem satisfy stress iq
Correlation is significant at the 0.01 level (2-tailed).**.
Correlation is significant at the 0.05 level (2-tailed).*.
– .
88
) 2(
)correlation2(
:
SPSS
Correlations
1.000 .718*. .019
10 10.718* 1.000.019 .
10 10
Correlation CoefficientSig. (2-tailed)NCorrelation CoefficientSig. (2-tailed)N
Spearman's rho
Correlation is significant at the 0.05 level (2-tailed).*.
=0.718
. Sig.=.019
– .
89
Test Chi-Square
) 1(
.
.
39 : .
– – .( )
: .– –
.
.
)chi_square1(.
5 80%
Analyze – Descriptive Statistics – Crosstabs
* Crosstabulation
9 3 1 133.7 4.7 4.7 13.0
69.2% 23.1% 7.7% 100.0%1 10 2 13
3.7 4.7 4.7 13.07.7% 76.9% 15.4% 100.0%
1 1 11 133.7 4.7 4.7 13.0
7.7% 7.7% 84.6% 100.0%11 14 14 39
11.0 14.0 14.0 39.028.2% 35.9% 35.9% 100.0%
CountExpected Count% within CountExpected Count% within CountExpected Count% within CountExpected Count% within
Total
Total
– .
90
Chi-Square Tests
34.208a 4 .00032.871 4 .000
19.118 1 .000
39
Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases
Value dfAsymp. Sig.
(2-sided)
9 cells (100.0%) have expected count less than 5. Theminimum expected count is 3.67.
a.
Sig. =0.000
df :) (
( )
2 1df 0.10 0.30 0.50
3 2df 0.07 0.21 0.35
4 3df 0.06 0.17 0.29
2 34 208 0 439 0 662
39 2c c.V . .
n df
– .
91
)1(
.
1 - .
2 -
3 - ) 2 (
4 - ) 1 . (
– .
92
20 20 40 80
32.0 32.0 16.0 80.0
25.0% 25.0% 50.0% 100.0%
20 20 0 40
16.0 16.0 8.0 40.0
50.0% 50.0% .0% 100.0%
40 40 0 80
32.0 32.0 16.0 80.0
50.0% 50.0% .0% 100.0%
80 80 40 200
80.0 80.0 40.0 200.0
40.0% 40.0% 20.0% 100.0%
10
20
40
Total
75.000 4 .00089.257 4 .000
34.068 1 .000
200
Pearson Chi-SquareLikelihood RatioLinear-by-LinearAssociationN of Valid Cases
Value dfAsymp. Sig.
(2-sided)
– .
93
Linear Regression
Simple Linear Regression
Independent variable x
Dependent variable y.
) y () x.(
) Scatter
Plot(
) Scatter
Plot(
yx, y
y
y x xy 10
x
y
0 y
1 y x.
– .
94
( )
( )
(Dummy Variables) " 0" "1 "
) 1(
300 350 500 600 900 1000 900 1200 1050 250
280 340 500 550 800 750 850 1050 1000 250
:
Income(J.D)
a . Enter
Model1
VariablesEntered
VariablesRemoved Method
Variables Entered/Removedb
All requested variables entered.a.
Dependent Variable: Consumption (J.D)b.
.982a .965 .960 58.6090Model1
R R SquareAdjustedR Square
Std. Errorof the
Estimate
Model Summary
Predictors: (Constant), Income (J.D)a.
751329.9 1 751329.9 218.727 .000a
27480.111 8 3435.014778810.0 9
RegressionResidualTotal
Model1
Sum ofSquares df
MeanSquare F Sig.
ANOVAb
Predictors: (Constant), Income (J.D)a.
Dependent Variable: Consumption (J.D)b.
48.229 43.913 1.098 .304
.835 .056 .982 14.789 .000
(Constant)Income(J.D)
Model1
B Std. Error
UnstandardizedCoefficients
Beta
Standardized
Coefficients
t Sig.
Coefficientsa
Dependent Variable: Consumption (J.D)a.
– .
95
:
Consump. = 48.229 + 0.835 * Income
= 0.982
). 0.000 0.05Sig(
965.02R =0.96 = 58.6190.
96.5% ( )
3.5%
F= 218.727000.0.Sig
098.1t0bSig.=0.304
789.14t1bSig.=0.000
– .
96
) 2(
.
25 .
.
.
.
1 - " X "
"Y."
2-
3 - )
.( Analyze Regression Linear
:
Model Summary
.826a .683 .669 47.332Model1
R R SquareAdjusted R
SquareStd. Error ofthe Estimate
Predictors: (Constant), a.
R=0.826 :
R Square=0.683 :( )68.3%
ANOVAb
110987.2 1 110987.191 49.541 .000a
51526.81 23 2240.296162514.0 24
RegressionResidualTotal
Model1
Sum ofSquares df Mean Square F Sig.
Predictors: (Constant), a.
Dependent Variable: b.
– .
97
Coefficientsa
221.126 15.964 13.852 .00015.929 2.263 .826 7.039 .000
(Constant)Model1
B Std. Error
UnstandardizedCoefficients
Beta
StandardizedCoefficients
t Sig.
Dependent Variable: a.
= 221.126 +15.929 *
Sig. =0.000
– .
98
)1(
) Y ( )1X (
)2X ( 1990 -2012 .
1. .
2. .
3. " " .
4.
5. ( ) " " ) 4 (
Model Summary
.995a .990 .989 2.15754Model1
R R SquareAdjustedR Square
Std. Error ofthe Estimate
Predictors: (Constant), x2, x1a.
– .
99
ANOVAb
9040.379 2 4520.189 971.045 .000a
93.099 20 4.6559133.478 22
RegressionResidualTotal
Model1
Sum ofSquares df Mean Square F Sig.
Predictors: (Constant), x2, x1a.
Dependent Variable: yb.
Coefficientsa
52.029 24.038 2.164 .043-.395 .152 -.472 -2.601 .017.035 .012 .525 2.893 .009
(Constant)x1x2
Model1
B Std. Error
UnstandardizedCoefficients
Beta
StandardizedCoefficients
t Sig.
Dependent Variable: ya.
– .
100
Multiple Linear Regression
) y (1x 2x
n
y 12 , xx
22110 xxy
22110ˆ xbxbby
Y
1 2 kX ,X , , X.
– .
101
) 1(
salary salbegin
educ minority )1 =0 ( =474
- salary salbegin, educ, minority .
-
Model Summary
.891a .794 .792 $7,783.85Model1
R R SquareAdjusted R
Square
Std. Errorof the
Estimate
Predictors: (Constant), Minority Classification,Educational Level (years), Beginning Salary
a.
ANOVAb
1.09E+11 3 3.65E+10 602.097 .000a
2.85E+10 470 605882611.38E+11 473
RegressionResidualTotal
Model1
Sum ofSquares df
MeanSquare F Sig.
Predictors: (Constant), Minority Classification, Educational Level (years),Beginning Salary
a.
Dependent Variable: Current Salaryb.
Coefficientsa
-7200.395 1792.199 -4.018 .0001.664 .059 .767 28.186 .000
1009.327 160.440 .171 6.291 .000-1394.343 875.659 -.034 -1.592 .112
(Constant)Beginning SalaryEducational Level (years)Minority Classification
Model1
B Std. Error
UnstandardizedCoefficients
Beta
Standardized
Coefficients
t Sig.
Dependent Variable: Current Salarya.
salary salbegin, educ, minority :
Salary = -7200.395 + 1.664 * Salbegin + 1009.327 * Educ – 1394.343 * Minority
2 .Salary salbegin, educ, minority .891
.
3 .794.0R 2 =.792 = 7783.85
– .
102
79.4% ( )
20.6%
F=602.097. 0.000Sig
018.4t0bSig.=0.000
186.28t1bSig.=0.000
291.6t2bSig.=0.000
592.1t2bSig.=0.112
– .
103
)1(
.
.
.
30 .
)
) .(
.(
.( )
)
(
.( )
)
) .(
developmental ability (.
1 -
2 - .
Analyze Regression Linear
:
Model Summary
.930a .865 .849 5.664Model1
R R SquareAdjusted R
SquareStd. Error ofthe Estimate
Predictors: (Constant), homeenv, temper, supporta.
– .
104
ANOVAb
5326.979 3 1775.660 55.342 .000a
834.221 26 32.0856161.200 29
RegressionResidualTotal
Model1
Sum ofSquares df Mean Square F Sig.
Predictors: (Constant), homeenv, temper, supporta.
Dependent Variable: developb.
Coefficientsa
-8.307 5.344 -1.555 .132.447 .071 .663 6.284 .000.291 .148 .165 1.967 .060.563 .271 .221 2.080 .048
(Constant)supporttemperhomeenv
Model1
B Std. Error
UnstandardizedCoefficients
Beta
StandardizedCoefficients
t Sig.
Dependent Variable: developa.
Predicted DEVELOP = -8.307 + 0.447 *(SUPPORT) + 0.291 *(TEMPER) + 0.563 *(HOMEENV)
Stepwise Model Summary
.899a .809 .802 6.487 .809 118.416 1 28 .000
.919b .844 .833 5.958 .036 6.193 1 27 .019
Model12
R R SquareAdjusted R
SquareStd. Error ofthe Estimate
R SquareChange F Change df1 df2 Sig. F Change
Change Statistics
Predictors: (Constant), supporta.
Predictors: (Constant), support, homeenvb.
ANOVAc
4982.957 1 4982.957 118.416 .000a
1178.243 28 42.0806161.200 295202.779 2 2601.390 73.285 .000b
958.421 27 35.4976161.200 29
RegressionResidualTotalRegressionResidualTotal
Model1
2
Sum ofSquares df Mean Square F Sig.
Predictors: (Constant), supporta.
Predictors: (Constant), support, homeenvb.
Dependent Variable: developc. Coefficientsa
6.509 3.246 2.005 .055.606 .056 .899 10.882 .000
-3.299 4.942 -.667 .510.476 .073 .705 6.487 .000.689 .277 .271 2.489 .019
(Constant)support(Constant)supporthomeenv
Model1
2
B Std. Error
UnstandardizedCoefficients
Beta
StandardizedCoefficients
t Sig.
Dependent Variable: developa. Predicted DEVELOP = -3.299 + 0.476 *(SUPPORT) + 0.689 *(HOMEENV)
– .
105
)2(
:
.
1. .
2. .
3. "
"
– .
106
4.
5. " "
6. )
.(
.856 .733 .724 .65940Model1
R R SquareAdjustedR Square
Std. Error ofthe Estimate
150.190 4 37.547 86.354 .00054.786 126 .435
204.976 130
RegressionResidualTotal
Model1
Sum ofSquares df Mean Square F Sig.
.173 .508 .341 .734
.257 .103 .208 2.494 .014
.142 .106 .140 1.343 .182
.226 .108 .241 2.088 .039
.367 .090 .341 4.100 .000
(Constant)Model1
B Std. Error
UnstandardizedCoefficients
Beta
StandardizedCoefficients
t Sig.
– .
107
)3(
) Profits (
) :Dep () Inv (
) Fas () Bra(
) Lab(1980-2009.
1.
2. .
3. .
– .
108
4. "
"
5.
6.
– .
109
.913 .834 .800 5.50148Model1
R R SquareAdjustedR Square
Std. Error ofthe Estimate
3654.606 5 730.921 24.150 .000726.391 24 30.266
4380.998 29
RegressionResidualTotal
Model1
Sum ofSquares df Mean Square F Sig.
Coefficientsa
-.250 7.740 -.032 .974
-.095 .364 -.027 -.260 .797
-.010 .014 -.107 -.710 .484
.048 .014 1.729 3.498 .002
-.073 .019 -2.304 -3.771 .001
.138 .019 1.584 7.236 .000
(Constant)
Model
1
B Std. Error
Unstandardized
Coefficients
Beta
Standardized
Coefficients
t Sig.
Dependent Variable: a.