1. SPSS STATISTICS GUIDE FOR RESEARCH BY PETER JAMES KPOLOVIE

2. WORLD REVOLUTIONS The world has experienced several revolutions. The revolution that most impacted or changed the world for the better is Information and Communication Technology (ICT). ICT has so revolutionized all spheres of human endeavour to the extent that effective ICT use or otherwise in any given area is synonymous with the success or failure, respectively of that field (Kpolovie & Iderima, 2016; Kpolovie, 2020, 2021, 2022).

3. M OST E SSENTIAL R EQUIREMENT Mastering how to personally make the best use of ICT is the most essential requirement for any person or organization seeking competitive advantage over others. True success in today’s changed, rapidly changing and highly competitive world depends on ICT skills mastery. Refusal to embrace the opportunities offered by ICT today is tantamount to absolute failure in any field of human endeavour one is engaged in (Kpolovie, 2018).

4. APPLICATION OF IBM SPSS STATISTICS Learning in the university must be technologically mediated with the most suitable educational software. Research can best be done with the application of ICT. The greatest challenge facing every contemporary and subsequent researcher is how to personally utilize ICT effectively and efficiently in data analyses. ICT usage is the bedrock for national survival and development in the rapidly changing global village we live in.

5. M OST C OMPREHENSIVE S TATISTICAL S OFTWARE A landmark advancement in ICT application is IBM SPSS® Statistics. SPSS is the most comprehensive statistical software system for accurate analyses of all types of data. SPSS is by far the most widely used computer package for statistical analysis globally. Learning to use SPSS is a necessity for research execution, making of inventions, discoveries and innovation. SPSS makes use of only simple menu and dialog box selections to perform analyses.

6. SPSS ACQUISITION/SUBSCRIPTION IBM SPSS Statistics (SPSS) is the world's leading statistical software. SPSS is the fastest software for accurate data analysis and interpretation. Visit IBM SPSS ® Statistics Website at https://www.ibm.com/products/spss-statistics to purchase it. https://www.ibm.com/products/spss-statistics It is very easily to Subscribe to use the software instantly at the Website.

7. FOUR FORMS OF SPSS You will also be able to start practicing SPSS with the available Free Trial Version even before you either subscribe or buy the software. For buying or subscription, special offer for students is as well available at the Website. Each Version of SPSS has four forms: 1.Base, 2.Standard, 3.Professional 4.Premium.

8. SPSS APPLICATION STEPS

9. COMPARISON OF GROUPS FOR DIFFERENCE Research mainly make use of the listed statistical tests for analyzing data that deal with group comparisons.  One-sample t Test  Independent-samples t Test  Paired-sample t Test

10. GROUP COMPARISON ANALYSIS  One-way Analysis of Variance (ANOVA)  Two-way Analysis of Variance (Two-way ANOVA)  Three-Way ANOVA  Repeated-measures ANOVA  Analysis of Covariance (ANCOVA)  Multivariate Analysis of Variance.

11. INDEPENDENT-SAMPLES T TEST. As the name implies, the Independent-Samples t Test is used for comparison of means from two independent samples on a dependent variable. An investigation that compares two independent groups in terms of one dependent variable, uses the Independent-Samples t Test for analyzing the data. Whenever Randomized Between-Subjects After Only Experimental Design is adopted for an investigation, the suitable statistical technique is the Independent- Samples t Test.

12. INDEPENDENT SAMPLES T TEST The most common scenario where t Test is applied is for comparison of two means, each from a completely independent sample. In such situation, the type of t Test applied is called t Test for independent means or t Test for independent samples. Most frequently, researchers engage in comparison of means from two samples that are randomly drawn independently from two separate populations.

13. T TEST: EFFECT OF ASPIRIN ON THE LEANING OF NONSENSE SYLLABLES. Control group35224043383946504441 30 2928324336404835 Experimental group3830202332184240222619 3320323829252837242338

14. HOW THE DATA ARE ENTERED

15. ANALYZE > COMPARE MEANS > INDEPENDENT-SAMPLES T TEST >

16. NMC INDEPENDENT SAMPLES T TEST SYNTAX Apart from the Dialog Boxes Selection Method, SYNTAX Method can also be used to execute the analysis. The Syntax is as follows. T-TEST GROUPS=Treatment(1 2) /MISSING=ANALYSIS /VARIABLES=Learning /ES DISPLAY(TRUE) /CRITERIA=CI(.95).

17. DESCRIPTIVE STATISTICS

18. INDEPENDENT SAMPLES TEST

19. INDEPENDENT SAMPLES EFFECT SIZE.

20. INTERPRETATION The p value (Sig.) of.001 for 2-tailed test is less than the chosen alpha of 0.05 or even 0.01. The null hypothesis in the example under consideration is therefore rejected. That is, the mean of control group’s (1) scores on the learning of nonsense syllables (M = 37.4500, SD = 7.35903) is significantly higher than the experimental group’s (2) mean (M = 28.9545, SD = 7.51809).

21. INTERPRETATION CONTD. The null hypothesis is rejected: (t = 3.694, df = 40, two-tailed p = 0.001). Technically, the difference is statistically significant; the null hypothesis is rejected as [t (40) = 3.694, p <.05, 2-tailed, d = 1.141, a Large Effect Size]. The conclusion drawn, the means, the standard deviations and the computed t ratio here with SPSS are the same as what were obtained with the manual computations.

22. EFFECT SIZE FOR T TEST COHEN’S D d AS THE EFFECT SIZE IN t Test DESCRIPTIVE CLASSIFICATION OF THE d 0.000 to 0.199Trivial Effect Size 0.200 to 0.499Small Effect Size 0.500 to 0.799Medium Effect Size 0.800 and aboveLarge Effect Size

23. CORRELATED-SAMPLES T TEST. Correlated-Samples t Test is also termed Paired-Samples t Test. It is used for comparison of means when the members of a single group each has two scores. They could be scores on a pretest and post test, or scores on two variables. The Paired-samples t Test analysis is used to determine whether the two sets of scores differ significantly.

24. ANXIETY BEFORE AND AFTER BLOOD DONATION. Anxiety Before Blood Donation Anxiety After Blood Donation Anxiety Before Blood Donation Anxiety After Blood Donation 70807068 64707479 65608088 80837268 90896775 72747986 83886470 77807588 69658286 81876970 75867173 69706865 60508788 66786370 85907880 9095

25. PAIRED-SAMPLES T TEST: ANXIETY BEFORE AND AFTER BLOOD DONATION.

26. ENTER DATA > ANALYZE > COMPARE MEANS > PAIRED-SAMPLES T TEST > TRANSFER Variables > OK:

27. SYNTAX FOR PAIRED-SAMPLES T TEST EXECUTION. T-TEST PAIRS=AnxietyBefore WITH AnxietyAfter (PAIRED) /ES DISPLAY(TRUE) STANDARDIZER(SD) /CRITERIA=CI(.9500) /MISSING=ANALYSIS.

28. PAIRED SAMPLE STATISTICS

29. PAIRED SAMPLES CORRELATIONS

30. PAIRED SAMPLES TEST

31. PAIRED SAMPLES EFFECT SIZE

32. INTERPRETATION The Paired Samples correlation coefficient is 0.866 which is statistically significant even at.001 alpha. The Paired Samples Test has mean difference of - 3.35484. A standard deviation of 5.28866 and a standard error of mean of.94987. The computed paired samples t ratio is -3.532 with 30 degrees of freedom and a p value of.001.

33. CONTD. INTERPRETATION Since the p value (Sig. 2-tailed) of.001 is less than the chosen alpha of 0.05 and even of 0.01, the null hypothesis of ‘no significant difference in anxiety level before and after blood donation’ is rejected. The correlated samples t test is statistically significant as [t (30) = -3.532, p <.05, p <.01, 2-tailed, d =.634, a Medium Effect Size]. Anxiety after blood donation (M = 77.3871) is significantly higher than before blood donation (M = 74.0323).

34. ONE-SAMPLE T TEST. One-Sample t Test is used for comparison of a group’s mean on a dependent variable with the population mean on the variable. Determination of whether the 2015 Batch A NYSC members have a higher or lower age mean than that of the entire population. Population mean of the NYSC members age is 25. Take a random sample of 66 NYSC members. 22 each from those posted to the three geopolitical regions in Nigeria. Obtain the data from NYSC Directorate.

35. AGE OF 2015 BATCH A NYSC MEMBERS 243029 27 233026283028 2927282629 252827242829 2628 292730 2930 272529 282925283029 30272529 24 292630262830 2927292529 28272827 30

36. ONE-SAMPLE T TEST: ENTER AND SAVE THE DATA

37. SYNTAX FOR ONE-SAMPLE T TEST. T-TEST /TESTVAL=25 /MISSING=ANALYSIS /VARIABLES=NYSCAGE /ES DISPLAY(TRUE) /CRITERIA=CI(.95).

38. ANALYZE > TRANSFER VARIABLE > TEST VALUE > OK: OUTPUT

39. ONE-SAMPLE EFFECT SIZE

40. INTERPRETATION The computed t value (12.804), df (65), Sig. for 2-tailed test (.000), mean difference (2.81818). Lower (2.3786) and upper (3.2577) interval limits at 95% of confidence. The computed t value of 12.804 is statistically significant because Mean = 27.8182, SD = 1.78807, [t (65) = 12.804, p <.001, d = 1.576, a Large Effect Size]. Therefore the null hypotheses of ‘no significant difference between the 2015 Batch A NYSC members’ age and the population age of NYSC members’ is rejected.

41. ONE-WAY ANOVA. Analysis of variance, ANOVA, is a very powerful and most suitable statistical technique for analysis of research data, particularly when three or more means are to be compared. ANOVA is the most commonly used advanced statistical technique in professional, psychological, educational, business, agricultural, behavioral, social, and the natural sciences research.

42. ANOVA WITH SPSS: EFFECT OF INFORMATION PROCESSING TECHNIQUES ON LEARNING. Silent Reading (1) Reading Aloud (2) Recitation (3)Writing (4) 60536584 50586095 40598575 40707585 50757091 55706080 45608072 65557068 48506762 47506888

43. ENTER, CODE, NAME AND SAVE DATA

44. ANALYZE > COMPARE MEANS > ONE WAY ANOVA > MOVE VARIABLES > Options > Descriptive > Homogeneity of variance test > Mean Plot > Continue. P ost hoc pairwise multiple comparisons > Post Hoc > Scheffé > Bonferroni > Continue > OK.

45. ANOVA SYNTAX UNIANOVA Learning BY Infoprotec /METHOD=SSTYPE(3) /INTERCEPT=INCLUDE /PLOT=PROFILE(Infoprotec) TYPE=LINE ERRORBAR=NO MEANREFERENCE=YES YAXIS=AUTO /EMMEANS=TABLES(Infoprotec) COMPARE ADJ(BONFERRONI) /PRINT ETASQ DESCRIPTIVE HOMOGENEITY /CRITERIA=ALPHA(.05) /DESIGN=Infoprotec.

46. ANOVA DESCRIPTIVE STATISTICS

47. LEVENE’S TEST OF ERROR VARIANCES

48. TEST OF BETWEEN-SUBJECTS EFFECT

49. PAIRWISE COMPARISONS

50. INTERPRETATION Descriptives (mean and standard deviation) is used to answer the research question. Test of Homogeneity of variance, has shown Leven statistic of 0.578 which is not significant (p >.05) in line with ANOVA assumptions requirement. ANOVA has presented that for between groups, the sum of squares is 5000.00, with 3 degrees of freedom and a mean square of 1666.667. Within groups sum of squares is 2888.000 and 36 df with a mean square of 80.222.

51. CONTD. INTERPRETATION. The total has 7888.00 sum of squares and 39 degrees of freedom. The computed F is 20.776, which is statistically significant, even as at low as.001 alpha. The null hypothesis “information processing techniques do not significantly affect students’ learning”, is rejected. Technically, reject Ho as [F (3, 36) = 20.776, p <.01, ɳ 2 =.634, a Large Effect Size].

52. CONTD. INTERPRETATION. Multiple Comparisons, shows the six possible pairwise comparisons of the means. While there is significant mean difference between (1) groups 1 and 4, (2) groups 1 and 3 and (3) groups 2 and 4; significant difference was not found for each of the other pairs of means. Mean plot graphically indicates the relative position of each group mean.

53. EFFECT SIZE IN ANOVA – PARTIAL ETA SQUARED Eta Squired or Partial Eta Squired (ɳ 2 ) is used for specification of Effect Size in ANOVA. The Eta Squired (ɳ 2 ) is interpreted as follows: .000 -.009 = Trivial Effect Size. .010 -.059 = Small Effect Size. .060 -.139 = Medium Effect Size. .140 and above = Large Effect Size.

54. TWO-WAY ANOVA. Two-Way ANOVA is used for determination of the effects of two independent variables separately on a dependent variable as well as the collective or joint effect of the two independent variables on the dependent variable. Two-Way ANOVA simultaneously produces three results: 1. The Main Effect of the column variable. 2. The Main Effect of the row variable. 3. The Interaction Effect of the Column and Row variables on the Dependent Variable.

55. TWO-WAY ANOVA SPSS: COUNSELLING AND BEHAVIOR THERAPY EFFECTS ON SOCIAL PHOBIA. Behaviour Therapy Counselling Methods Individual Counselling (4) *T.E. (1)S.D.(2)C.(3) 5060 305540 6530 607050 206520 Group Counselling (5) 807560 908050 609520 709025 609520

56. ENTER, CODE, NAME, LABEL, AND SAVE THE DATASET Analyze > General Linear Model > Univariate.

57. UNIVARIATE DIALOG BOX WITH VARIABLES MOVED

58. UNIVARIATE PLOTS > MOVE VARIABLES > ADD > CONTINUE

59. UNIVARIATE ESTIMATED MARGINAL MEANS, VARIABLE MOVED.

60. UNIVARIATE: OPTIONS

61. Click Continue > Select Options > Check Descriptive statistics > Check Estimates of effect size > Check Homogeneity Tests > Click Continue > Click OK to have the Output displayed.

62. TWO-WAY ANOVA SYNTAX. UNIANOVA Phobia BY Therapy Counselling /METHOD=SSTYPE(3) /INTERCEPT=INCLUDE /PLOT=PROFILE(Therapy*Counselling) TYPE=LINE ERRORBAR=NO MEANREFERENCE=NO YAXIS=AUTO /EMMEANS=TABLES(Therapy) COMPARE ADJ(BONFERRONI) /EMMEANS=TABLES(Counselling) COMPARE ADJ(BONFERRONI) /EMMEANS=TABLES(Therapy*Counselling) /PRINT ETASQ DESCRIPTIVE HOMOGENEITY /CRITERIA=ALPHA(.05) /DESIGN=Therapy Counselling Therapy*Counselling.

63. OUTPUT: DESCRIPTIVE STATISTICS.

64. LEVENE’S TEST OF EQUALITY OF ERROR VARIANCES.

65. TESTS OF BETWEEN-SUBJECTS.

66. ESTIMATED MARGINAL MEANS FOR BEHAVIOUR THERAPY

67. PAIRWISE COMPARISONS FOR BEHAVIOUR THERAPY

68. ESTIMATED MARGINAL MEANS FOR COUNSELLING METHODS

69. PAIRWISE COMPARISONS FOR COUNSELLING METHODS

70. BAHAVIOUR THERAPY INTERACTION WITH COUNSELLING METHODS

71. PROFILE PLOTS: ESTIMATED MARGINAL MEANS OF SOCIAL PHOBIA.

72. INTERPRETATION OF THE OUTPUT Descriptive Statistics of the Social Phobia is provides in the first table of the Two-Way Output. The Levene’s Test of Equality of Error Variances has affirmed the appropriateness of the use of Two-Way ANOVA in analyzing the data. Levene’s Test Statistic of 2.157 has Sig. of.093 that is greater than the chosen alpha of.05.

73. TEST OF BETWEEN-SUBJECTS EFFECTS This table of the Output has revealed that: Behaviour therapy has 7931.667 Sum o Squares 2 degrees of freedom. 3515.833 Mean Square. F of 18.585. Sig. of <.001. Partial Eta Squared of.608.

74. BEHAVIOUR THERAPY EFFECT The F is significant statistically as the Sig is smaller than.05 alpha. Since, the Probability (Sig.) of obtaining an F of 18.586 is smaller that the classically chosen alpha of.05, the null hypothesis of “no significant effect of behaviour therapy on social phobia” is rejected. The Partial Eta Squared (PES) is.608, which depicts a Large Effect Size. Technically, the Ho on effect of Behaviour Therapy on Social Phobia is rejected because [F (2, 24) = 18.586, p <.05, PES =.608, a Large Effect Size].

75. EFFECT OF COUNSELLING ON SOCIAL PHOBIA Counselling has: 2167.500 Sum of Squares. 1 degrees of freedom. 2167.500 Mean Square. F of 11.458. 0.002 Sig..323 Partial Eta Squared.

76. EFFECT OF COUNSELLING The F on Counselling methods is significant statistically as the Sig. is smaller than.05 alpha. Since, the Probability (Sig.) of obtaining an F of 11.458 is smaller than the classically chosen alpha of.05, the null hypothesis of “no significant effect of counselling methods on social phobia” is rejected. The Partial Eta Squared (PES) is.323, which depicts a Large Effect Size. Technically, the Ho on effect of Counselling method on Social Phobia is rejected because [F (1, 24) = 11.458, p <.05, PES =.323, a Large Effect Size].

77. INTERACTION EFFECT OF THERAPY AND COUNSELLING Behaviour Therapy and Counselling Interaction has: 1895.00 Sum of Squares. 2 degrees of freedom. 947.500 Mean Square. 5.009 F..015 Sig..294 Partial Eta Squared.

78. INTERACT EFFECT OF BEHAVIOUR THERAPY AND COUNSELLING The F on Behaviour therapy and Counselling methods Interaction is significant statistically as the Sig. is smaller than.05 alpha. Since, the Probability (Sig.) of obtaining an F of 5.009 is smaller than the classically chosen alpha of.05, the null hypothesis of “no significant interaction effect of behaviour therapy and counselling methods on social phobia” is rejected. The Partial Eta Squared (PES) is.294, which depicts a Large Effect Size. Technically, the Ho on effect of Counselling method on Social Phobia is rejected because [F (2, 24) = 5.009, p <.05, PES =.294, a Large Effect Size].

79. CONCLUSIVE INTERPRETATION Test of Between-Subjects Effects, is the main summary of the independent samples two-way ANOVA. MAIN EFFECT 1. Behavioural therapy has a statistically significant effect on social phobia [F (2, 24) = 18.586, p <.05 or p <.01, η 2 =.608, a Large Effect Size]. MAIN EFFECT 2. Counseling methods has a significant effect on social phobia [F (1, 24) = 11.458, p <.05, p <.01, η 2 =.323, a Large Effect Size].

80. CONTD. CONCLUSIVE INTERPRETATION. INTERACTION EFFECT. The interaction effect of behaviour therapy and counselling methods on social phobia is statistically significant [F (2, 24) = 5.009, p <.05, a Large Effect Size]. Error Sum of Squares is 4540.000 with 24 degrees of freedom and 189.167 MS. The corrected total sum of squares and degrees of freedom are 110275.000 and 30, respectively. Finally, each of the Pairwise Comparisons is significantly different in favour of the group with a higher mean. Profile plots is used to graphically portray the group means and their interaction.

81. EFFECT SIZE IN TWO-WAY ANOVA – PARTIAL ETA SQUARED Partial Eta Squared (ɳ 2 ) is used for specification of Effect Size in ANOVA. The Eta Squired (ɳ 2 ) is interpreted as follows: .000 -.009 = Trivial Effect Size. .010 -.059 = Small Effect Size. .060 -.139 = Medium Effect Size. .140 and above = Large Effect Size.

83. ANCOVA WITH SPSS Random assignment of subjects and treatment conditions in experimental investigations equate the groups with regard to all influences other than the manipulated independent variable(s). However, it has been observed that in some cases, randomization does not totally equate the subjects in each of the experimental conditions prior to administration of the experimental treatment and therefore there is great need for application of ANCOVA.

84. RANDOMIZATION + ANCOVA A combination of randomization and ANCOVA provides exceptional control for the influence of extraneous variables or covariates. This is because ANCOVA statistically adjusts for variables other than the dependent variable which correlate with the dependent variable before exceptional accurate comparison of the means on the dependent variable alone.

85. SITUATIONS FOR USE OF ANCOVA ANCOVA adjusts the dependent variable and eliminates the effect of the covariate from the experiment. Five main situations in which analysis of covariance is necessarily used in research data analysis are: i)Determination of change. ii)Elimination of the effect of nuisance variables. iii)Reduction of the error term. iv)Adjustment of the group means. v)Use of randomization.

86. EFFECT OF MNEMETAB ON THE SUBJECTS’ MEMORY. Group 1 = 40mgGroup 2 = 80mgGroup 3 = placebo CovariatePosttestCovariatePosttestCovariatePosttest 6070508550 608045656055 355055855560 5560 954030 455055854540 45605055 404550803530 45654065 70 607560906050 5540605060

87. ENTER, CODE, NAME, LABEL, & SAVE DATASET

88. DATASET

89. ANALYZE > GENERAL LINEAR MODEL > UNIVARIATE > TRANSFER VARIABLES

90. TRANSFER OF VARIABLES Move Dependent Variable into Dependent variables field. Transfer the Covariate into Covariates field. Move the Independent Variable into Fixed Factors. Select Plots: Move Independent Variable into Horizontal Axis. Click Add. Click Continue.

91. SELECT ESTIMATED MARGINAL MEANS PUSHBUTTON. Transfer Independent Variable into Display Means for. Check Compare Main effects. Look for and choose Bonferroni. Click Continue. Select Options pushbutton.

92. UNIVARIATE OPTIONS Transfer the Independent Variable into Display means for field. Check:  Descriptives statistics.  Estimates of Effect Size.  Homogeneity tests. Click Continue. Click OK.

93. ANCOVA SYNTAX UNIANOVA Memory BY Mnemetab WITH Covariate /METHOD=SSTYPE(3) /INTERCEPT=INCLUDE /PLOT=PROFILE(Mnemetab) TYPE=LINE ERRORBAR=NO MEANREFERENCE=YES YAXIS=AUTO /EMMEANS=TABLES(Mnemetab) WITH(Covariate=MEAN) COMPARE ADJ(BONFERRONI) /PRINT ETASQ DESCRIPTIVE HOMOGENEITY /CRITERIA=ALPHA(.05) /DESIGN=Covariate Mnemetab.

94. ANCOVA OUTPUT

95. LEVENE’S TEST

96. TESTS OF BETWEEN SUBJECTS

97. ESTIMATED MARGINAL MEANS

98. PAIREWISE COMPARISONS

99. UNIVARIATE TESTS

100. PROFILE PLOTS

101. INTERPRETATION Descriptive statistics shows the mean and standard deviation for each of the groups as coded (40mg of Mnemetab = 1, 80mg of Mnemetab = 2 and placebo = 3) and for the total. Leven’s Test of Equality of Error Variance, has an F of.702 which is not significant (p >.05) and thus meets one additional condition or ANCOVA assumptions.

102. TESTS OF BETWEEN SUBJECTS EFFECTS. Tests of Between-Subjects Effects is the actual ANCOVA summary. The Mnemetab has type III sum of squares of 4045.375, 2 df, 2022.688 mean square, 48.222 F ratio and.001 Sig. The Error has type III sum of squares of 1090.577, df of 26 and mean square of 41.945.

103. DECISION BASED ON THE RESULTS The computed F of 48.222 is statistically significant as [F (2, 26) = 48.222, p <.01, PES =.778, a Large Effect Size]. With the effect of the Pretest covaried out, adjusted for, or removed, the null hypothesis of “no significant effect of Mnemetab on memory” is rejected both at.05 and.01 alpha.

104. PAIRWISE COMPARISONS Haven covaried out the effect of the pretest (the covariate), the first group which received 40mg of Mnemetab differs significantly in their memory even at as low as.001 from the second that took 80mg of Mnemotab, and from the third group which received placebo.

105. PAIRWISE COMPARISONS CONTD. The second group (80mg of Mnemetab) also differs significantly even at.001 from group 1 (40mg Mnemetab) and group 3 (placebo). The sub table equally shows lower bound and upper bound at 95% confidence interval for difference for each of the pairwise comparisons to be statistically significant as each mean difference ranges fully above or fully below zero.

106. PAIRWISE COMPARISONS CONTD. Judging from the magnitude of mean difference, group 2 has a mean that is significantly the highest, group 1 has a mean that is significantly second to the highest and group 3 has a mean that is significantly the lowest; p <.05 and p <.01 and even p <.001 in each case. Estimated Marginal Means Profile Plots graphically portray the differences between the three groups.

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108. APPRECIATION THANK YOU IMMENSELY FOR ACTIVELY PARTICIPATING IN THE APPLICATION OF SPSS DATA ANALYSIS FOR COMPARISON OF GROUPS. KPOLOVIE, PETER JAMES CONTACTS: 0916 050 0061 kpolovie1@gmail.com https://www.amazon.com/author/kpolovie.books NEXT, RELATIONSHIP ANALYSES WITH SPSS