INDIVIDUAL WRITE-UP: THE AMOUNT OF TIME FATHERS OF CHILDREN WITH A DISABILITY PLAY WITH THEIR CHILDREN by Name Liberty University Partial Fulfillment Of the Requirements for EDUC 812 Liberty University 2016 FINDINGS Research Question The research question for this study was: RQ1: Is there a significant difference among the amount of time fathers of children with a disability play with their children? Null Hypothesis The null hypothesis for this study was: H01: There is no significant difference among the amount of time fathers play with their children with no disability, a physical disability, or an intellectual disability. H02: There is no significant difference between the amount of time fathers play with their male or female children. H03: There is no significant interaction among the amount of time fathers play with their male or female children with no disability, a physical disability, or an intellectual disability. Descriptive Statistics Data obtained for the dependent variable play can be found in Table 1. Table 1 Descriptive Statistics Dependent Variable: Play Gender of Disability status Child of the child Male Typically Developing Physical Disability Mental Retardation Total Female Typically Developing Physical Disability Mental Retardation Total Total Typically Developing Physical Disability Mental Retardation Total Mean Std. Deviation Results N Data 7.30 1.829 10 3.00 1.563 10 3.22 1.716 4.55 2.613 29 data screening 6.80 2.201 10 was conducted 3.40 1.897 10 on each 4.00 1.612 11 4.71 2.369 31 dependent 7.05 1.986 20 variable (play) 3.20 1.704 20 screening Two- 9 way ANOVA group's to evaluate differences 3.65 1.663 20 4.63 2.470 60 among groups (gender of child) regarding data inconsistencies and outliers. The examiner sorted the data on each variable and performed screening for inconsistencies. A graphical representation in the form of a box and whisker plot was used to detect outliers on each dependent variable. Data results obtained from the screening found no identifiable errors or inconsistencies.. See Figure 1 for box and whisker plot. Tests of Normality Group Kolmogorov-Smirnova Statistic TL Score .179 df Shapiro-Wilk Sig. Statistic df Sig. 10 .200* .883 10 .140 * AL .224 9 .200 .921 9 .399 SL .105 11 .200* .958 11 .751 *. This is a lower bound of the true significance. a. Lilliefors Significance Correction Figure 1. Box and Whisker Plot for Typically Developing, Physical Disability, and Mental Retardation. Assumptions A Two-Way (ANOVA) analysis of variance was conducted to test the three null hypothesis that looked at the differences among the amount of time fathers play with their children with no disability, a physical disability, or mental retardation. The two-way ANOVA required that the assumptions of normality and homogeneity of variance are met. A test for normality using Shapiro-Wilk was conducted because of the large sample sizes. Shapiro-Wilk was used because the small sample sizes (p < 50). No violations of normality were found. See Table 2 for Shapiro-Wilk test. Table 2 Shapiro-Wilk test of Normality Tests of Normalitya Kolmogorov-Smirnovb Gender of Child play Male Statistic df .161 Shapiro-Wilk Sig. 10 Statistic .200* df .954 Sig. 10 .713 a. Disability status of the child = Typically Developing, Gender of Child = Male Tests of Normalitya Kolmogorov-Smirnovb Gender of Child play Female Statistic df .242 Shapiro-Wilk Sig. 10 Statistic .100 df .819 Sig. 10 .025 a. Disability status of the child = Typically Developing, Gender of Child = Female Tests of Normalitya Kolmogorov-Smirnovb Gender of Child play Male Statistic df .161 Shapiro-Wilk Sig. 10 Statistic .200* df .933 Sig. 10 .475 a. Disability status of the child = Physical Disability, Gender of Child = Male Tests of Normalitya Kolmogorov-Smirnovb Gender of Child play Female Statistic df .224 Shapiro-Wilk Sig. 10 .168 Statistic df .942 Sig. 10 .573 a. Disability status of the child = Physical Disability, Gender of Child = Female Tests of Normalitya Kolmogorov-Smirnovb Gender of Child play Male Statistic .183 df Shapiro-Wilk Sig. 9 .200* Statistic .901 a. Disability status of the child = Mental Retardation, Gender of Child = Male df Sig. 9 .255 Tests of Normalitya Kolmogorov-Smirnovb Gender of Child play Statistic Female df .187 Shapiro-Wilk Sig. 11 .200* Statistic .937 df Sig. 11 .480 a. Disability status of the child = Mental Retardation, Gender of Child = Female The assumption of mormality was met, a Levene's test was used to analyze the variance difference among the amount of time fathers of children with a disability play with their children. The assumption of equality of variance was determined using the Levene's test. No violation was found where (p = .8) The researcher determined there was an equal variance across groups; therefore, the assumption of homogeneity of normality was met. See Table 3 for Levene's Test. For this reason, further analysis could be conducted. Table 3 Levene's Test of Equality of Error Variance Dependent Variable: Play F df1 .427 df2 5 Sig. 54 .828 Tests the null hypothesis that the error variance of the dependent variable is equal across groups. Results for Null Hypothesis One Table 4 Tests of Between-Subjects Effects Dependent Variable: Play Type III Sum Source of Squares Corrected Mean df Square 182.278a 5 1276.571 1 gender .763 1 .763 disable 178.579 2 4.294 Error Total Sig. Observed Squared Parameter Powerb gender * disable Corrected 11.081 .000 .506 55.405 1.000 1276.571 388.025 .000 .878 388.025 1.000 .232 .632 .004 .232 .076 89.289 27.140 .000 .501 54.281 1.000 2 2.147 .653 .525 .024 1.305 .154 54 3.290 1648.000 Intercept Total F Noncent. 177.656 Model 36.456 Partial Eta 60 359.933 59 a. R Squared = .506 (Adjusted R Squared = .461) b. Computed using alpha = .05 Because the null was rejected, post hoc analysis was conducted using a Tukey Test HSD. There was a significant difference between the attitude scores of traditional (M = 18.7, S.D. = 2.9) and senior (M = 22.8, S.D. = 4.5) vocational learners (p = .02). See Table 5 for Multiple Comparisons Groups. Table 5 Multiple Comparisons Multiple Comparisons Dependent Variable: Play Tukey HSD (I) Disability status of the child Typically Developing Physical Disability Mental Retardation (J) Disability status of the child Physical Disability Mental Retardation Mean Difference (I-J) Std. Error Sig. 95% Confidence Interval Lower Upper Bound Bound .000 2.47 5.23 3.40* .574 .000 2.02 4.78 .574 .000 -5.23 -2.47 -.45 .574 .714 -1.83 .93 -3.40* Physical Disability .574 -3.85* Mental Retardation 3.85* .574 .000 -4.78 -2.02 .45 .574 .714 -.93 1.83 Page 1 of 9 SPSS Worksheet 3: (Two-Way ANOVA) This worksheet was developed by Dr. Kurt Michael of Liberty University 2015 Name: Instructions: Lesson 26 Exercise File 2 is located at the end of the chapter under the heading Exercises in your Green and Salkind textbook. Complete the exercise and then complete the worksheet below by filling in the blanks and answering the questions. Note: The two-way ANOVA looks at three null hypotheses at one time. H01: There is no significant difference among the amount of time fathers play with their children with no disability, a physical disability, or an intellectual disability. H02: There is no significant difference between the amount of time fathers play with their male or female children. H03: There is no significant interaction among the amount of time fathers play with their male or female children with no disability, a physical disability, or an intellectual disability. Assumptions Outliers: Create a Box and Whisker plot for each group. Hint: Go to Graph > Legacy Dialog > Boxplot and use the Cluster function. See page 184 in the Salkind and Green textbook for more information on how to display results. Page 2 of 9 Fill in the blanks: Group Outliers (Item #) Are there any outliers? Male Typically No Male Physical No Male Mental No Female Typically No Female Physical No Female Mental No Page 3 of 9 < Note: Remove any outliers from the dataset before continuing.> Assumption of Normality: Run a normality test each group. Hint: Begin by going to Data > Split File > Organize output by groups (see lesson 15, p. 64), then run Analyze > Descriptive > Explore (see lesson 40, p. 327). Insert six Tests of Normality tables below: Tests of Normalitya Kolmogorov-Smirnovb Gender of Child play Statistic Male df .161 Shapiro-Wilk Sig. 10 Statistic .200* df .954 Sig. 10 .713 *. This is a lower bound of the true significance. a. Disability status of the child = Typically Developing, Gender of Child = Male b. Lilliefors Significance Correction Tests of Normalitya Kolmogorov-Smirnovb Gender of Child play Statistic Female df .242 Shapiro-Wilk Sig. 10 Statistic .100 df .819 Sig. 10 .025 a. Disability status of the child = Typically Developing, Gender of Child = Female b. Lilliefors Significance Correction Tests of Normalitya Kolmogorov-Smirnovb Gender of Child play Statistic Male df .161 Shapiro-Wilk Sig. 10 Statistic .200* df .933 Sig. 10 .475 *. This is a lower bound of the true significance. a. Disability status of the child = Physical Disability, Gender of Child = Male b. Lilliefors Significance Correction Tests of Normalitya Kolmogorov-Smirnovb Gender of Child play Statistic Female .224 df Shapiro-Wilk Sig. 10 .168 Statistic .942 a. Disability status of the child = Physical Disability, Gender of Child = Female b. Lilliefors Significance Correction df Sig. 10 .573 Page 4 of 9 Tests of Normalitya Kolmogorov-Smirnovb Gender of Child play Statistic Male df .183 Shapiro-Wilk Sig. .200* 9 Statistic df .901 Sig. 9 .255 *. This is a lower bound of the true significance. a. Disability status of the child = Mental Retardation, Gender of Child = Male b. Lilliefors Significance Correction Tests of Normalitya Kolmogorov-Smirnovb Gender of Child play Statistic Female df .187 Shapiro-Wilk Sig. .200* 11 Statistic .937 df Sig. 11 .480 *. This is a lower bound of the true significance. a. Disability status of the child = Mental Retardation, Gender of Child = Female b. Lilliefors Significance Correction Fill in the blanks: Should you use a Shapiro-Wilks or Kolmogorov-Smirnov test? Why? Answer: Shapiro-Wilks due to small sample size Groups Significance Male Typically Male Physical Male Mental Female Typically Female Physical Female Mental .713 .475 .255 .025 .573 .480 Is the assumption of normality met? Yes Yes Yes No Yes Yes Assumption of Equal Variance: Insert Levene's Test of Equality of Error Variancesa table(s) below. Hint: Begin by going to Data > Split File > RESET > then run the Analyze. Levene's Test of Equality of Error Variancesa Page 5 of 9 Dependent Variable: play F df1 df2 .427 5 Sig. 54 .828 Tests the null hypothesis that the error variance of the dependent variable is equal across groups. a. Design: Intercept + gender + disable + gender * disable Fill in the blanks: Significance Is the assumption of equal variance met? Yes .828 Results Insert Tests of Between-Subjects Effects table(s) below: Tests of Between-Subjects Effects Dependent Variable: play Type III Sum Source Corrected of Squares Mean df Square 182.278a 5 1276.571 1 gender .763 1 .763 disable 178.579 2 4.294 177.656 Model Intercept gender * disable Error 36.456 Partial Eta F Sig. Noncent. Observed Squared Parameter Powerb 11.081 .000 .506 55.405 1.000 1276.571 388.025 .000 .878 388.025 1.000 .232 .632 .004 .232 .076 89.289 27.140 .000 .501 54.281 1.000 2 2.147 .653 .525 .024 1.305 .154 54 3.290 Page 6 of 9 Total 1648.000 60 359.933 59 Corrected Total a. R Squared = .506 (Adjusted R Squared = .461) b. Computed using alpha = .05 Differences among disabilities Fill in the blanks: Results for Disability: d.f. between Groups Value 2 d.f. within Groups 54 F-statistic 27.140 F-critical (See Appendix C in Warner) 3.168 p- value 0.000 Partial Eta Squared .501 Is the F- statistic greater than F-critical? Answer: Yes Is the p- value less than .05? Answer: Yes Should you reject or fail to reject the null? Answer: Reject Null What is the effect size small, medium, or large (See Table 5.2 in Warner, p. 208)? Answer: Medium Should you run post hoc analysis? Answer: Yes Page 7 of 9 If so, between which groups do the differences exist? Answer: \"Typically Developing and Physical Disability\" and \"Typically Developing and Mental Retardation\" Differences between genders Fill in the blanks: Results for Gender: d.f. between Groups Value 1 d.f. within Groups 54 F-statistic F-critical (See Appendix C in Warner) .232 4.020 p- value 0.632 Partial Eta Squared 0.004 Is the F- statistic greater than F-critical? Answer: No Is the p- value less than .05? Answer: No Should you reject or fail to reject the null? Answer: Fail to reject What is the effect size small, medium, or large (See Table 5.2 in Warner, p. 208)? Answer: Small Should you run post hoc analysis? Hint: There are only two groups (Male and Females). Answer: No Page 8 of 9 Interaction among groups Fill in the blanks: Results for Interaction: d.f. between Groups Value 2 d.f. within Groups F-statistic 54 .653 F-critical (See Appendix C in Warner) 3.168 p- value .525 Partial Eta Squared .024 Is the F- statistic greater than F-critical? Answer: No Is the p- value less than .05? Answer: No Should you reject or fail to reject the null? Answer: Fail to reject What is the effect size small, medium, or large (See Table 5.2 in Warner, p. 208)? Answer: Small Descriptive Statistics Fill in the blanks: Groups Male Typically Mean 7.30 S.D. 1.829 Male Physical 3.00 1.563 Male Mental 3.22 1.716 Page 9 of 9 Female Typically 6.80 2.201 Female Physical 3.40 1.897 Female Mental 4.00 1.612