DATA ANALYSIS AND STATISTICS

Data from all the different research tools, namely the HKQ, DDQ and DDS, tuck shop visits, PQL, Self-Administered Questionnaire for Educators and PQE was captured electronically in Microsoft Excel® spreadsheets with regular cross-referencing to ensure precision of data transfer. The objectives of the study were discussed by using descriptive statistics. Data was analysed with the assistance of the Centre for Statistical Consultation using Statsoft Inc. (2011) STATISTICA (data analysis software), version 10.0. (www.statsoft.com).11

Descriptive summary statistics such as means, medians, frequencies and standard deviations were used to describe the perception and acceptability of the FFG in all the selected Grade 4 educators, for example, whether they regarded the FFG as HP, if the FFG could be a valuable tool in NE, and whether the children enjoyed playing an educational nutrition board game. Relationships and associations between variables were determined by using appropriate inferential statistics

3.4.1 HealthKick Questionnaire for Learners

Descriptive summary statistics such as means, medians, frequencies and standard deviations were used to describe the characteristics of all the selected Grade 4 learners, for example, age, gender, language, number of household members, and who assisted them with homework. Relationships and associations between variables were determined by using appropriate inferential statistics.

Regression or multiple regression analysis (like Spearman rank correlations and Pearson correlations) was used when continuous variables were compared with other continuous

variables. Normal probability plots were constructed to test for normality of residuals in the particular analysis where required, and appropriate scatter plots of variables involved were given. Analysis of variance was used when continuous variables were compared vs. nominal variables. A non-parametric method like the Bonferroni test was used if the residuals were not normally distributed.

A non-parametric method was used (Bonferroni test) where ordinal were compared vs. nominal variables and appropriate contingency tables were constructed where nominal variables were compared with other nominal variables. No categorical data analysis was used. A p-value of <0.05 was used to indicate the significance of the results. Missing data was excluded per variable.

3.4.2 Dietary Diversity Questionnaire and Dietary Diversity Score

Descriptive summary statistics such as means, medians, frequencies and standard deviations were used to describe the characteristics of all the selected Grade 4 learners per school in the pre- vs. the post-setting, for example, did they have breakfast, did they bring a lunch box to school, did they visit the tuck shop, did they consume fast food, eggs, fish and shellfish, legumes, nuts and seeds, and milk and milk products. Relationships and associations between variables were determined by using appropriate inferential statistics.

Regression or multiple regression analysis (like rank correlations) was used when continuous variables were compared with other continuous variables. Normal probability plots were constructed to test for normality of residuals in the particular analysis where required, and appropriate scatter plots of variables involved were given. Analysis of variance was used when continuous variables were compared vs. nominal variables. Non-parametric methods like the Wilcoxon Matched-Pairs test and Box-and-Whisker plot were used if the residuals were not normally distributed, and histograms were used if variables could not be analysed because of no or too little variation.

Non-parametric methods were used (like the Wilcoxon Matched-Pairs test and Box-and- Whisker plot) where ordinal was compared vs. nominal variables and appropriate contingency tables were constructed where nominal variables were compared with other nominal variables. Histograms were used if no or too few variables were reported. Categorical data analysis (chi-square tests), for example, maximum-likelihood (M-L) chi-square test, Pearson‘s chi-square test, Yates‘s chi-square test, Fisher‘s exact, one-tailed, Fisher‘s exact, two-tailed,

and McNemar‘s chi-square (A/D) was used. Cross-tabulation results were done with the McNemar test. A p-value of <0.05 was used to indicate the significance of the results. Missing data was excluded per variable.

3.4.3 Tuck Shop Visits by Selected Grade 4 Learners

Descriptive summary statistics such as means, medians, frequencies and standard deviations were used to describe the characteristics of all the selected Grade 4 learners per school, for example, tuck shop visits in the pre- and post-setting. Relationships and associations between variables were determined by using appropriate inferential statistics.

The tuck shop visits were reported on the DDQ. Regression or multiple regression analysis (like rank correlations) was used when continuous variables were compared with other continuous variables. Normal probability plots were constructed to test for normality of residuals in the particular analysis where required, and appropriate scatter plots of variables involved were given. Analysis of variance was used when continuous variables were compared vs. nominal variables. Non-parametric methods like the Wilcoxon Matched-Pairs test and Box-and-Whisker plot were used if the residuals were not normally distributed, and histograms were used if variables could not be analysed because of no or too little variation.

Non-parametric methods were used (like the Wilcoxon Matched-Pairs test and Box-and- Whisker plot), where ordinal was compared vs. nominal variables and appropriate contingency tables were constructed where nominal variables were compared with other nominal variables. Histograms were used if no or too few variables were reported. Categorical data analysis (chi-square tests), for example, maximum-likelihood (M-L) chi-square test, Pearson‘s chi-square test, Yates‘s chi-square test, Fisher‘s exact, one-tailed, Fisher‘s exact, two-tailed, and McNemar‘s chi-square (A/D) was used. Cross-tabulation results were done with the McNemar test. A p-value of <0.05 was used to indicate the significance of the results. Missing data was excluded per variable.3.4.3 Dietary Diversity Questionnaire and Dietary Diversity Score.

Descriptive summary statistics such as means, medians, frequencies and standard deviations were used to describe the perception and acceptability of all the selected Grade 4 learners, for example, learners thought more about what they ate, they liked to learn about food, they learned to play the game easily, they would play again, it was fun, the time it took for learners to play the FFG once, and whether they thought they could play the FFG independently.

Relationships and possible associations between variables were determined by using appropriate inferential statistics.

3.4.4 The Perception Quantitative Questionnaire for English-speaking Grade 4 learners Descriptive summary statistics such as means, medians, frequencies and standard deviations were used to describe the perception and acceptability of all the selected Grade 4 learners, for example, learners thought more about what they ate, they liked to learn about food, they learned to play the game easily, they would play again, it was fun, the time it took for learners to play FFG once, and whether they thought they could play the FFG independently. Relationships and possible associations between variables were determined by using appropriate inferential statistics.

3.4.5 Self-Administered Questionnaire for Grade 4 Educators

Descriptive summary statistics such as means, medians, frequencies and standard deviations were also used to describe the characteristics of all the selected Grade 4 LO educators, for example, gender, qualifications, experience (years) in teaching NE, time spent on NE, tools to assist learning, and sources of nutrition advice. Relationships and possible associations between variables were determined by using appropriate inferential statistics.

3.4.6 The Post-Knowledge Quantitative and Qualitative Questionnaire for Grade 4 Life Orientation Educators

Descriptive summary statistics such as means, medians, frequencies and standard deviations were used to describe the perception and acceptability of the FFG in all the selected Grade 4 educators, for example, do you regard the FFG as HP, the FFG could be a valuable tool in NE, and children enjoyed playing an educational nutrition board game. Relationships and associations between variables were determined by using appropriate inferential statistics.