My research study is based on investigating how Technology is affecting kids relationships (parents, siblings etc). So I will collect the data through questionnaire sheets filled by kids and observations of their behaviors during technology use.
I would like to know what is suggested data analysis tool to be used for coding the data and understand the phenomena that at what extent technology (mobile, social media etc) harming kids relations.
Have you collected any data in the form of questionnaire? Only after knowing the variables under consideration, anyone can suggest the analysis tool.
Hello Sharda
A. Studying the consistency of the survey and the accuracy of data collection. In order to study the consistency of the survey and the accuracy of data collection, several tests need to be developed. Some of which are the following:
1. The reliability measures could be developed for the whole questionnaire or for each dimension of the questionnaire .
2. Reliability consists of several measures:
Item alpha reliability and split-half reliability assess the internal consistency of the items in a questionnaire – that is, do the items tend to be measuring much the same thing?
Split-half reliability on SPSS refers to the correlation between scores based on the first half of items you list for inclusion and the second half of the items. This correlation can be adjusted statistically to maintain the original questionnaire length.
Coefficient alpha is merely the average of all possible split-half reliabilities for the questionnaire and so may be preferred, as it is not dependent on how the items are ordered. Coefficient alpha can be used as a means of shortening a questionnaire while maintaining or improving its internal reliability.
B. statistical analysis
In order to analysis the data of the questionnaires, the following requirements/assumptions need to be studied:
1. What are the research questions/hypotheses of your research.
2. Analysis of the questionnaire is different than any life data or practical data.
3. The analysis of the questionnaire as also based on the given hypotheses.
4. The assumptions of the sample size, both variables should be normally distributed (normally distributed variables have a bell-shaped curve). Other assumptions include linearity and homoscedasticity. Linearity assumes a straight line relationship between each of the two variables and homoscedasticity assumes that data is equally distributed about the regression line have to be satisfied for all measures of correlation coefficients and hypotheses testing.
5. Most of statistical measures/tests are based on above requirements/assumptions.
6. Then, several tests like T-test, T-test for related data, T-test for independent samples, ANOVA (one way, two way, mixed, ...), Multiple comparisons, ANCOVA, ... could be developed.
7. References:
Landau, S. and Everitt, B. S.(2004). A Handbook of Statistical analyses using SPSS.
Howitt, D. and Cramer, D.(2008). Introduction to SPSS.
Validity and Reliability of Students and Academic Staff’s Surveys to Improve Higher Education. Educational Alternatives, Journal of International Scientific Publications, 2016, Vol.14, pp. 242-263 .
HEIs Quality Improvement Through Students and Academic Staff’s Perception: Data Analysis and Robustness of the Results. International Journal for Quality Research, 2018, Vol.11, No.2, pp.261-278.
Regards,
Zuhair
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