Geoff And Francis
Currently Browsing: Data Analysis

Open Ended Questions – How to devise open ended questions in your survey questionnaire for PhD research

An open-ended question is an open question where the response is recorded verbatim. An open-ended question is nearly always an open question. (It would be wasteful to record yes-no answers verbatim.)Open-ended questions are also known as ‘unstructured’ or ‘free response’ questions. Open-ended questions are used for a number of reasons: The researcher cannot predict what the responses might be, or it is dangerous to do so. Questions about what is liked and disliked about a product or service should always be open-ended, as it would be presumptuous to assume what people might like or dislike by having a list of pre-codes. We wish to know the precise phraseology that people used to respond to the question. We may be able to predict the general sense of the response but wish to know the terminology that people use. We may wish to quote some verbatim responses in the report or the presentation to illustrate something such as the strength of feeling that respondents feel. In response to the question ‘why will you not use that company again?’, a respondent may write in: ‘They were that awful. They mucked me for months, didn’t respond to my letters and when they did they could never get anything right. I shall never use them again.’ Had pre-codes been given on the questionnaire this might simply have been recorded as ‘poor service’.The verbatim response provides much richer information to the end-user of the research. Through analysis on the verbatim responses, clients can determine if the customer is talking about a business process, a policy issue, a people issue (especially in service delivery surveys), etc. This enables them to determine the extent of any challenges they will face when reporting the findings of the survey to their management. Common uses for open-ended questions include : Likes and dislikes of a product, concept, advertisement, etc; Spontaneous...

Preparing for Interviews – Guide for Qualitative Research

There are many different types of question that can be asked and in many different ways. What is common to all questions, though, is that they must be worded in a way that is understood by the respondents and to which respondents can relate. This means ensuring that there are minority-language versions of the questionnaire if the sample is likely to include people who speak a language is unlikely to be sufficiently good to be able to complete an interview in it. By denying sections of the survey population the opportunity to participate in the study, the questionnaire writer is effectively disenfranchising them from influencing the findings. For many studies commissioned by the public sector in countries, it is important that the interview is capable of being conducted in any language that is spoken by a significant number of people in the any language that is the spoken by a significant number of people in the survey population to avoid the danger of disenfranchisement. In the UK Many government studies require questionnaire versions in Welsh, Urdu, Hindi and other languages, and in USA a Spanish-language version will often be required. read...

An introduction to Data Mining & its Applications in Bioinformatics

With the increasing importance of bioinformatics in agriculture, molecular medicine, microbial genome applications, etc. the research in this field has gained momentum than ever before. Bioinformatics, also known as computational biology, deals with interpreting biological data by using computer science and information technology. Of lately, research in bioinformatics has produced vast amounts of data and will continue to generate proteomic, genomic, etc. data. To analyze and gain deep insights into such biological data necessitates making sense of the information by inferring the data. For instance, gene classification, protein structure prediction, clustering of gene expression data, protein-protein interactions, etc. These processes, in turn, increases the need for interaction between bioinformatics and data mining.   read...

Spoiler Alert Ahead: 6 Great Steps for Conducting Factor Analysis using SPSS

Statistics, a scientific approach to investigating statistical data, is employed to determine associations among the phenomena to define, predict and control their occurrence. To successfully perform statistical tests, it is a must to identify the underlying factors or variables under study. This is when the factor analysis comes into the picture.   Factor analysis, known as a dimension reduction technique, helps to reduce the dimension creating new factors from the old ones by checking the correlations and eigenvalue.  read...

One-Way MANOVA Test: How to Assess If Mean Differences Exist Between the Samples Using SPSS?

It is extended version an ANOVA with two or more dependent variables. ANOVA test is used for evaluating the difference in means between two or more related groups, while a MANOVA test is used for evaluating the difference in two or more vectors of factors.  ASSUMPTIONS: All the observations should be statistically independent. We should have an adequate sample size. As a larger sample size, the better it is. We should be having more cases than the number of variables in each group. In ANOVA, the Dependent variables are normally distributed within the group. whereas in MANOVA,the Dependent variables have multivariate normality within the groups. There are no univariate or multivariate outliers. Univariate outliers are often just called outliers.In one-way MANOVA, we see how to:         (1) detect univariate outliers using box plots using SPSS statistics in order to check outliers         (2) check for multivariate outliers using Mahalanobis distance, which we can do in SPSS  read...