Statistical Data Analysis
Undertaking a survey is useless if there is a lack of proper skills and facilities to do an appropriate statistical analysis of the collected data. The primary function of Html surveys is to gather enough data to allow for more informed decisions. If the statistic of survey data is not properly collated from the survey form, analyzed and presented that purpose is defeated completely. For many a proper data analysis seems too far fetched to be undertaken by them as any thing related to statistic is feared but in reality it need not be so. Data analysis and interpretation is so vital that it should even be thought about from the preparation of the online survey plan.
You could easily at least do elementary data analysis. You simply start from analyzing one data variable at a go, then two and then more than two at one time. Two variable analyses being examined at a go is referred to as Bivarite analysis. The analysis of more than two variables at one time is called multivariate analysis. Most of online surveys however concern just one or two variables so data analysis is much easier. Analyzing single data variables concerns checking of variable results one at a go. Common techniques used include the use of tables, percentage and frequency measurement. Measures of central tendency such as mean, median and mode also come in handy.
The term frequency measures the number of occurrence of a particular unit. If a conducted online survey reports that 50 women out of 100 smoke, that would mean that the frequency of female smokers is 50. If that information is expressed in percentage it would become; 50% of the conducted survey are female smokers. Frequency measurement could be tabulated to become tabled data, if more than one variable is involved then the table would be involve cross tabulation.
Most variables based on questions used in the survey form are presented in single tabulated frequency table. Answers to questions such as are you married? Do you own a car? and others would all get to be presented in a table. Tables are thus drawn from eSurvey results of age, sex, income bracket, education level, occupation and the like.
It may become necessary to pick a most occurring survey result within a variable question. Questions such as number income size might generate numerous varied answers. Statistical measures using mean, mode and median are useful to find out average figure to represent the group. Thus we could have an average income size of web based survey group. Mean median and mode are all methods in statistics used to measure averages.
Data analysis usually falls under qualitative or quantitative analysis. The methods mentioned above are all quantitative methods of doing statistical data analysis. It is concerned and restricted to measuring quantities and frequency of variable occurrences. Qualitative data analysis is concerned with measuring the effects and quality of collated data. If 50 women from 100 are smokers how can the information be used? And questions like that are the concerns of qualitative data analysis.
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