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Research Methodologies Applied To Evaluate The Impact Of Stimulant Energy Drink - Assignment Example

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Objectives of Our Study and the Study Design
The objective of the study was to found the effect whether our new launch energy drink pink cow will be better than the current market leader CML in terms of giving people more energy and keeping them awake.
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Research Methodologies Applied To Evaluate The Impact Of Stimulant Energy Drink
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Methodology Collection Of Data The first thing for any study is the process of data collection and the method of sampling. Data is collected on the basis of sampling which can be randomized, or purposive with respect to the variable that has to be analyzed. Randomized data means each individual will have equal probability to be included in the sample. Purposive data is considered by some criteria fixed by the experimenter (effects of a drug on diabetic patients).Sampling makes sure that the results are based on non biased assumptions and simply random sampling reduces the chance of bias.

So in this study we will fix inclusion criteria with a purposive sampling- that means people who use computers whether desktops and laptops will be included and the others in the population will not be included- thus our purposive sampling will narrow it to population of computer users. The exclusion criteria would be non computer users and having vision problems other than technology related. Data will be collected through a set of questionnaire method:- a. Energy severity score: Rate your self energy on a scale of 1 to 10( more energy feeling more score) b.

Rate your sleep scale from 1-1 0 ( more score more awake) We would see then whether our distribution obtained is symmetrical or asymmetrical and conform to normal distribution and whether undue weightage has been given to extreme values during data collection. Collected data can have a symmetrical representation and in that case mean, median and mode will be the same for a particular variable and when these value changes it is called asymmetrical and this measure is called skewness, On the other hand there can be incidences such the data is collected more on the upper and lower sides of a variable(tails) it will be called leptokurtic data and if the middle values of a variable are collected it is called platykurtic data.

In the former the distribution looks pointed and in later it has a plateau shaped. Ideally if a data is ideally collected then the curve should look mesokurtic with frequency of the scores evenly distributed at upper and lower and middle limits. This is called a normal distribution. The normal distribution has a unit area of one and this is helpful to measure testing of hypothesis.(Chance,2005). Thus the need for data representation becomes important Analysis of Data Testing of Hypothesis: We will take the mean scores of sleepiness and energy in both the groups and go for a testing of hypothesis Data can be analyzed for statistical significance based on the normal distribution.

This means if the computed probability value or p value as measured from t test or Anova is

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