Using statistics for choosing sample size for establishing a hypothesis
Establishing hypothetical questions in a research work through statistical data interpretation is the most important and the most difficult task. In the process of disproving a null hypothesis for establishing a real hypothesis, it is very important that a proper method of data analysis relevant to the research question is used. It is also important to predetermine the specific sample size while carrying out the primary research, to do which a researcher needs to have appropriate statistical knowledge. The different factors that need to be considered while determining a research sample are-
1. the level of precision
2. the confidence level, and
3. the variability degree
The researcher also needs to contemplate whether a small sample population would provide the desired result or a large population would, according to the requirements of the research, in which the mean and the proportion of the sample are major aspects to consider. Unless the researcher has an accurate understanding of his research work and the techniques relevant to his exposition, it would be difficult to calculate the sample size. Depending on whether the data to be collected should be quantitative or categorical, the different formulas necessary for calculating the required size of the sample are used. This calls for understanding of the population proportion and determining the highest limit of error desirable suitable for Type I error risk. The following table can be used to decide upon the correct sample size suitable for nearly all research works, as it provides a suggestion for a favourable size of sample under a ‘specific size of population', ‘specific margin of error(confidence interval)' and the ‘preferred level of confidence'.
Margin of error or confidence interval reflects a plus-or-minus numeral that we normally observe in opinion poll results broadcasted by the television or newspaper, enabling one to pick up a sure answer. Confidence level expresses the level of sureness or reflection of the true percentage of the sample population that would select an answer contained by the confidence interval. The percentage reflected is the percentage of certainty. The greater the acceptance of a wide confidence interval, the greater is the certainty of the entire population answer. Hence to arrive at a definite conclusion pertaining to establishment of a hypothesis, a dissertation statistics help often becomes inevitable, where an authentic conversion of a hypothetical question through statistical analysis takes place.
1. the level of precision
2. the confidence level, and
3. the variability degree
The researcher also needs to contemplate whether a small sample population would provide the desired result or a large population would, according to the requirements of the research, in which the mean and the proportion of the sample are major aspects to consider. Unless the researcher has an accurate understanding of his research work and the techniques relevant to his exposition, it would be difficult to calculate the sample size. Depending on whether the data to be collected should be quantitative or categorical, the different formulas necessary for calculating the required size of the sample are used. This calls for understanding of the population proportion and determining the highest limit of error desirable suitable for Type I error risk. The following table can be used to decide upon the correct sample size suitable for nearly all research works, as it provides a suggestion for a favourable size of sample under a ‘specific size of population', ‘specific margin of error(confidence interval)' and the ‘preferred level of confidence'.
Margin of error or confidence interval reflects a plus-or-minus numeral that we normally observe in opinion poll results broadcasted by the television or newspaper, enabling one to pick up a sure answer. Confidence level expresses the level of sureness or reflection of the true percentage of the sample population that would select an answer contained by the confidence interval. The percentage reflected is the percentage of certainty. The greater the acceptance of a wide confidence interval, the greater is the certainty of the entire population answer. Hence to arrive at a definite conclusion pertaining to establishment of a hypothesis, a dissertation statistics help often becomes inevitable, where an authentic conversion of a hypothetical question through statistical analysis takes place.
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