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Statistical Analysis and Power Calculations: Sample Size Estimation and Research Design Considerations

Comprehensive assignment on sample size estimation and power calculations in research design.

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    5/27/2015 Statistics DeaconIceLion4113 Course Name

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    Solution1. Compare and Contrast Internal and External Validity Internal Validity External Validity The internal validity depends over the accuracy of the results. Therefore, if the sample did not select randomly , then it affect the internal validity because internal validity depends over the data collection method. T he external validity includes the concepts of generalization to know the impacts of the results for the larger population (Herek, 2012). Hence, it also depends over the data collection method as like internal validity. The internal validity generally makes some dealing with the research study without the help of other research elements. E xternal validity looks over that situation, when one could take the outcomes of the research study and simplify it in a broader perspective. The generalization also works with the help of external validity ( Kimmel, 2007). It could be better understood with an example. When researchers conduct a research study for the testing of drug, the drug organization could not consist in the test population as the target population. Let’s take an example: “To identify the impact of changes in ecology on the living style of teenagers Hispanic” then it would be very difficult to generalize and simplify the outcomes of this question for the whole people of the Hispanic community. In this situation internal va lidity is a primary concern because without it, the result of the study could not be effective ( Herek, 2012) . Let’s take an example: “To identify the impact of changes in ecology on the living style of Hispanic”. Then, for this research question, the external validity could be a primary concern because this question focuses over the whole group of Hispanic instead of someone or a partic ular group. For making strong claims in the context of applicability of findings towards a target population the researchers use the random sampling method, systematic samples, and cluster sampling for gathering the information and data from the selected population ( Kimmel, 2007). This strategy plays an effective role in the generalization of study outcomes because the sampling process based on probability always includes the high response rate that helps the researchers to apply the result of study in the broader mann er.

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    Solution2. Compare and Contrast Random Selection and Random Assignment Random Selection Random Assignment The random selection describes how the research could draw the sample from the whole population related to the research study . T he random assignment describes about the process of researchers that they use to assign and draw the sample from different groups of the population ( Trochim, 2006). A n example. If a researcher draws 50 people from a group of 500 people with the help of random sample, then it would call random sampling. If the researcher selects 50 people for new treatment instead of remaining 450 people from whole population then it would be called random assignment. In some situation, when the researcher does not use the random sample to select the population but selected the some people for providing the different treatment, then the random selection could not be applied but random assignment could be used ( McNabb, 2010). Random selection depends over sampling process and it is directly related to the external validity of the study results ( Trochim, 2006). R andom assignment is related to the study design and also related to the internal validity of the study’s result. Solution 3 . Sample Size and Likelihood of a Statistically Significance In the sense of statistics, significance is also a statistical term, which helps to ensure the difference and relationship takes place in two groups. It also depends on the sample size (StatPac Inc., 2013). For example, in a study, 50 people are selected for a test and the merit would be decided on the basis of male and female category. T he males score 100 and the females score 98. The t - test gives the difference in significance is .001. At the same time, there is no huge difference in 100 and 98. This result describes that there is small difference between the groups that could not make n egative impact on the outcomes of the study. Therefore, it could be stated that the sample size makes the drastic impacts on the outcomes of the study, whether the study is conducted for any population or for

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