Statistical Design and Analysis Grid

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Statistical Design and Analysis Grid Name Institutional affiliations Statistical designs and analysis grid Statistical Test Definition Strengths Weaknesses Examples of where/how used Correlations Correlation is a statistical method that is used to describe and measure the direction and strength between two variables (Goos & Meintrup, 2016). It requires two results from the same sample. Correlation enables researchers to gather more information compared to experiments (Goos & Meintrup, 2016). The results of correlation are applicable in day to day life since the research occurs outside the lab. Correlation provides room for further studies by other researchers, and it may be easy to find results and cause of relations. One problem with correlations is that they show relationships but not their cause (Graham, 2008). Similarly, the finding of a correlation does not reveal the variable that influences the other. Unknown variables may influence others in a relationship causing confusion (Graham, 2008). Correlation shows whether a relationship is negative or positive (Graham, 2008). It is an appropriate method of showing quantifiable data. t-tests (student t-tests) These are analysis methods where two populations use statistical examination (Goos & Meintrup, 2016). Two samples are used for the test with small sample sizes, and the variance determined even when the normal distributions are not known (Rencher & Schaalje, 2008). In research, t-tests are easy to calculate since computers are used. These tests allow for ease of gathering information as little data is required (Rencher & Schaalje, 2008). T-tests also accommodate robustness as

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