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Statistics Project
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Parametric and Nonparametric Inferential Statistical Tests (Statistics Project Sample)




Module 5 focuses on conducting parametric and nonparametric inferential statistical tests: t-tests, chi-square analyses.


Using the website link below, please take some time to answer the following questions:


  1. Identify the types of variables you would need to conduct a Chi-square (last name begins with A-H), one-sample t-test (last name begins with I-P) and paired t-test (last name begins with Q-Z. Be sure to explain the number of dependent and independent variables, and the types of dependent variables necessary for the statistical analysis.


  1. Furthermore, provide a health related example (or using a peer-reviewed article that used a chi-square test) to explain your answer.
Parametric and Nonparametric Inferential Statistical Tests: One-Sample T-Test
[student’s name]
Parametric and Nonparametric Inferential Statistical Tests: One-Sample T-Test
Choosing the right statistical analysis depends on the nature of the variables being tested; and in the case of t-test, the kind of comparison that needs to be made. The one-sample t-test deal compares whether the average of a sample differs significantly from the average of the defined population. In order to use the one-sample t-test, the sample must come from a subset of a normally distributed population and the data to be measured is expressed as an interval ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "URL" : "/stat/mult_pkg/whatstat/", "accessed" : { "date-parts" : [ [ "2015", "3", "15" ] ] }, "author" : [ { "dropping-particle" : "", "family" : "Leeper", "given" : "James D.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Introduction to SAS", "id" : "ITEM-1", "issued" : { "date-parts" : [ [ "2015" ] ] }, "title" : "What statistical analysis should I use?", "type" : "webpage" }, "uris" : [ "/documents/?uuid=b1425787-cb9e-43b2-ac7e-650d2c8dd1d8" ] } ], "mendeley" : { "formattedCitation" : "(Leeper, 2015)", "plainTextFormattedCitation" : "(Leeper, 2015)", "previouslyFormattedCitation" : "(Leeper, 2015)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(Leeper, 2015). Population mean is typically known but population standard deviation is usually unknown. Unlike other statistical tools, one-sample t-test cannot be used to discover relationships between independent and dependent variables. One-sample t-test is usually used for a small sample size where subjects are less than 30. In the case of large samples with the same characteristics described above, a z-test may be used instead.
To better understand how one-sample t-test can be used, let us look at a research that aimed to compare the health-related quality of life (HQoL) among trauma patients with the general population ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1186/1757-7241-19-22", "ISBN" : "1757-7241", "ISSN" : "1757-7241", "PMID" : "21477280", "abstract" : "Trauma patients have impaired health-related quality of life (HRQOL) after trauma. The aim of the study was to assess HRQOL during the first year after trauma and hospital stay in trauma patients admitted to an intensive-care unit (ICU) for >24 hours compared with non-ICU trauma patients and the general population, and to identify predictors of HRQOL.", "author" : [ { "dropping-particle" : "", "family" : "T\u00f8ien", "given" : "Kirsti", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Bredal", "given" : "Inger S", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Skogst...
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