[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-472924-105":59,"doc-detail-472924-en":130},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":123,"head_meta":125,"extra_data":127,"updated_unix":129},105,"en","t-test-types-and-application","t-Test - Types and Application","","t-Test is an inferential, parametric statistical method used to determine whether observed differences between groups are statistically significant or could have occurred by chance. The material explains three major types: independent samples t-test, paired samples t-test, and one-sample t-test, and provides interpretation for comparing numerical means. It also contrasts t-test with correlation and regression, ANOVA, contingency tables, and Fisher’s/chi-square approaches, detailing key assumptions, hypotheses, equations, and practical example scenarios across medicine, sociology, biology, economics, and marketing.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":20,"@type":76,"position":81},"https://docshare.wps.com/document/exam/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/t-test-types-and-application/472924/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/t-test-types-and-application/472924.png","ImageObject",300,407,{"name":92,"@type":93},"Muffet","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-08","2026-09-30",true,{"@type":102,"interactionType":103,"userInteractionCount":29},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What is the purpose of a t-test in inferential statistics?","Question",{"text":112,"@type":113},"A t-test assesses whether differences between group means are statistically significant. It helps determine whether the differences could plausibly be due to chance.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"What are the three main types of t-test described?",{"text":117,"@type":113},"The document lists independent samples t-test (two unrelated groups), paired sample t-test (same group measured at different times), and one-sample t-test (one group mean compared to a known mean).",{"name":119,"@type":110,"acceptedAnswer":120},"How does a t-test differ from ANOVA and from correlation/regression?",{"text":121,"@type":113},"The t-test compares exactly two groups, while ANOVA compares three or more groups. Correlation and regression assess how two variables vary together rather than comparing means between two groups.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},472924,1791398007,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":19,"category_name":20,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":29,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":145},962090768927,"https://ap-avatar.wpscdn.com/davatar_085a072bc5b1113ac321206ff7593b45","t-Test: Types and Application  \nSwami Vidyamritananda  \nThe t test is one type of inferential, parametric statistics.  \nThe t-test tells us how significant the differences between groups are; In other words, it lets us know if those differences (measured in means/averages) could have happened by chance.  \n• There are three main types ofttest:  \n1. Independent Samples t-test  \ncompares the means for two groups.  \n2. Paired sample t-test compares means from the same group at different times (say, one year apart) .  \n3. One sample t-test tests the mean of a single group against a known mean.  \nStudent's t-test or Independent t-test  \nDetermines whether there is a statistically significant difference between the means in two unrelated groups.  \n• E.g. -compare whether systolic blood pressure differs between a control and treated group, IQ between men and women, or any other two groups.  \n• In social science research this type of t-test is mostly used in survey type of research design.  \nIt is also known as independent samplest-test, two sample t-tests, between samples t-test and unpaired samples ttest.  \nCorrelation & Regression  \nT-test  \nANOVA  \nContingency Table  \n• The t-test compares one variable (perhaps blood pressure) between two groups.  \n• Correlation and regression is performed to see how two variables (perhaps blood pressure and heart rate) vary together.  \nT-Test vs Corre lat ion & regression  \n• The t-tests (and related nonparametric tests) compare exactly two groups.  \n• ANOVA (and related nonparametric tests) compare three or more groups.  \nT-Test vs ANOVA  \n• t-test is performed to compare a continuous/scalable variable  \n(e.g. , blood pressure, weight or enzyme activity) .  \n• a contingency table is used to compare a categorical variable (e.g. , [pass vs. fail](pass vs. fail) , viable vs. not  \nviable) .  \nT-Test vs Fishers or ch i-square tests  \nA t-test is used when we are looking at a numerical variable (which is in ratio or interval /scale) -for example, height-and then comparing the averages of two separate populations or groups (categorical variables e.g., males and females) .  \nAssumptions:  \n• Two independent samples; One independent, categorical variable that has two levels/groups. One continuous dependent variable.  \n• Unrelated groups  \n• Data should be normally distributed  \n• The two samples should have the same variance Assumption of homogeneity of variance  \nThe independent t-test assumes the variances of the two groups we are measuring are equal in the population. If variances are unequal, this can affect the Type I error rate. The assumption of homogeneity of variance can be tested using Levene's Test of Equality of Variances.  \nNull Hypothesis:  \nH0 : u1-u2 = 0, where u1 is the mean of first population and u2 the mean of the second.  \nAs above, the null hypothesis tends to be that there is no difference between the means of the two populations; or, more formally, that the difference is zero (so, for example, that thereis no difference between the average heights of two populations of males and females) .  \nEquation:  \nThe difference between the mean divided by the pooled standard error of the mean.  \nExample:  \nStudent’s T-tests can be used in real life to compare means. For example, a drug company may want to test a new cancer drug to find out if it improves life expectancy. In an experiment, there’s always a control group (a group who are given a placebo, or “sugar pill”) . The control group may show an average life expectancy of +5 years, while the group taking the new drug might have a life expectancy of +6 years. It would seem that the drug might work. But it could be due to a fluke. To test this, researchers would use a Student’s t-test to find out if the results are repeatable for an entire population.  \nExamples of typical questions that the independent samples t-test answers are as follows:  \n􀂙 Medicine – Has the quality of life improved for patients who took drug A as opposed to patien","cbCaiq8xlfYb0Udn","https://ap.wps.com/l/cbCaiq8xlfYb0Udn","pdf",968809,13,"English","# t-Test: Types and Application\n## Types of t-test\n## Student’s t-test vs Correlation & Regression\n## T-test vs ANOVA and contingency tables\n## T-test vs Fisher’s or chi-square tests\n## Assumptions and hypothesis (H0)\n## Examples and typical questions","[{\"question\":\"What is the purpose of a t-test in inferential statistics?\",\"answer\":\"A t-test assesses whether differences between group means are statistically significant. It helps determine whether the differences could plausibly be due to chance.\"},{\"question\":\"What are the three main types of t-test described?\",\"answer\":\"The document lists independent samples t-test (two unrelated groups), paired sample t-test (same group measured at different times), and one-sample t-test (one group mean compared to a known mean).\"},{\"question\":\"How does a t-test differ from ANOVA and from correlation/regression?\",\"answer\":\"The t-test compares exactly two groups, while ANOVA compares three or more groups. Correlation and regression assess how two variables vary together rather than comparing means between two groups.\"}]","t-Test - Types and Application | PDF",1790781642,33]