1. Before you conduct a test, first draw a dot plot to find out potential outliers. 2. To check normality, you can either use some graphical tool like q-q plot or conduct a formal test (search "check normality" in wikipedia). 3. Compared to the normality assumption, the independence assumption is more important because t distribution is close to normal distribution as long as sample size is large enough (when the data are i.i.d.). On the other hand, if each subject is randomly assigned to one of the two group, then using t distribution won't be a bad idea, even when the data are dependent and the sample size is small. 4. If the assumption of equal variance between the two groups is a concern, then a F-test can be used. ※ 引述《clara830 (...)》之銘言： : 我現在有2組data是要作為之後心理實驗要用的stimulus items : 我現在想要比較2組data在某些控制的variables上是否有顯著差異 : (檢定出來是希望不要有差異.... : 也就是說希望這2組data在某些控制變項上是matched的 : 因為才能避免2組data在之後作實驗的時候是受到其他variables的影響) : 我知道現在是應該要跑t-test去作檢定 : 可是再仔細查一下資料後 : 我有幾個問題不太確定怎麼作.. : 1. 好像跑t-test前 必須要先確定常態分配跟同質性才能做 : 不過我現在不太知道怎麼用SPSS來作常態分配檢定和同質性假設檢定?? : 2. 如果檢定出來不是常態分配的話...那要用什麼檢定去比較呢?? : 3. 如果T檢定出來2組data有顯著差異 那要怎麼作篩選的動作?? : 找出可能影響的outliers並剔除... 才能使我的2組data是matched的呢? : 謝謝解答!! --

※ 發信站: 批踢踢實業坊(ptt.cc) ◆ From: 76.124.84.13