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 最新版 GraphPad Prism
5
相關軟體
GraphPad
Prism 5│
GraphPad InStat
│
GraphPad StatMate
GraphPad Prism 集生物統計、曲線擬合和科技繪圖於一體，其所具有的功能均非常實用和精煉，包括了一些特色的功能，如ROC曲線分析、Bland-Altman分析等；曲線擬合功能是GraphPad
Prism超越其他統計軟體的制勝法寶，GraphPad
Prism的線性\非線性擬合功能使用操作極其方便，不僅內置了常見的回歸模型，還專門內置了Aadvanced Rradioligand
Bbinding, Bacterial Growth, 劑量反映曲線，峰擬合等數十個生物統計模組，GraphPad
Prism的繪圖功能也很具特色，無需專門繪製統計圖形，只要輸入資料，圖表自動生成且隨資料改變及時更新，非常方便實用。
在能進行自定義方程曲線擬合的軟體中，GraphPad
Prism的操作最為簡便快捷，擬合前參數設置方便，擬合速度快，並支援批量擬合，這在同類軟體中非常少見，可以說GraphPad
Prism當之無愧為非線性擬合的高手。
Prism 在科學圖表的繪製方面可以視為Sigmaplot的替代軟體，但是卻又包含了簡單的試算表，可以直接輸入原始數據，軟體自動計算標準差和p
value，此外，也包含了其他幾項數值分析的能力。
GraphPad Prism還有一個兄弟產品GraphPad Instat，兩者配合使用則會使Prism的統計功能極大增強。
GraphPad
InStat
絕大多數的統計軟體都是由統計數家來設計的，其目的也是為了方便統計學家的使用。這些軟體都具有各自的個性和極強的功能。但是作為一個普通的科學研究人員，往往被他們那厚厚的說明書、晦澀的統計學術語和高昂的價格所困。與他們不同的是，他是由科學家自己為自己的使用而設計的。下面是你應該選擇的四個理由：
首先，可以一步一步地引導你地使用，這樣就大大方便了你對該軟體的掌握，毫不誇張地說，你甚至可以在幾秒的時間裏學會該軟體的使用。
第二，可以通過對你的資料提出若干問題的方法來幫助你挑選一個合適的測試方法，你甚至沒有必要知道你所需要的測試方法的名字。如果你還沒有把握的話，還可以參考軟體提供的幫助頁面，在裏面你將會得到相關統計原因的解釋。
第三，並不在意你是否是一個專業統計人員，他所最終提供的統計結果是用簡單的語言和很少的統計術語來展示。
第四，通常，在統計軟體中，很容易對一個正確的問題而得到一個錯誤的回答，為此，提供了一種獨特的分析檢測列表。你可以兩次核對那些沒有違反測試假設的資料，以及你所選擇的測試方法，當然該方法應該與你的實驗設計相匹配。
GraphPad StatMate
GraphPad StatMate
統計軟體,搭配Prism及InStat使用，提供八種統計計算。
GraphPad StatMate
takes the guesswork out of evaluating how many data points you'll
need for an experiment, and makes it easy for you to quickly
calculate the power of an experiment to detect various hypothetical
differences. Its wizard-based format leads you through the necessary
steps to determine the tradeoffs in terms of risks and costs. There
is no learning curve with StatMate because it is self-explanatory.
All the documentation you need is built right into the program.
Why sample-size
matters
Many experiments and clinical trials are run with too few subjects.
An underpowered study is wasted effort if even substantial treatment
effects go undetected. When planning a study, therefore, you need to
choose an appropriate sample size. Your decision depends upon a
number of factors including, how scattered you expect your data to
be, how willing you are to risk mistakenly finding a difference by
chance, and how sure you must be that your study will detect a
difference, if it exists.
StatMate shows you the tradeoffs
Some programs ask how much statistical power you desire and how
large an effect you are looking for and then tell you what sample
size you should use. The problem with this approach is that often
you can't really know this in advance. You want to design a study
with very high power to detect very small effects and with a very
strict definition of statistical significance. But doing so requires
lots of subjects, more than you can afford. StatMate 2 shows you the
possibilities and helps you to understand the tradeoffs in terms of
risk and cost so you can make sound sample-size and power decisions.
What about power?
You also need to know if your completed experiments have enough
power. If an analysis results in a "statistically significant"
conclusion, it's pretty easy to interpret. But interpreting "not
statistically significant" results is more difficult. Its never
possible to prove that a treatment had zero effect, because tiny
differences may go undetected. StatMate shows you the power of your
experiment to detect various hypothetical differences.
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