Prism 7 新版特色

Prism 7 lets you do more kinds of statistical analyses, make more kinds of graphs, and organize your data with more flexibility. But Prism is still Prism! You can switch to Prism 7 with almost no learning curve, and can use the trial  license of Prism 7 without removing earlier versions.

Here are some of the highlights.

Heat maps
Three-way ANOVA
FDR approach to  multiple comparisons
More accurate (asymmetrical, likelihood) confidence intervals from nonlinear regression
Label subcolumns
Color code sheet names, and selected cells in tables
Semitransparent colors so you can see overlap
Enter dates (or elapsed  times) as X values

Prism 7 for Windows runs under either the 32- or 64-bit versions of Windows Vista, 7, 8 or 10.  Prism will run in a screen as small as 800 x 540. While it runs fine on 64 bit versions of Windows, it is a 32 bit program.

Prism 7 for Macintosh requires OS X 10.9 (Mavericks) or later. If you use OS X 10.7 or 10.8, Prism will launch and seems to run ok but we haven't tested Prism thoroughly on these versions of OS X and can't provide much support.

Prism windows requires 60 megabytes of space on the hard drive. Prism Mac requires 80 megabytes space.

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

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.