StackOverflow2013

Note that there are some explanatory texts on larger screens.

plurals

PO
primarykey
Id
9379021
data
AcceptedAnswerId
0
AnswerCount
0
ClosedDate
CommentCount
0
CommunityOwnedDate
CreationDate
2012-02-21T14:12:25.123
FavoriteCount
0
LastActivityDate
2012-02-21T14:54:37.630
LastEditDate
2012-02-21T14:54:37.630
LastEditorUserId
1073244
OwnerUserId
1073244
ParentId
9378482
PostTypeId
2
Score
1
ViewCount
0
LastEditorDisplayName
text
Body
First let's make some example data. For each sample, we have a unique ID, its experimental group, and some variables for which we want to calculate the mean and SD. <pre><code>## Make a data frame called "Data" with five columns Data <- as.data.frame(cbind(1:100, sample(1:2), rnorm(100), rnorm(100), rnorm(100), rnorm(100))) names(Data) <- c("ID", "Group", "V1", "V2", "V3", "V4") ## Now we will take a peak at the top of our data frame > head(Data) ID Group V1 V2 V3 V4 1 1 2 0.3681539 -0.5008400 1.2060665 -0.7352376 2 2 1 -0.1043180 2.2038190 -1.4367898 2.1961246 3 3 2 -0.2720279 -0.5923554 -1.4628190 -1.8776453 4 4 1 -2.3299662 -0.1216227 0.4200776 1.5504020 5 5 2 -0.3670578 -1.5903221 -0.6287083 -1.0543262 6 6 1 0.4840047 -0.3181554 -1.4596980 -0.4261827 </code></pre> Now we can run a for loop through the variables, pull their means and SDs and p values, and dump them all in an object called "Results". <pre><code>## Define object which will receive our results Results <- NULL Results <- as.data.frame(Results) ## Open for loop for (i in 3:6) { ## Run the t.test() and save it in a temporary object temp <- t.test(Data[which(Data$Group == 1), i], Data[which(Data$Group == 2), i]) ## Put the name of our variable in our results object Results[i-2,1] <- names(Data)[i] ## Group 1 mean and SD Results[i-2,2] <- temp$estimate[1] Results[i-2,3] <- sd(Data[which(Data$Group == 1), i]) ## Group 2 mean and SD Results[i-2,4] <- temp$estimate[2] Results[i-2,5] <- sd(Data[which(Data$Group == 2), i]) ## P value for difference Results[i-2,6] <- temp$p.value rm(temp) } </code></pre> Now we can make our results pretty and print them. <pre><code>## Add column names names(Results) <- c("Variable", "Group.1.Mean", "Group.1.SD", "Group.2.Mean", "Group.2.SD", "P.Value") ## View our results > Results Variable Group.1.Mean Group.1.SD Group.2.Mean Group.2.SD P.Value 1 V1 0.21544390 0.9404104 -0.01426226 1.0570324 0.2537820 2 V2 0.26287585 1.0048291 0.22992285 0.9709686 0.8679038 3 V3 -0.06112963 0.9855287 0.17423440 1.0198694 0.2434507 4 V4 0.33848678 0.9360016 0.07905932 0.9106595 0.1632705 </code></pre>
Tags
Title
singulars
PostAcceptedAnswerId
1. This table or related slice is empty.
PostParentId
1. POR: how can I create a table with mean and sd according to experimental group alongside p-values?
 singulars
 PostTypePostTypeId
 PTQuestion
PostTypePostTypeId
1. PTAnswer
UserLastEditorUserId
1. USAlexander
UserOwnerUserId
1. USAlexander
plurals
PostLinksPostIdRelatedPostId
1. This table or related slice is empty.
PostLinksRelatedPostIdPostId
1. This table or related slice is empty.
PostsAcceptedAnswerId
1. This table or related slice is empty.
PostsParentIdCreationDate
1. This table or related slice is empty.
VotesPostIdCreationDate
1. VO
 singulars
 PostPostId
 PO
 UserUserId
 This table or related slice is empty.
 VoteTypeVoteTypeId
 VTUpMod
CommentsPostId
1. This table or related slice is empty.

Querying!

Guidance

A row detail

Detail views are divided into sections. All the information in the data section comes from columns in the selected row. The other sections display data from other, related rows.

Related data can be related in a to-one or a to-many fashion. Captions of data related in a to-many fashion link to a list view showing a filtered view of the table.

Try moving around until you find a non-empty to-many entry and click on the label to get to one. You can move back to the root by clicking on the database name in the header.