**Introduction**

Sometimes, you will need to create a single variable from two or more existing variables in R. In this blog, we’ll show you some options for doing so.

**Create Data**

Let’s assume that you administered a survey with four questions that measure a construct such as confidence. Now you need to add the numerical answers to these questions together in order to generate a single confidence score for each participant. First, we’ll create mock data, then we’ll show you how to add them.

q1.a <- runif(30, min=1, max=7)

q1 <- round(q1.a)

q2.a <- runif(30, min=1, max=7)

q2 <- round(q2.a)

q3.a <- runif(30, min=1, max=7)

q3 <- round(q2.a)

q4.a <- runif(30, min=1, max=7)

q4 <- round(q2.a)

**Add Data Values**

You can create a new value, total, that sums the values of answers to your four survey questions as follows:

total <- q1 + q2 + q3 + q4

**Average Data Values**

You can create a new value, average, that averages the values of answers to your four survey questions as follows:

average <- (q1 + q2 + q3 + q4) / 4

**Multiply Data Values**

You can create a new value, mult, that multiplies the values of answers to your four survey questions as follows:

mult <- (q1*q2*q3*q4)

**Create a Data Frame**

Now you can bring you data together using:

mydata <- data.frame(q1, q2, q3, q4, total, average, mult)

print(mydata)

Here’s what you get (note that, because of the random number generation processes, your results will vary, but the format will look the same):

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