This post will take you from a variable that shows numeric values, such as the number of days to trial a product:

To a state where you can visualize the probability of an event at a certain time interval, such as the proportion of people who have yet to purchase at each point in time. Survival curves are also known as Kaplan-Meier curves:

## Requirements

- A
*numeric*variable.

## Method

- Go to
**Create > R Output.** - In the
**object inspector**, go to**Properties > R CODE**and paste in the following code and click**Calculate.**library(survival)

surv.days = Surv(Days)

surv.fit = survfit(surv.days~1)

#Set Plot title

plot(surv.fit, main = "Kaplan-Meier estimate with 95% confidence bounds (86% of data)",

#Set x-axis title

xlab = "Days since trial started",

#Set x-axis maximum and minimum limits

xlim = c(0, 180),

# Set y-axis title

ylab = "Survival function")

grid(20, 10, lwd = 2)

In the code above, "surv.days = Surv(*Days*)", *Days *is the name of your numeric variable being used to create the density plot. This must be updated with the variable's

**Name**in your data set.

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