calculate survival probability and expected payout I have data taken from here. Let us look at one specific column qx for female up to the age of 10. qx represents the mortality rate between age x and (x+1), that is the probability that a person aged x exact will die before reaching age (x+1). The data and problem is expressed as R code as follows:
library(dplyr)

    qxs <- tribble(
        ~age,  ~qx,
        0, 0.003536,
        1, 0.000213,
        2, 0.000127,
        3, 0.000098,
        4, 0.000068,
        5, 0.000086,
        6, 0.000082,
        7, 0.000062,
        8, 0.000064,
        9, 0.000053,
        10, 0.000064
    ) %>%
    mutate(
        survival_probability = 1 - qx
        , expected_payout = 100 * survival_probability
    )
    
    qxs 


First question:
Can I simply calculate the survival probability as I did 1 - qx?
Second question, not sure if you can help, let us say some pension firm agrees to pay 100 dollars per month, can the expected payout simply be calculated as 100 * survival probability?
 A: From your data source

$q_x$ is the mortality rate between age $x$ and $(x +1)$, that is the probability that a person aged $x$ exact will die before reaching age $(x +1)$.

Thus the answer to Question 1 is NO, assuming that you are calculating "survival probability" in the standard way as the fraction of an initial cohort (at age = 0 here) still alive at a certain time. This requires an iterative combination of: calculating the fraction of the original cohort surviving at age $x$, multiplying that by $q_x$ to get the fraction of the original cohort the will die between ages $x$ and $(x +1)$, then calculating the fraction of the original cohort still alive at age $(x+1)$. To get you started:
At age = 1 , the fraction still alive is $1-q_0=1-0.003536= 0.996464$. Of that surviving fraction, a fraction $q_1 = 0.000213$ will die before age = 2, for a fraction of the original cohort (at age = 0) dying between age = 1 and age = 2 of: $0.996464 * 0.000213 = 0.0002122$. So the fraction of the original cohort still alive at age 2 is 1 minus the fraction of the original cohort dying during each year of age: $1-0.003536-0.0002122=0.996252$. And so on ...
To check your calculations, note that the column lx in the original data table has those surviving as a function of time, expressed as the above fractions multiplied by 100,000.
With respect to question 2, the terminology "expected payout" typically means the average payout per person in the population. You thus need to calculate the mean lifetime from the entire survival distribution to get that expected payout.
These concepts can be very confusing. This Wikipedia page is one place to start.
