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Simulating sales under new market conditions

The company's financial analyst is predicting that next quarter, the worth of each sale will increase by 20% and the volatility, or standard deviation, of each sale's worth will increase by 30%. To see what Amir's sales might look like next quarter under these new market conditions, you'll simulate new sales amounts using the normal distribution and store these in the new_sales data frame, which has already been created for you.

In addition, dplyr and ggplot2 libraries are loaded.

This exercise is part of the course

Introduction to Statistics in R

View Course

Exercise instructions

  • Currently, Amir's average sale amount is $5000. Calculate what his new average amount will be if it increases by 20% and store this in new_mean.
  • Amir's current standard deviation is $2000. Calculate what his new standard deviation will be if it increases by 30% and store this in new_sd.
  • Add a new column called amount to the data frame new_sales, which contains 36 simulated amounts from a normal distribution with a mean of new_mean and a standard deviation of new_sd.
  • Plot the distribution of the new_sales amounts using a histogram with 10 bins.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Calculate new average amount
new_mean <- ___

# Calculate new standard deviation
new_sd <- ___

# Simulate 36 sales
new_sales <- new_sales %>% 
  mutate(amount = ___)

# Create histogram with 10 bins
___
Edit and Run Code