Question 1.You work for a company that manufactures lifts and you need to estimate the expected weight it needsto carry.You know that the weights of passengers using the lift would vary both individually and as groups. Your jobis to design a lift that would be able to carry 99% of all possible groups entering the lift at the same time.For thepurpose of this exercise, you do not need to worry about the groups whose cumulative weight is in the heaviest 1%.Your company manufactures two versions of the lift: one small model with just enough space for five people and onelarge model with space for ten people. Answer the questions below:1.1Search online for a dataset with people's weights. Transform weights to kilograms where appropriate. Describeit and report where you found the dataset (e.g., link to the website). Create diagrams showing the distributionof the weights in the dataset, using density curves, boxplots, violin chart etc. Add appropriate descriptivestatistics (mean, median, standard deviation, range etc). Assume that this dataset is a representative sample ofthe passengers that would use your lift.1.2Sample your dataset, generating groups of five (for the small lift) and groups of ten (for the larger lift). Providediagrams for the distribution of the mean weights for each of the two lifts, as well as the appropriatedescriptive statistics. How do the distributions of the two lifts compare? How do they compare to thedistribution of people's weights?1.3Find the average weight of a person in the heaviest group that your design would support. You will need onemeasure for each type of lift. Can you explain the difference between the two measures? Calculations need to be done i R programming language