This data set includes the percentage of protein intake from different types of food in countries around the world. We will do a bootstrap experiment on the variable protein
| var.name |
|---|
| Country |
| AlcoholicBeverages |
| AnimalProducts |
| Animalfats |
| CerealsExcludingBeer |
| Eggs |
| FishSeafood |
| FruitsExcludingWine |
| Meat |
| MilkExcludingButter |
| Offals |
| Oilcrops |
| Pulses |
| Spices |
| StarchyRoots |
| Stimulants |
| Treenuts |
| VegetalProducts |
| VegetableOils |
| Vegetables |
| Miscellaneous |
| Obesity |
| Confirmed |
| Deaths |
| Recovered |
| Active |
| Population |
Here, we are performing a bootstrapping process by taking a sample of the population in the variable “eggs”. Afterwards we will take means of the sample 1000 times and plot all the means in a historgram. We are resampling with replacement to maintain the data structure of the population as we reshuffle the values, while extrapolating to the population.
Without bootstrapping, we are 95% confident that the mean of the amount of eggs consumed is between 1.04 and 1.28
| 2.5 % | 97.5 % | |
|---|---|---|
| (Intercept) | 1.042265 | 1.28067 |
While calculating our confidence interval from our bootstrapped sample, we calculated that we are 95% confident that the mean of the amount of eggs consumed is between 1.04 and 1.278. Since both of the confidence intervals of the original population and the sampling distribution are almost similar, we can assume that the original population is normally distributed.
| x | |
|---|---|
| 2.5% | 1.049033 |
| 97.5% | 1.278352 |
The following is a bootstrap sampling distribution with n=170
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