# 4.4.2.3 - Example: One sample mean sodium content

## Sodium Content: CI for One Sample Mean Section

A nutritionist is conducting a study on the sodium content in fast food. They have collected a random sample of 50 different fast-food items from several popular fast-food chains, including burgers, fries, salads, and sandwiches. For each item, the sodium content (in milligrams) is recorded.

The Dietary Guidelines for Americans recommend that adults limit their sodium intake to less than 2300 mg per day. By examining the sodium content in these fast-food items, the nutritionist aims to provide more informed dietary information to their clients so that they can make healthier choices based on the sodium levels found in popular fast foods.

Data: FF_sodium.csv

Construct a 90% confidence interval using the percentile method to estimate the average sodium content (mg) in a single fast-food item.

To construct a 90% bootstrap confidence interval using the percentile method follow these steps:

1. Determine what type(s) of variable(s) you have and what parameters you want to estimate.
In this scenario, we are dealing with the average sodium content (mg) which is a single mean. In StatKey, choose Bootstrap Confidence Intervals > CI for Single Mean, Median, St. Dev.

2. Upload the sample data file into StatKey using the 'Upload File' button.

Select the quantitative variable, 'Sodium(mg)' > 'OK'

3. Generate at least 5,000 bootstrap samples.
4. Check the "Two-Tail" box at the upper left corner of the bootstrap dotplot. By default, this will give you a 95% confidence interval. Select the 0.95 box in the middle and change to 0.90 to display the 90% interval.

The 90% confidence interval for the average sodium content (mg) of a single fast food item is 1112.1 to 1391.1 mg.