Population vs Sample Statistics Example 3

Follow the full solution, then compare it with the other examples linked below.

Example 3

easy
A factory produces 10,000 light bulbs per day. Quality control tests 100 randomly chosen bulbs. Identify the population, sample, and explain why sampling is used.

Solution

  1. 1
    Step 1: Population: all 10,000 light bulbs produced that day. Sample: the 100 tested bulbs.
  2. 2
    Step 2: Sampling is used because testing all 10,000 bulbs would be too time-consuming and costly, and destructive testing would destroy the product.

Answer

Population: 10,000 bulbs. Sample: 100 bulbs. Sampling saves time, cost, and avoids destroying all products.
Sampling is essential when testing is destructive, populations are large, or resources are limited. Random selection helps avoid bias.

About Population vs Sample

In statistics, the population is the entire group of individuals or items you want to study, while the sample is the smaller subset you actually collect data from. We use sample statistics to estimate unknown population parameters.

Learn more about Population vs Sample →

More Population vs Sample Examples

Example 1 easy

A researcher wants to know the average height of all 16-year-olds in the UK. She measures 500 random

Example 2 medium

Distinguish between a parameter and a statistic. Give an example of each.

Example 4 easy

A website wants to know the average time spent on the site by all visitors. It studies 1,200 randoml

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