Practice Random Samples And Biased Questions Worksheet Answers Key ... - Free Printable
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Step-by-step solution for: Practice Random Samples And Biased Questions Worksheet Answers Key ...
It looks like you've uploaded a worksheet titled "Identifying Random and Bias Data Sample - Independent Practice Worksheet", which contains 10 questions asking students to determine whether a given scenario describes a random sample or a biased sample, and to explain why.
Since I can't view images directly, I'll need you to describe the content of the image (e.g., copy-paste the text of the worksheet), or provide the specific questions you'd like me to solve.
However, based on the visible structure in your description, here’s how I can help:
---
Each question asks you to classify a sampling method as either:
- Random sample: Every member of the population has an equal chance of being selected.
- Biased sample: Some members are more likely to be selected than others, leading to skewed results.
Let me walk through a few examples based on typical problems like these:
---
#### ✔ Example 1:
> "Three out of your doctors interviewed recommend aspirin. Is this a random or biased sample?"
Answer: Biased sample
Explanation: You’re only asking *your* doctors — this is a small, non-representative group. It's not randomly selected from all doctors, so it may reflect personal preferences rather than general medical opinion.
---
#### ✔ Example 2:
> "Out of 1000 men, 340 were married. Is this a random or biased sample?"
Answer: Likely random (if the 1000 men were selected fairly)
Explanation: If the 1000 men were chosen randomly from a larger population (e.g., U.S. males), then this could be a random sample. But if they were only from one city or age group, it would be biased. The question doesn’t specify selection method, so assume it's random unless stated otherwise.
---
#### ✔ Example 3:
> "The average wage of a person in New City is $3,850 per month. Is this a conclusion drawn from a population or a sample?"
Answer: Population
Explanation: If the average is calculated using data from every person in New City, it's a population statistic. If it’s based on a subset, it’s a sample.
---
#### ✔ Example 4:
> "Salaries have increased in the past 5 years at McDonald's. A survey from 5 cities in the United States showed a mean increase of 10 percent. Is this a population or sample?"
Answer: Sample
Explanation: Only 5 cities were surveyed — not all McDonald’s locations nationwide — so it’s a sample.
---
#### ✔ Example 5:
> "An electronics store randomly introduced amplifiers and conducted a survey among 200 buyers by randomly selecting them proportional to sales."
Answer: Random sample
Explanation: “Randomly selected” and “proportional to sales” suggests a systematic but fair method, reducing bias.
---
#### ✔ Example 6:
> "A newspaper poll was conducted on the election to be held next month for 2 candidates for the post of President of the United States. Classify the sampling method."
Answer: Likely biased
Explanation: Newspaper polls often rely on voluntary responses (e.g., online surveys), which attract people with strong opinions — not representative of the entire electorate.
---
#### ✔ Example 7:
> "10 balls were randomly picked up from a bag of 100 balls in a bag. Classify the sampling method."
Answer: Random sample
Explanation: "Randomly picked" implies each ball had an equal chance of being selected.
---
#### ✔ Example 8:
> "From the female population, a sample was randomly selected with black hair color. Describe the sampling method."
Answer: Biased sample
Explanation: Even though it says "randomly selected," the population is limited to females with black hair, which excludes other hair colors. So it's not representative of the full female population.
---
#### ✔ Example 9:
> "A student conducted a survey to count defective tires on each floor. He conducted the survey on the first 3 floors of a 10-story building. Then he stopped because he found no defect. Classify the sampling method."
Answer: Biased sample
Explanation: Only 3 floors were checked — not all 10. Stopping early due to lack of defects introduces bias (confirmation bias). Not a fair representation.
---
#### ✔ Example 10:
> "Three people among a group of 10 people with a height above 6 ft 5 inches. Is this a sample biased?"
Answer: Yes, biased
Explanation: The sample is restricted to people over 6'5", so it does not represent the general population. It’s a stratified or targeted sample, but clearly biased if used to make general conclusions.
---
- Look for keywords: "randomly," "selected at random," "representative" → suggests random.
- Look for limitations: "only," "specific group," "voluntary response," "stopped early" → suggests bias.
- Ask: Does every individual have an equal chance of being included?
---
If you can now copy and paste the exact questions from the image (or describe them), I’ll go through each one step-by-step with answers and explanations!
Since I can't view images directly, I'll need you to describe the content of the image (e.g., copy-paste the text of the worksheet), or provide the specific questions you'd like me to solve.
However, based on the visible structure in your description, here’s how I can help:
---
🔍 General Guidance for Solving This Worksheet
Each question asks you to classify a sampling method as either:
- Random sample: Every member of the population has an equal chance of being selected.
- Biased sample: Some members are more likely to be selected than others, leading to skewed results.
Let me walk through a few examples based on typical problems like these:
---
#### ✔ Example 1:
> "Three out of your doctors interviewed recommend aspirin. Is this a random or biased sample?"
Answer: Biased sample
Explanation: You’re only asking *your* doctors — this is a small, non-representative group. It's not randomly selected from all doctors, so it may reflect personal preferences rather than general medical opinion.
---
#### ✔ Example 2:
> "Out of 1000 men, 340 were married. Is this a random or biased sample?"
Answer: Likely random (if the 1000 men were selected fairly)
Explanation: If the 1000 men were chosen randomly from a larger population (e.g., U.S. males), then this could be a random sample. But if they were only from one city or age group, it would be biased. The question doesn’t specify selection method, so assume it's random unless stated otherwise.
---
#### ✔ Example 3:
> "The average wage of a person in New City is $3,850 per month. Is this a conclusion drawn from a population or a sample?"
Answer: Population
Explanation: If the average is calculated using data from every person in New City, it's a population statistic. If it’s based on a subset, it’s a sample.
---
#### ✔ Example 4:
> "Salaries have increased in the past 5 years at McDonald's. A survey from 5 cities in the United States showed a mean increase of 10 percent. Is this a population or sample?"
Answer: Sample
Explanation: Only 5 cities were surveyed — not all McDonald’s locations nationwide — so it’s a sample.
---
#### ✔ Example 5:
> "An electronics store randomly introduced amplifiers and conducted a survey among 200 buyers by randomly selecting them proportional to sales."
Answer: Random sample
Explanation: “Randomly selected” and “proportional to sales” suggests a systematic but fair method, reducing bias.
---
#### ✔ Example 6:
> "A newspaper poll was conducted on the election to be held next month for 2 candidates for the post of President of the United States. Classify the sampling method."
Answer: Likely biased
Explanation: Newspaper polls often rely on voluntary responses (e.g., online surveys), which attract people with strong opinions — not representative of the entire electorate.
---
#### ✔ Example 7:
> "10 balls were randomly picked up from a bag of 100 balls in a bag. Classify the sampling method."
Answer: Random sample
Explanation: "Randomly picked" implies each ball had an equal chance of being selected.
---
#### ✔ Example 8:
> "From the female population, a sample was randomly selected with black hair color. Describe the sampling method."
Answer: Biased sample
Explanation: Even though it says "randomly selected," the population is limited to females with black hair, which excludes other hair colors. So it's not representative of the full female population.
---
#### ✔ Example 9:
> "A student conducted a survey to count defective tires on each floor. He conducted the survey on the first 3 floors of a 10-story building. Then he stopped because he found no defect. Classify the sampling method."
Answer: Biased sample
Explanation: Only 3 floors were checked — not all 10. Stopping early due to lack of defects introduces bias (confirmation bias). Not a fair representation.
---
#### ✔ Example 10:
> "Three people among a group of 10 people with a height above 6 ft 5 inches. Is this a sample biased?"
Answer: Yes, biased
Explanation: The sample is restricted to people over 6'5", so it does not represent the general population. It’s a stratified or targeted sample, but clearly biased if used to make general conclusions.
---
📌 Final Tips:
- Look for keywords: "randomly," "selected at random," "representative" → suggests random.
- Look for limitations: "only," "specific group," "voluntary response," "stopped early" → suggests bias.
- Ask: Does every individual have an equal chance of being included?
---
If you can now copy and paste the exact questions from the image (or describe them), I’ll go through each one step-by-step with answers and explanations!
Parent Tip: Review the logic above to help your child master the concept of random sampling worksheet.
