Understanding Sampling and Bias in Statistics

Understanding Sampling and Bias in Statistics

Assessment

Interactive Video

Mathematics, Science, Social Studies

8th - 12th Grade

Hard

CCSS
HSS.IC.B.3, 7.SP.A.1, HSS.IC.A.1

Standards-aligned

Created by

Emma Peterson

FREE Resource

Standards-aligned

CCSS.HSS.IC.B.3
,
CCSS.7.SP.A.1
,
CCSS.HSS.IC.A.1
This video tutorial by Lucy introduces the concept of statistics, emphasizing its role in data collection, organization, and analysis. It explains the importance of understanding statistics and its limitations. The video focuses on sampling and bias, discussing various sampling methods such as random, systematic, convenience, cluster, and stratified sampling. It highlights the challenges of ensuring a representative sample and the inevitability of sampling errors. The tutorial concludes by stressing the need for careful study design to minimize bias.

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10 questions

Show all answers

1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the primary focus of statistics as a branch of mathematics?

Solving algebraic equations

Understanding geometric shapes

Dealing with data collection and analysis

Studying the history of mathematics

Tags

CCSS.7.SP.A.1

CCSS.HSS.IC.A.1

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Why is sampling used in data collection?

To include every individual in the population

To avoid data bias

To ensure data accuracy

To save time and resources

Tags

CCSS.HSS.IC.B.3

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which sampling method gives each member of the population an equal chance of being selected?

Random sampling

Systematic sampling

Cluster sampling

Convenience sampling

Tags

CCSS.7.SP.A.1

CCSS.HSS.IC.A.1

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is a major drawback of convenience sampling?

It requires complex calculations

It introduces significant bias

It is expensive

It is time-consuming

Tags

CCSS.HSS.IC.B.3

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How does cluster sampling work?

By choosing individuals based on convenience

By randomly selecting individuals from the entire population

By dividing the population into groups and sampling entire groups

By selecting every nth individual

Tags

CCSS.HSS.IC.B.3

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the purpose of stratified sampling?

To reduce the cost of sampling

To increase the sample size

To simplify the sampling process

To ensure each subgroup is represented

Tags

CCSS.HSS.IC.B.3

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Why can sampling errors never be completely eliminated?

Because samples are always biased

Because statistics is an imperfect science

Because samples are not the entire population

Because data collection is always flawed

Tags

CCSS.HSS.IC.B.3

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