Two Sample Hypothesis Testing for Mean Differences

Two Sample Hypothesis Testing for Mean Differences

Assessment

Interactive Video

Science

6th - 10th Grade

Hard

Created by

Liam Anderson

FREE Resource

10 questions

Show all answers

1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the main focus of the two-sample hypothesis test discussed in the video?

Comparing the means of two different populations

Comparing the proportions of two different populations

Comparing the medians of two different populations

Comparing the variances of two different populations

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

In the Target and Walmart plastic bag example, what is the null hypothesis?

The medians of the two populations are different

The variances of the two populations are equal

The means of the two populations are equal

The means of the two populations are different

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Why is a two-sided test used in the plastic bag example?

Because we know which bag holds more weight

Because we don't know which bag holds more weight

Because we are only interested in one direction of difference

Because the sample sizes are unequal

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What must be true for both samples in the random condition?

Both samples must be from the same population

Both samples must have the same variance

Both samples must be random

Both samples must have the same mean

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which condition cannot be checked using the Central Limit Theorem in this example?

Independence

Sample size

Randomness

Normality

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the purpose of creating box plots for the data?

To check for normality and outliers

To check for independence

To check for randomness

To check for equal variances

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the test statistic formula used in the two-sample hypothesis test?

Difference of sample means divided by standard error

Sum of sample variances divided by standard error

Sum of sample means divided by standard error

Difference of sample variances divided by standard error

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