Hypothesis Testing

Hypothesis Testing

Assessment

Interactive Video

Health Sciences, Mathematics, Biology

University

Easy

Created by

Wayground Content

Used 2+ times

FREE Resource

This video tutorial covers the basics of hypothesis testing, including the definition of a hypothesis, the process of sampling, and making inferences about populations. It explains the concepts of null and alternative hypotheses, P values, significance levels, and confidence intervals. The tutorial uses examples to illustrate how these statistical tools are used to test hypotheses and make informed decisions based on sample data.

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10 questions

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1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the main topic discussed in the video?

Probability theory

Hypothesis testing

Regression analysis

Descriptive statistics

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is a hypothesis?

A random guess

An untestable assumption

A testable theory

A proven fact

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

In hypothesis testing, what is the null hypothesis?

A hypothesis that there is no effect or difference

A hypothesis that is always true

A hypothesis that is always false

A hypothesis that cannot be tested

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the purpose of taking a sample in hypothesis testing?

To avoid bias

To ensure randomness

To represent the entire population

To prove the null hypothesis

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What does a significance level indicate in hypothesis testing?

The probability of accepting the null hypothesis

The average value of the sample

The probability of rejecting the null hypothesis

The threshold for determining statistical significance

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the P value used for in hypothesis testing?

To calculate the mean of the sample

To measure the probability of the null hypothesis being true

To find the standard deviation

To determine the sample size

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

If the P value is less than the significance level, what decision is made?

Decrease the significance level

Accept the null hypothesis

Reject the null hypothesis

Increase the sample size

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