9 Steps of Hypothesis Testing: Quiz and Flashcards

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Questions and Answers

What is the purpose of the null hypothesis in statistical hypothesis testing?

To provide a hypothesis of no difference. (correct)

To calculate the critical value for test statistics.

To determine if there is a significant difference between two means.

To highlight the rejection region for hypothesis testing.

Which type of error occurs when true null hypothesis is incorrectly rejected?

Acceptance region error

Type I error (correct)

Critical value error

Type II error

What is the alternative hypothesis in statistical hypothesis testing?

It agrees with the null hypothesis.

It disagrees with the null hypothesis. (correct)

It states that there is no significant difference.

It provides the critical value for test statistics.

What does the critical value in hypothesis testing determine?

The point that separates acceptance and rejection regions. Signup and view all the answers

What is the purpose of the test statistics in hypothesis testing?

To provide a mathematical expression of the sample value. Signup and view all the answers

What is the purpose of the assumption step in hypothesis testing?

To check for normality, equality, and independence of samples Signup and view all the answers

In hypothesis testing, what defines whether the null hypothesis will be accepted or rejected?

The calculated value must be less than the critical value. Signup and view all the answers

When is the null hypothesis rejected in hypothesis testing?

When the calculated value is less than the tabulated value Signup and view all the answers

What does the decision rule specify in hypothesis testing?

Whether to accept or reject the null hypothesis Signup and view all the answers

Which test is commonly used to compare means of two different groups in hypothesis testing?

$ ext{t-test}$ Signup and view all the answers

What type of data is commonly used with the student (t) test in hypothesis testing?

Numerical data Signup and view all the answers

In hypothesis testing, what does the distribution of test statistics help determine?

Whether to accept or reject the null hypothesis Signup and view all the answers

What is the purpose of hypothesis testing?

To help in decision-making regarding a population Signup and view all the answers

In the context of hypothesis testing, what is a statement focused on?

Population parameters Signup and view all the answers

What are the two types of hypothesis testing mentioned?

Research type and statistical type Signup and view all the answers

What percentage of observations typically lies within plus or minus 1.96 standard deviation units in a normal distribution?

95% Signup and view all the answers

If the sample size (n) is less than or equal to 30, what value is used instead of 1.96 for calculating the confidence interval in a normal distribution?

$t \sqrt{n}$ Signup and view all the answers

Which measure of a normal distribution is zero by definition?

Skewness Signup and view all the answers

Study Notes

Hypothesis testing involves a 9-step procedure including determining the nature of data, assumptions about normality and independence, setting up hypotheses (null or alternative), using test statistics to make decisions, drawing the distribution curve, setting a decision rule for accepting or rejecting the null hypothesis, calculating test statistics, making a statistical decision based on the calculated value, and finally reaching a conclusion.
There are two types of errors in hypothesis testing: Type I error (α) involves incorrectly rejecting a true null hypothesis, while Type II error (β) is accepting a false null hypothesis.
The normal distribution, also known as the Gaussian Distribution, is characterized by a mean, median, and mode that are all equal, with skewness and kurtosis being zero. It is symmetrical and the total area under the curve is 1.
In the normal distribution, about 68% of observations fall within plus or minus one standard deviation (SD), 95% within plus or minus 1.96 SD units, 99% within plus or minus 2.58 SD units, and 99.7% within plus or minus 3 SD units.
Confidence intervals for the mean provide a range in which the true population mean is likely to lie with a certain level of assurance, expressed as X ± 1.96√n for a 95% confidence interval and X ± 2.58√n for a 99% confidence interval when n > 30, and X ± t√n when n ≤ 30.

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Description

Learn about the 9 steps involved in hypothesis testing, from analyzing the nature of data to making conclusions about the null and alternative hypotheses. Understand the significance of rejecting or failing to reject the null hypothesis based on the evidence from the test.