Five steps for hypothesis testing StepsConsiderations Step 1: Making assumptions and meeting test requirements. Considerations/Cautions: The sample has been selected according to the rules of EPSEM. The variable being tested is interval-ratio in level of measurement. The sampling distribution of all possible sample means is normal in shape. This will allow us to use the standardized normal distribution to find areas un-der the sampling distribution. We can be sure that this assumption is satisfied by using large samples. Step 2: Stating the null hypothesis. Considerations/Cautions: The null hypothesis is always a statement of "no difference." It has a varying form depending on the test being conducted. The null hypothesis is usually wanting to be rejected so researchers create a research hypothesis to contradict the null hypothesis. Step 3: Selecting the sampling distribution and establishing the critical region. Considerations/Cautions: Sampling distributions is a problem against which a particular sample outcome is measured. The critical region is also known as the region of rejection. If the Z-score falls outside the Z-critical it would cause us to reject the null hypothesis. Size of the critical region is known as Alpha. Step 4: Computing the test statistic. Considerations/Cautions: The test statistic is also known as the Z-Score. The value of the Z-Score is also known as the Z(obtained). Calculating the test statistic helps evaluate the probability of the sample outcome. Step 5: Making a decision and interpreting the results of the test. Considerations/Cautions: If the test statistic falls in the critical region, we reject the null hypothesis. If the test statistic does not fall in the critical region, we fail to reject the null hypothesis. After determining whether to or not to reject the null hypothesis you have to describe the meaning. Choose a empirical example and explain how one would go through the 5 steps.

Hypothesis testing is an inferential procedure.

Answered: Steps Considerations Step 1: Making…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

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Five steps for hypothesis testing

Steps	Considerations
Step 1: Making assumptions and meeting test requirements.	Considerations/Cautions: The sample has been selected according to the rules of EPSEM. The variable being tested is interval-ratio in level of measurement. The sampling distribution of all possible sample means is normal in shape. This will allow us to use the standardized normal distribution to find areas un-der the sampling distribution. We can be sure that this assumption is satisfied by using large samples.
Step 2: Stating the null hypothesis.	Considerations/Cautions: The null hypothesis is always a statement of "no difference." It has a varying form depending on the test being conducted. The null hypothesis is usually wanting to be rejected so researchers create a research hypothesis to contradict the null hypothesis.
Step 3: Selecting the sampling distribution and establishing the critical region.	Considerations/Cautions: Sampling distributions is a problem against which a particular sample outcome is measured. The critical region is also known as the region of rejection. If the Z-score falls outside the Z-critical it would cause us to reject the null hypothesis. Size of the critical region is known as Alpha.
Step 4: Computing the test statistic.	Considerations/Cautions: The test statistic is also known as the Z-Score. The value of the Z-Score is also known as the Z(obtained). Calculating the test statistic helps evaluate the probability of the sample outcome.
Step 5: Making a decision and interpreting the results of the test.	Considerations/Cautions: If the test statistic falls in the critical region, we reject the null hypothesis. If the test statistic does not fall in the critical region, we fail to reject the null hypothesis. After determining whether to or not to reject the null hypothesis you have to describe the meaning.

Choose a empirical example and explain how one would go through the 5 steps.

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

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