You wish to test the following claim (Ha) at a significance level of a = 0.01. H.:µ = 73.7 Ha:µ + 73.7 You believe the population is normally distributed, but you do not know the standard deviation. Your sample has: size: n = 54 mean: M = 65.8 standard deviation: SD = 20.1. What is the test statistic for this sample? (Round the answer accurate to 3 decimal places.) test statistic: t = What is the P-value for this sample? (Round the answer accurate to 3 decimal places.) P-value = The P-value is... less than (or equal to) a greater than a This leads to a decision to... O reject the null accept the null O fail to reject the null So, the final conclusion is that... O The data do not support the claim of the alternative hypothesis that the population mean is not equal to 73.7. O The sample data support the claim of the alternative hypothesis that the population mean is not equal to 73.7.
Inverse Normal Distribution
The method used for finding the corresponding z-critical value in a normal distribution using the known probability is said to be an inverse normal distribution. The inverse normal distribution is a continuous probability distribution with a family of two parameters.
Mean, Median, Mode
It is a descriptive summary of a data set. It can be defined by using some of the measures. The central tendencies do not provide information regarding individual data from the dataset. However, they give a summary of the data set. The central tendency or measure of central tendency is a central or typical value for a probability distribution.
Z-Scores
A z-score is a unit of measurement used in statistics to describe the position of a raw score in terms of its distance from the mean, measured with reference to standard deviation from the mean. Z-scores are useful in statistics because they allow comparison between two scores that belong to different normal distributions.
![**Testing Population Mean with Unknown Standard Deviation**
This page explains how to test a population mean when the standard deviation is unknown using the t-test. We will use the given data to determine the test statistic and the P-value, then make a decision regarding the null hypothesis.
### Hypotheses and Significance Level
You wish to test the following hypothesis at a significance level of α = 0.01:
\[ H_0: \mu = 73.7 \]
\[ H_a: \mu \neq 73.7 \]
### Sample Information
The population is assumed to be normally distributed, but the standard deviation is unknown. Your sample has the following characteristics:
- **Sample size** (\(n\)): 54
- **Sample mean** (\(\bar{M}\)): 65.8
- **Sample standard deviation** (\(SD\)): 20.1
### Test Statistic Calculation
What is the test statistic for this sample? (Round the answer to 3 decimal places.)
\[ \text{test statistic: } t = \_\_\_\_\_ \]
### P-value Calculation
What is the P-value for this sample? (Round the answer to 3 decimal places.)
\[ \text{P-value: } \_\_\_\_\_ \]
The P-value is:
- ○ less than (or equal to) α
- ○ greater than α
### Decision
Based on the comparison between the P-value and α, decide:
- ○ reject the null
- ○ accept the null
- ○ fail to reject the null
### Conclusion
So, the final conclusion is:
- ○ The data do **not** support the claim of the alternative hypothesis that the population mean is not equal to 73.7.
- ○ The sample data **support** the claim of the alternative hypothesis that the population mean is not equal to 73.7.
By completing the steps above, you will be able to determine if there is enough evidence to reject the null hypothesis in favor of the alternative hypothesis, based on your sample data.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F1a3586c7-75e0-478e-8b93-fa570f1e3b86%2Fd862e3ee-9dab-4ebb-8ac8-c20e6c0152c9%2Ftgusu6p_processed.png&w=3840&q=75)

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