P-0.9 = 0.005 0.0079 p-0.9 = -2.576, from the excel function, = NORM.INV 0.005 0.0079 P=0. 88 le proportion is 0.88
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
What am I doing wrong on 5.24?
i keep getting .92 for the answer for p-hat.
please write the answer out the long way this time. Thanks.
![**5.22 Getting Enough Sleep**
400 students were randomly sampled from a large university, and 289 students said they did not get enough sleep. Conduct a hypothesis test to check whether this represents a statistically significant difference from 70% and use a significance level of 0.01.
---
**5.23 Working Backwards, Part I**
You are given the following hypotheses:
- \(H_0: p = 0.3\)
- \(H_A: p \neq 0.3\)
We know the sample size is 90. For what sample proportion would the p-value be equal to 0.067? Assume that all conditions necessary for inference are satisfied.
---
**5.24 Working Backwards, Part II**
You are given the following hypotheses:
- \(H_0: p = 0.9\)
- \(H_A: p \neq 0.9\)
We know that the sample size is 90. For what sample proportion would the p-value be equal to 0.017? Assume that all conditions necessary for inference are satisfied.
---
**5.25 Testing for Fibromyalgia**
A patient named Diana was diagnosed with fibromyalgia, a long-term syndrome of body pain, and was prescribed anti-depressants. Being the skeptical type, Diana was suspicious of being on anti-depressants and initially believed that anti-depressants would help only a couple of her symptoms. However, after a few months on the medication, she decides that the anti-depressants are working, because she feels like her symptoms are in fact getting better.
(a) Write the hypotheses in words for Diana's skeptical position when she started taking the anti-depressants.
(b) What is a Type 1 Error in this context?](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fb45547dd-c628-45a5-8939-a65a109b41c7%2F64b28df6-827d-41be-bbb8-5484e3d13024%2Fwflnnza.jpeg&w=3840&q=75)
![**5.24 Working Backwards, Part II**
**Step 1:**
- Given test is a two-tail test.
- Population proportion is \( p = 0.9 \).
- Sample size is \( n = 1429 \).
**Hypotheses:**
- Null hypothesis (\( H_0 \)): \( p = 0.9 \)
- Alternative hypothesis (\( H_a \)): \( p \neq 0.9 \)
**Step 2:**
- Significance level \( p = 0.05 \)?
**Calculate Sample Proportion (\( \hat{p} \)):**
1. **P-value:**
- \( p = 0.01 \) for a two-tailed test.
- \( Z = \pm 2.58 \) for 99% confidence interval.
2. **Standard Error (SE):**
\[
SE = \sqrt{\frac{p(1-p)}{n}} = \sqrt{\frac{0.9(1-0.9)}{1429}} = 0.0079
\]
3. **Calculate \( \hat{p} \):**
- Use formula for Z-score:
\[
Z = \frac{\hat{p} - p}{SE}
\]
\[
2.58 = \frac{\hat{p} - 0.9}{0.0079}
\]
\[
\hat{p} - 0.9 = 2.58 \times 0.0079
\]
\[
\hat{p} = 0.9 + 0.0204 = 0.92
\]
**Conclusion:**
- The sample proportion (\( \hat{p} \)) is calculated to be \( 0.92 \).](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fb45547dd-c628-45a5-8939-a65a109b41c7%2F64b28df6-827d-41be-bbb8-5484e3d13024%2F02zg1tx.jpeg&w=3840&q=75)
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