A magazine provided results from a poll of 500 adults who were asked to identify their favorite pie. Among the 500 respondents, 14% chose chocolate pie, and the margin of error was given as ±5 percentage points. What values do p, q, n, E, and p represent? If the confidence level is 90%, what is the value of a? The value of p is The value of q is The value of n is The value of E is The value of p is If the confidence level is 90%, what is the value of a? |(Type an integer or a decimal. Do not round.) α
A magazine provided results from a poll of 500 adults who were asked to identify their favorite pie. Among the 500 respondents, 14% chose chocolate pie, and the margin of error was given as ±5 percentage points. What values do p, q, n, E, and p represent? If the confidence level is 90%, what is the value of a? The value of p is The value of q is The value of n is The value of E is The value of p is If the confidence level is 90%, what is the value of a? |(Type an integer or a decimal. Do not round.) α
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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![### Understanding Polling Results: Favorite Pie Flavor Study
A magazine conducted a poll among 500 adults to determine their favorite pie. The results provided the following insights:
- **14% of respondents chose chocolate pie.**
- **The margin of error for this poll is ± 5 percentage points.**
The following symbols are used in statistical analysis of the poll results:
- \( \hat{p} \): Proportion of the sample choosing chocolate pie
- \( \hat{q} \): Proportion of the sample choosing something other than chocolate pie
- n: Total number of respondents surveyed
- E: Margin of error
- p: The true proportion of the entire population's preference for chocolate pie (unknown, estimated by \( \hat{p} \))
Given these values, we need to determine what each of these symbols represents, if the confidence level is 90%. Additionally, we need to find the value of \( \alpha \).
#### Values
- **\( \hat{p} \)**: \(\hat{p} = 0.14\) (14% from the sample)
- **\( \hat{q} \)**: \(\hat{q} = 1 - \hat{p} = 0.86\)
- **n**: \( n = 500 \) (total respondents)
- **E**: \( E = 0.05 \) (5% margin of error)
- **p**: (unknown, estimated by \(\hat{p}\))
#### Confidence Interval
- **Confidence Level**: 90%
- **Value of \( \alpha \)**: The significance level (\( \alpha \)) is \( 1 - \text{confidence level} \). Therefore, for a 90% confidence level,
\[ \alpha = 1 - 0.90 = 0.10 \]
### To Summarize
- **The value of \( \hat{p} \) is:** 0.14
- **The value of \( \hat{q} \) is:** 0.86
- **The value of \( n \) is:** 500
- **The value of \( E \) is:** 0.05
- **The value of \( p \) is:** estimated by \( \hat{p} \), so approximately 0.14
- **The value of \( \alpha](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F86445a01-0a3f-49cc-9d22-b352e3028fb5%2Fee9184d6-940c-4702-9b1c-a5cc921033c3%2Fr1idtgh_processed.png&w=3840&q=75)
Transcribed Image Text:### Understanding Polling Results: Favorite Pie Flavor Study
A magazine conducted a poll among 500 adults to determine their favorite pie. The results provided the following insights:
- **14% of respondents chose chocolate pie.**
- **The margin of error for this poll is ± 5 percentage points.**
The following symbols are used in statistical analysis of the poll results:
- \( \hat{p} \): Proportion of the sample choosing chocolate pie
- \( \hat{q} \): Proportion of the sample choosing something other than chocolate pie
- n: Total number of respondents surveyed
- E: Margin of error
- p: The true proportion of the entire population's preference for chocolate pie (unknown, estimated by \( \hat{p} \))
Given these values, we need to determine what each of these symbols represents, if the confidence level is 90%. Additionally, we need to find the value of \( \alpha \).
#### Values
- **\( \hat{p} \)**: \(\hat{p} = 0.14\) (14% from the sample)
- **\( \hat{q} \)**: \(\hat{q} = 1 - \hat{p} = 0.86\)
- **n**: \( n = 500 \) (total respondents)
- **E**: \( E = 0.05 \) (5% margin of error)
- **p**: (unknown, estimated by \(\hat{p}\))
#### Confidence Interval
- **Confidence Level**: 90%
- **Value of \( \alpha \)**: The significance level (\( \alpha \)) is \( 1 - \text{confidence level} \). Therefore, for a 90% confidence level,
\[ \alpha = 1 - 0.90 = 0.10 \]
### To Summarize
- **The value of \( \hat{p} \) is:** 0.14
- **The value of \( \hat{q} \) is:** 0.86
- **The value of \( n \) is:** 500
- **The value of \( E \) is:** 0.05
- **The value of \( p \) is:** estimated by \( \hat{p} \), so approximately 0.14
- **The value of \( \alpha
![### Understanding Statistical Notation and Definitions
When dealing with statistical notation, it's important to recognize what each symbol represents. Below, we will detail the meanings of common symbols used in statistics.
1. **Symbols and Their Meanings**:
- **\(\hat{p}\)**: The value of \(\hat{p}\) refers to the sample proportion. This is an estimate of the true proportion of the population based on the sampled data.
- **\(\hat{q}\)**: The value of \(\hat{q}\) is found from evaluating \(1 - \hat{p}\). It represents the proportion of the sample that does not meet the criteria defined by \(\hat{p}\).
- **\(n\)**: The value of \(n\) is the sample size. This is the total number of observations or data points in the sample.
- **\(E\)**: The value of \(E\) is the margin of error. This quantifies the uncertainty or potential error in the sample estimate and is often used in confidence interval calculations.
- **\(p\)**: The value of \(p\) represents the population proportion. This is the true proportion of the population that meets the criteria defined by the research question.
2. **Confidence Level and Alpha (\(\alpha\))**:
- **\(\alpha\)** represents the level of significance in hypothesis testing. It is typically expressed as a decimal (e.g., 0.05) and corresponds to the probability of making a Type I error, which is rejecting a true null hypothesis.
3. **User Input**:
- Users are typically asked to input the value of \(\alpha\) in hypothesis testing scenarios. For example, if you want a 95% confidence level, then \(\alpha\) would be 0.05.
### Interactive Example
Consider the following multiple-choice question to reinforce your understanding:
#### Question: What does the symbol \(\hat{p}\) represent?
- [ ] the sample size.
- [ ] the population proportion.
- [ ] the margin of error.
- [X] the sample proportion.
- [ ] found from evaluating \(1 - \hat{p}\).
By providing these explanations and interactive questions, students can practice and enhance their understanding of statistical symbols and concepts.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F86445a01-0a3f-49cc-9d22-b352e3028fb5%2Fee9184d6-940c-4702-9b1c-a5cc921033c3%2Fpw9r0o_processed.png&w=3840&q=75)
Transcribed Image Text:### Understanding Statistical Notation and Definitions
When dealing with statistical notation, it's important to recognize what each symbol represents. Below, we will detail the meanings of common symbols used in statistics.
1. **Symbols and Their Meanings**:
- **\(\hat{p}\)**: The value of \(\hat{p}\) refers to the sample proportion. This is an estimate of the true proportion of the population based on the sampled data.
- **\(\hat{q}\)**: The value of \(\hat{q}\) is found from evaluating \(1 - \hat{p}\). It represents the proportion of the sample that does not meet the criteria defined by \(\hat{p}\).
- **\(n\)**: The value of \(n\) is the sample size. This is the total number of observations or data points in the sample.
- **\(E\)**: The value of \(E\) is the margin of error. This quantifies the uncertainty or potential error in the sample estimate and is often used in confidence interval calculations.
- **\(p\)**: The value of \(p\) represents the population proportion. This is the true proportion of the population that meets the criteria defined by the research question.
2. **Confidence Level and Alpha (\(\alpha\))**:
- **\(\alpha\)** represents the level of significance in hypothesis testing. It is typically expressed as a decimal (e.g., 0.05) and corresponds to the probability of making a Type I error, which is rejecting a true null hypothesis.
3. **User Input**:
- Users are typically asked to input the value of \(\alpha\) in hypothesis testing scenarios. For example, if you want a 95% confidence level, then \(\alpha\) would be 0.05.
### Interactive Example
Consider the following multiple-choice question to reinforce your understanding:
#### Question: What does the symbol \(\hat{p}\) represent?
- [ ] the sample size.
- [ ] the population proportion.
- [ ] the margin of error.
- [X] the sample proportion.
- [ ] found from evaluating \(1 - \hat{p}\).
By providing these explanations and interactive questions, students can practice and enhance their understanding of statistical symbols and concepts.
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