Math Problem Statement

In the spring of 2017, the Consumer Reports National Research Center conducted a survey of 1,007 adults to learn about their major healthcare concerns. The survey results showed that 577 of the respondents lack confidence they will be able to afford health insurance in the future. (a) What is the point estimate of the population proportion of adults who lack confidence they will be able to afford health insurance in the future. (Round your answer to two decimal places.) (b) At 90% confidence, what is the margin of error? (Round your answer to four decimal places.) (c) Develop a 90% confidence interval for the population proportion of adults who lack confidence they will be able to afford health insurance in the future. (Round your answer to four decimal places.) to (d) Develop a 95% confidence interval for this population proportion. (Round your answer to four decimal places.)

Solution

Let's work through each part of this problem step by step.

Part (a) - Point Estimate

The point estimate for the population proportion p^\hat{p} is calculated as:

p^=Number of respondents who lack confidenceTotal number of respondents=5771007\hat{p} = \frac{\text{Number of respondents who lack confidence}}{\text{Total number of respondents}} = \frac{577}{1007}

Calculating this:

p^=57710070.573\hat{p} = \frac{577}{1007} \approx 0.573

So, the point estimate of the population proportion is p^=0.57\hat{p} = 0.57 (rounded to two decimal places).


Part (b) - Margin of Error (90% Confidence Level)

The formula for the margin of error (ME) at a confidence level is:

ME=zα/2×p^(1p^)n\text{ME} = z_{\alpha/2} \times \sqrt{\frac{\hat{p}(1 - \hat{p})}{n}}

Where:

  • zα/2z_{\alpha/2} is the critical value for the given confidence level,
  • p^\hat{p} is the sample proportion (calculated in part (a)),
  • nn is the sample size.

For a 90% confidence level, zα/2z_{\alpha/2} (the z-value for 90% confidence) is approximately 1.645.

Using the values:

  • p^=0.573\hat{p} = 0.573,
  • n=1007n = 1007,
  • zα/2=1.645z_{\alpha/2} = 1.645,

The margin of error is:

ME=1.645×0.573(10.573)10071.645×0.01570.0258\text{ME} = 1.645 \times \sqrt{\frac{0.573(1 - 0.573)}{1007}} \approx 1.645 \times 0.0157 \approx 0.0258

So, the margin of error at 90% confidence is approximately ME=0.0258\text{ME} = 0.0258 (rounded to four decimal places).


Part (c) - 90% Confidence Interval

The confidence interval (CI) is calculated using:

CI=p^±ME\text{CI} = \hat{p} \pm \text{ME}

Using p^=0.573\hat{p} = 0.573 and ME=0.0258\text{ME} = 0.0258:

Lower bound=0.5730.0258=0.5472\text{Lower bound} = 0.573 - 0.0258 = 0.5472 Upper bound=0.573+0.0258=0.5988\text{Upper bound} = 0.573 + 0.0258 = 0.5988

Thus, the 90% confidence interval is:

(0.5472,0.5988)(0.5472, 0.5988)


Part (d) - 95% Confidence Interval

For a 95% confidence level, the critical value zα/2z_{\alpha/2} is approximately 1.96.

The margin of error for the 95% confidence level is:

ME=1.96×0.573(10.573)10071.96×0.01570.0308\text{ME} = 1.96 \times \sqrt{\frac{0.573(1 - 0.573)}{1007}} \approx 1.96 \times 0.0157 \approx 0.0308

Using this margin of error, the 95% confidence interval is:

Lower bound=0.5730.0308=0.5422\text{Lower bound} = 0.573 - 0.0308 = 0.5422 Upper bound=0.573+0.0308=0.6038\text{Upper bound} = 0.573 + 0.0308 = 0.6038

Thus, the 95% confidence interval is:

(0.5422,0.6038)(0.5422, 0.6038)


Summary of Results

(a) Point estimate: p^=0.57\hat{p} = 0.57
(b) Margin of error at 90% confidence: ME=0.0258\text{ME} = 0.0258
(c) 90% Confidence interval: (0.5472,0.5988)(0.5472, 0.5988)
(d) 95% Confidence interval: (0.5422,0.6038)(0.5422, 0.6038)

Would you like any more details or clarification on any step?

Here are some related questions you might find useful:

  1. How is the critical value zα/2z_{\alpha/2} determined for different confidence levels?
  2. How does increasing the sample size affect the margin of error?
  3. Why does the confidence interval widen when the confidence level increases?
  4. How would the results change if the sample proportion p^\hat{p} was closer to 0 or 1?
  5. What happens to the margin of error if the population proportion is unknown?

Tip: The margin of error decreases as the sample size increases, because a larger sample provides more accurate estimates of the population proportion.

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Math Problem Analysis

Mathematical Concepts

Statistics
Population Proportion
Confidence Intervals

Formulas

Point estimate of proportion: p̂ = x/n
Margin of error: ME = z * sqrt(p̂(1 - p̂) / n)
Confidence interval: CI = p̂ ± ME

Theorems

Central Limit Theorem

Suitable Grade Level

College/University Level