Perception and Reality In a presidential election, 308 out of 611 voters surveyed said that they voted for the candidate who won (based on data from ICR Survey Research Group). Use a 0.05 significance level to test the claim that among all voters, the percentage who believe that they voted for the winning candidate is equal to 43%, which is the actual percentage of votes for the winning candidate. What does the result suggest about voter perceptions?
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- 1. Intro to Stats and Collecting Data1h 14m
- 2. Describing Data with Tables and Graphs1h 56m
- 3. Describing Data Numerically2h 5m
- 4. Probability2h 16m
- 5. Binomial Distribution & Discrete Random Variables3h 6m
- 6. Normal Distribution and Continuous Random Variables2h 11m
- 7. Sampling Distributions & Confidence Intervals: Mean3h 23m
- Sampling Distribution of the Sample Mean and Central Limit Theorem19m
- Distribution of Sample Mean - Excel23m
- Introduction to Confidence Intervals15m
- Confidence Intervals for Population Mean1h 18m
- Determining the Minimum Sample Size Required12m
- Finding Probabilities and T Critical Values - Excel28m
- Confidence Intervals for Population Means - Excel25m
- 8. Sampling Distributions & Confidence Intervals: Proportion2h 10m
- 9. Hypothesis Testing for One Sample5h 8m
- Steps in Hypothesis Testing1h 6m
- Performing Hypothesis Tests: Means1h 4m
- Hypothesis Testing: Means - Excel42m
- Performing Hypothesis Tests: Proportions37m
- Hypothesis Testing: Proportions - Excel27m
- Performing Hypothesis Tests: Variance12m
- Critical Values and Rejection Regions28m
- Link Between Confidence Intervals and Hypothesis Testing12m
- Type I & Type II Errors16m
- 10. Hypothesis Testing for Two Samples5h 37m
- Two Proportions1h 13m
- Two Proportions Hypothesis Test - Excel28m
- Two Means - Unknown, Unequal Variance1h 3m
- Two Means - Unknown Variances Hypothesis Test - Excel12m
- Two Means - Unknown, Equal Variance15m
- Two Means - Unknown, Equal Variances Hypothesis Test - Excel9m
- Two Means - Known Variance12m
- Two Means - Sigma Known Hypothesis Test - Excel21m
- Two Means - Matched Pairs (Dependent Samples)42m
- Matched Pairs Hypothesis Test - Excel12m
- Two Variances and F Distribution29m
- Two Variances - Graphing Calculator16m
- 11. Correlation1h 24m
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- Linear Regression & Least Squares Method26m
- Residuals12m
- Coefficient of Determination12m
- Regression Line Equation and Coefficient of Determination - Excel8m
- Finding Residuals and Creating Residual Plots - Excel11m
- Inferences for Slope31m
- Enabling Data Analysis Toolpak1m
- Regression Readout of the Data Analysis Toolpak - Excel21m
- Prediction Intervals13m
- Prediction Intervals - Excel19m
- Multiple Regression - Excel29m
- Quadratic Regression15m
- Quadratic Regression - Excel10m
- 13. Chi-Square Tests & Goodness of Fit2h 21m
- 14. ANOVA2h 28m
9. Hypothesis Testing for One Sample
Performing Hypothesis Tests: Proportions
Problem 6.R.11
Textbook Question
Self-InjuryAccording to the article “Self-injurious Behaviors in a College Population,” 17% of undergraduate or graduate students have had at least one incidence of self-injurious behavior. The researchers conducted a survey of 40 college students who reported a history of emotional abuse and found that 12 of them have had at least one incidence of self-injurious behavior. What do the results of this survey tell you about college students who report a history of emotional abuse?
Verified step by step guidance1
Step 1: Identify the population proportion given in the problem. The article states that 17% (or 0.17) of all undergraduate or graduate students have had at least one incidence of self-injurious behavior. This is the baseline proportion for the general college student population.
Step 2: Note the sample data from the survey. Among 40 college students who reported a history of emotional abuse, 12 have had at least one incidence of self-injurious behavior. Calculate the sample proportion \(\hat{p}\) as \(\hat{p} = \frac{12}{40}\).
Step 3: Compare the sample proportion \(\hat{p}\) to the population proportion \(p = 0.17\). This comparison will help determine if students with a history of emotional abuse have a higher incidence of self-injurious behavior than the general student population.
Step 4: To assess whether the difference is statistically significant, consider performing a hypothesis test for a population proportion. Set up the null hypothesis \(H_0: p = 0.17\) (the proportion is the same as the general population) and the alternative hypothesis \(H_a: p > 0.17\) (the proportion is higher for students with emotional abuse history).
Step 5: Calculate the test statistic using the formula for a one-proportion z-test: \(z = \frac{\hat{p} - p}{\sqrt{\frac{p(1-p)}{n}}}\), where \(n=40\) is the sample size. Then, use the z-value to find the p-value and decide whether to reject the null hypothesis, which will tell you if the incidence is significantly higher in this group.
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Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Proportion and Percentage
Proportion represents a part of a whole expressed as a fraction or decimal, while percentage is that proportion multiplied by 100. In this question, understanding how to calculate and interpret the proportion of students with self-injurious behavior (e.g., 12 out of 40) is essential to compare it with the general 17% rate.
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Difference in Proportions: Hypothesis Tests
Comparative Analysis
Comparative analysis involves comparing two or more groups to identify differences or similarities. Here, comparing the 30% (12/40) incidence in students with emotional abuse history to the overall 17% helps assess whether emotional abuse is associated with higher self-injurious behavior.
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Comparing Mean vs. Median
Sampling and Generalizability
Sampling refers to selecting a subset of individuals from a population to make inferences. Understanding the sample size (40 students) and its representativeness is crucial to evaluate how confidently we can generalize the findings about emotional abuse and self-injury to the broader college population.
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