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Assignment Solution: Statistical Analysis and Hypothesis Testing

June 11, 2023
Jennifer Flores
Jennifer Flores
🇺🇸 United States
Statistical Analysis
Jennifer Flores, Ph.D. in statistics from Monmouth University, with 5+ years' experience, specializes in aiding students with statistical assignments for academic success.
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Statistics is all about finding patterns and answering questions. Cultivate curiosity, and don’t hesitate to ask questions about what your data might be hiding or what might be influencing it.
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A recent report highlights that AI-based learning technologies will increasingly drive personalized education in 2024, allowing students to follow customized learning paths and access real-time performance data to enhance their academic success.
Key Topics
  • Problem Description: First Generation College Students
  • Steps:
    • 1. Hypotheses:
    • 2. Randomization Distribution:
    • 3. P-Value Calculation:
    • 4. Decision:
    • 5. Conclusion:
  • Question Set 1_C:
  • Problem Description: Credit Card Fraud Detection
  • Hypotheses:
  • Question Set 2_B: Type I Error:
  • Question Set 2_C: Type II Error:
  • Question Set 2_D: Severity Comparison:
  • Question Set 2_E: Alpha Level Choice:
    • Reflection:

Problem Description: First Generation College Students

Question Set 1_A: Research Question: Do more than 25% of all World Campus students identify as first-generation students?

Steps:

Randomization test for a proportion

Figure 0.1: Randomization test for a proportion

1. Hypotheses:

  • Null Hypothesis:0.25H0:P≤0.25
  • Alternative Hypothesis:0.25HA:P0.25

2. Randomization Distribution:

  • Use StatKey to construct a randomization distribution with at least 5000 resamples.

3. P-Value Calculation:

  • According to StatKey, the p-value is 0.935 in a right-tailed test.
Using StatKey to construct a randomization distribution

Figure 2: Using StatKey to construct a randomization distribution

4. Decision:

  • Since the p-value significance level, fail to reject the null hypothesis.

5. Conclusion:

  • We lack sufficient evidence to support the claim that more than 25% of all World Campus students identify as first-generation students.

Question Set 1_C:

  • Compare results from parts 1_A and 1_B.
  • Explain why the p-value changed with the increase in sample size.
  • The p-value changed due to the larger sample size providing more precise estimates of the population proportion, resulting in a narrower distribution around the hypothesized proportion.

Problem Description: Credit Card Fraud Detection

Question Set 2_A: Research Question: Does the new AI technology detect fraudulent charges more than 97% of the time?

Hypotheses:

  • Null Hypothesis: 0.97H0:P≤0.97
  • • Alternative Hypothesis: 0.97HA:P 0.97

Question Set 2_B: Type I Error:

  • Falsely rejects the null hypothesis, indicating the technology detects fraud more than 97% when it does not.
  • Consequence: Wasting resources and implementing an ineffective system.

Question Set 2_C: Type II Error:

  • Fails to reject the null hypothesis, suggesting the technology does not detect fraud more than 97% when it does.
  • Consequence: Missing the chance to enhance fraud detection and exposing customers to fraudulent activity.

Question Set 2_D: Severity Comparison:

  • In this scenario, a Type II error is more serious. Failing to invest in the new technology could lead to continued losses from fraudulent charges and potential harm to customers.

Question Set 2_E: Alpha Level Choice:

  • Given the consequences, a lower alpha level (e.g., 0.05) is recommended to reduce the likelihood of Type II error.

Reflection:

  • Confidence Level:High confidence in answers grounded in provided information and hypothesis testing principles.
  • Challenges:Determining the severity of errors in the specific context was the most challenging aspect.

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