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Confidence Interval and t-score Hypothesis using Data Analysis assignment Solution

March 12, 2022
Dr. Evelyn Carter
Dr. Evelyn
🇺🇸 United States
Data Analysis
Dr. Evelyn Carter earned her Ph.D. from the University of Michigan, bringing over 12 years of experience in data analysis. Her expertise in statistical methods and data interpretation makes her a sought-after professional in the field.
Key Topics
  • Confidence Intervals and Hypothesis Testing
Tip of the day
Always verify your data for accuracy and completeness before analysis. Clean and organize your dataset to avoid errors, and use statistical software like R or Python to automate and streamline your calculations.
News
In 2024, the statistical software SAS introduced new machine learning modules, allowing statistics students abroad to conduct more sophisticated analyses and predictive modeling with ease. This update aims to enhance academic research and assignment quality.

Confidence Intervals and Hypothesis Testing

  1. Construct the following two confidence intervals for µ using only the given information. Answers should be in form x − t √s < µ < x + t √s or something Equivalent, where the t−score corresponds to a two-tail probability of α :
    1. n = 16, x = 23, s = 12, α = 0.05
    2. n = 25, x = 23, s = 12, α = 0.25
  2. Suppose a tutoring company advertises that its clientele average 80% in their math courses. Feeling skeptical, you question a sample of 9 students who used the tutoring service, finding that their average was only 68%, with a standard deviation of 11%:
    1. State the null and alternative hypotheses, H0 and H1:
    2. Calculate the appropriate t−statistic at the 5% significance level:
    3. Estimate the p−value, and describe what it means in the context of this problem:
    4. State your conclusions (ie: is the tutoring company necessarily not being truthful? Why would we observe an average of 68% when the stated average was so much greater? Share your thoughts):

Solution:

    1. Here n= 16, thus df= 15. Hence the critical value at α = 0.05 is t=2.131. Using these values, the confidence interval is 23±2.131*12/4 i.e. (16.607 <μ< 29.393)
    2. Here n= 25, thus df = 24. Hence the critical value at α = 0.25 is t=1.15. Using these values, the confidence interval is 23±1.15*12/5 i.e. (20.24<μ<25.76)
    1. H_0:μ=80 vs H_1:μ≠80, where μ is the average course in match course.
    2. The test statistic is T=(68-80)/(11/√9)= -3.273. The test statistic follows a t-distribution with 8 degrees of freedom.
    3. The p-value is given P(|T|>3.273)=2*P(T<-3.273) = 0.0113. It means that the probability of getting a sample that gives a similar or more extreme result than the obtained one is 0.0113.
    4. As the p-value is less than the significance level of 0.05, we reject the null hypothesis. Thus, we conclude that there is sufficient evidence to support the claim that the average match score is different.