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BESC 3010 - TEST 2 QUESTIONS AND ANSWERS | LATEST UPDATE | 2024/2025 | GRADED A+
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BESC 3010 - TEST 2 QUESTIONS AND ANSWERS | LATEST UPDATE | 2024/2025 | GRADED A+ What is the purpose of calculating a confidence interval in data analysis? A confidence interval provides a range that likely includes the population parameter, giving an estimate of the precision and reliabilit...

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  • November 4, 2024
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BESC 3010 - TEST 2 QUESTIONS AND
ANSWERS | LATEST UPDATE |
2024/2025 | GRADED A+
What is the purpose of calculating a confidence interval in data analysis?


✔✔A confidence interval provides a range that likely includes the population parameter, giving

an estimate of the precision and reliability of the sample statistic.




How is a point estimate different from an interval estimate?


✔✔A point estimate gives a single value as an estimate of a population parameter, while an

interval estimate provides a range of values, offering more information about the uncertainty

around the estimate.




What does a low p-value indicate in hypothesis testing?


✔✔A low p-value (typically less than 0.05) suggests that the observed result is unlikely to occur

under the null hypothesis, leading researchers to consider rejecting the null.




Why do researchers use the standard error in statistics?


✔✔The standard error indicates how much variability there is in a sample statistic, helping

researchers assess how well the sample represents the population.

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,What does the "95%" in a 95% confidence interval signify?


✔✔The "95%" means that if we were to take many samples, about 95% of the confidence

intervals calculated from those samples would contain the true population parameter.




Explain the term "degrees of freedom" and its role in statistical tests.


✔✔Degrees of freedom refer to the number of independent values in a calculation. In statistical

tests, it helps determine the critical values and affects the test’s accuracy.




What is a two-tailed test, and when would you use it?


✔✔A two-tailed test checks for effects in both directions, testing whether a parameter differs

significantly from a hypothesized value in either direction. It’s used when we don’t have a

specific direction in mind.




How does sample size affect a confidence interval?


✔✔A larger sample size results in a narrower confidence interval, meaning the estimate is more

precise. Smaller sample sizes produce wider intervals, reflecting more uncertainty.




What is statistical power, and why is it important?


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, ✔✔Statistical power is the probability of correctly rejecting a false null hypothesis. High power

reduces the risk of type II errors, making results more reliable.




What does a significant ANOVA result imply about group means?


✔✔A significant ANOVA result indicates that there are differences among group means, but it

doesn’t specify which groups differ. Further testing is needed for detailed comparisons.




What is a t-distribution, and how is it different from a normal distribution?


✔✔A t-distribution is similar to the normal distribution but has thicker tails, allowing for more

variability in smaller samples. It’s used when sample sizes are small and population variance is

unknown.




How do researchers interpret a 99% confidence level?


✔✔A 99% confidence level means that we are 99% confident the true population parameter lies

within the confidence interval, with only a 1% chance of it falling outside the interval.




What is an effect size, and why do researchers measure it?


✔✔Effect size measures the strength of a relationship or the magnitude of an effect, helping

researchers understand the practical significance of results beyond just statistical significance.


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