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BESC 3010 Chpt 9 Questions and Answers | Latest Version | 2024/2025 | Rated A+ CA$13.73   Add to cart
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BESC 3010 Chpt 9 Questions and Answers | Latest Version | 2024/2025 | Rated A+
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BESC 3010 Chpt 9 Questions and Answers | Latest Version | 2024/2025 | Rated A+ What is the central limit theorem, and why is it important in statistics? The central limit theorem states that the distribution of sample means will approximate a normal distribution as sample size increases, r...

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  • November 4, 2024
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BESC 3010 Chpt 9 Questions and
Answers | Latest Version | 2024/2025 |
Rated A+

What is the central limit theorem, and why is it important in statistics?


✔✔The central limit theorem states that the distribution of sample means will approximate a

normal distribution as sample size increases, regardless of the population’s distribution. This is

essential because it allows statisticians to make inferences about population parameters using

sample data.




Explain the concept of p-value and how it is interpreted in hypothesis testing.


✔✔A p-value indicates the probability of obtaining results as extreme as those observed,

assuming the null hypothesis is true. A low p-value (typically ≤ 0.05) suggests strong evidence

against the null hypothesis, leading to its rejection.




What is a type II error, and how does it differ from a type I error?


✔✔A type II error occurs when we fail to reject a false null hypothesis, missing an effect that

actually exists. This differs from a type I error, where a true null hypothesis is incorrectly

rejected.




1

, Describe the purpose and interpretation of a confidence interval.


✔✔A confidence interval provides a range of values within which the population parameter is

likely to fall, with a specified level of confidence (e.g., 95%). It gives an estimate of precision

around a sample statistic.




How does a one-sample t-test differ from an independent samples t-test?


✔✔A one-sample t-test compares the mean of a single sample to a known population mean,

while an independent samples t-test compares the means of two independent groups to see if they

differ significantly.




What is homoscedasticity, and why is it important in regression analysis?


✔✔Homoscedasticity refers to equal variance in the residuals across all levels of an independent

variable. It's crucial in regression because unequal variances (heteroscedasticity) can affect the

reliability of predictions and statistical conclusions.




In what scenario would you use a chi-square test, and what does it assess?


✔✔A chi-square test is used to assess relationships between categorical variables. It evaluates

whether observed frequencies differ significantly from expected frequencies, testing for

independence between variables.




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