#1
In hypothesis testing, what is the significance level?
The probability of rejecting the null hypothesis when it is actually true.
ExplanationProbability of rejecting null hypothesis when true.
#2
What is the purpose of using a hypothesis test in statistics?
To determine if there is enough evidence to reject a claim about a population parameter
ExplanationAssessing evidence to reject claims about population.
#3
Which of the following statements about Type I error is true?
It is also known as a false positive.
ExplanationType I error termed as false positive.
#4
In a hypothesis test, what does the alternative hypothesis typically represent?
The researcher's claim or hypothesis
ExplanationResearcher's alternative claim or hypothesis.
#5
What is the sampling distribution?
It is the distribution of a sample statistic based on multiple random samples from the same population.
ExplanationDistribution of sample statistic from multiple random samples.
#6
Which of the following is NOT an assumption of the Central Limit Theorem?
The population distribution is normal.
ExplanationNormality of population distribution not required.
#7
What is the standard error of the mean?
It is a measure of the variability of sample means around the true population mean.
ExplanationVariability of sample means around true population mean.
#8
What is a confidence interval?
It is a range of values that likely contains the population parameter with a certain level of confidence.
ExplanationRange of values likely containing population parameter.
#9
What is the formula for the standard error of the mean?
Standard Deviation / √(Sample Size)
ExplanationStandard deviation divided by square root of sample size.
#10
What does the Central Limit Theorem state?
It states that the sampling distribution of the sample mean approaches a normal distribution as the sample size increases, regardless of the shape of the population distribution.
ExplanationSample mean distribution approximates normal with large samples.
#11
Which of the following is a correct interpretation of a 95% confidence interval?
If the experiment were repeated many times, 95% of the resulting confidence intervals would contain the true population parameter.
ExplanationProportion of confidence intervals containing true parameter.
#12
Which of the following is an assumption of linear regression?
All of the above
ExplanationAll listed assumptions required for linear regression.