In hypothesis testing, what is the significance level?
The probability of committing a Type II error.
The probability of rejecting the null hypothesis when it is actually true.
The probability of failing to reject the null hypothesis when it is actually false.
The probability of rejecting the null hypothesis when it is actually false.
#2
What is the purpose of using a hypothesis test in statistics?
To estimate population parameters
To make predictions about future events
To determine if there is enough evidence to reject a claim about a population parameter
To calculate the standard error of the mean
#3
Which of the following statements about Type I error is true?
It is also known as a false positive.
It is also known as a false negative.
It is the probability of failing to reject the null hypothesis when it is actually false.
It is the probability of rejecting the null hypothesis when it is actually true.
#4
In a hypothesis test, what does the alternative hypothesis typically represent?
The researcher's claim or hypothesis
The status quo or null hypothesis
The population parameter being tested
The probability of making a Type I error
#5
What is the sampling distribution?
It is the distribution of a sample statistic based on multiple random samples from the same population.
It is the distribution of a population based on multiple random samples.
It is the distribution of a population based on a single random sample.
It is the distribution of a sample statistic based on a single random sample.
#6
Which of the following is NOT an assumption of the Central Limit Theorem?
The sample size is sufficiently large.
The population distribution is normal.
The samples are drawn independently and randomly from the population.
The population has a finite variance.
#7
What is the standard error of the mean?
It is a measure of how spread out the values in a sample are around the sample mean.
It is a measure of how spread out the values in a population are around the population mean.
It is a measure of the variability of sample means around the population mean.
It is a measure of the variability of sample means around the 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.
It is a range of values that represents the variability of sample means around the population mean.
It is a range of values that represents the spread of data within a population.
It is a range of values that represents the spread of data within a sample.
#9
What is the formula for the standard error of the mean?
Standard Deviation / √(Sample Size)
Standard Deviation * √(Sample Size)
Sample Size / √(Standard Deviation)
Sample Size * √(Standard Deviation)
#10
What does the Central Limit Theorem state?
It states that as sample size increases, the standard error decreases.
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.
It states that the mean of the sampling distribution is always equal to the population mean.
It states that the standard deviation of the sampling distribution is always equal to the population standard deviation.
#11
Which of the following is a correct interpretation of a 95% confidence interval?
There is a 95% chance that the true population parameter falls within the interval.
95% of the population falls within the interval.
The sample mean falls within the interval with 95% probability.
If the experiment were repeated many times, 95% of the resulting confidence intervals would contain the true population parameter.
#12
Which of the following is an assumption of linear regression?