In a dataset, if the _______ is zero, then all the numbers in the set are the same.
- Mean
- Range
- Standard Deviation
- Variance
If the variance of a dataset is zero, then all the numbers in the set are the same. Variance measures how far a set of numbers is spread out from their average value. If all the numbers in the dataset are identical, there would be no dispersion and the variance would be zero.
What does a Spearman’s Rank Correlation coefficient of 0 indicate?
- Data cannot be ranked
- No correlation
- Perfect negative correlation
- Perfect positive correlation
A Spearman’s Rank Correlation coefficient of 0 indicates that there is no correlation, meaning changes in one variable do not correspond to changes in the other variable.
How can undercoverage bias occur during sampling?
- By including every individual in the population in the sample
- By not including certain segments of the population in the sample
- By selecting too large of a sample
- By selecting too small of a sample
Undercoverage bias can occur during sampling if certain segments of the population are not included in the sample or are represented less than they should be. This can result in a sample that is not representative of the population, leading to biased estimates.
The Z-score and T-score are both types of _______ scores, which measure the number of standard deviations an observation is from the mean.
- mean
- median
- standard
- variance
The Z-score and T-score are both types of standard scores. They measure the number of standard deviations an observation or statistic is from the mean.
A ________ ANOVA is used when we have two independent variables and want to understand if there is an interaction between them.
- Factorial
- One-way
- Three-way
- Two-way
A two-way ANOVA is used when there are two independent variables. This type of ANOVA assesses the main effects of each independent variable and the interaction effect between the variables.
Can Pearson's Correlation Coefficient determine causality?
- No, never
- Yes, always
- Yes, but additional information is required
- Yes, but only if the coefficient is 1 or -1
No, Pearson's Correlation Coefficient cannot determine causality. It can only measure the degree of linear correlation between two variables. While two variables may be correlated, it does not mean that changes in one variable cause changes in the other. Correlation does not imply causation.
What does the range of a dataset represent?
- The average value
- The middle value
- The most frequent value
- The spread of the data
The range of a dataset is a measure of dispersion, representing the total spread of values in the dataset. It is calculated by subtracting the smallest value from the largest value in the dataset.
The _________ states that the sampling distribution of the sample means approaches a normal distribution as the sample size gets larger—no matter what the shape of the population distribution.
- Central Limit Theorem
- Law of Large Numbers
- Probability Rule
- Sampling Distribution
The Central Limit Theorem states that the sampling distribution of the sample means approaches a normal distribution as the sample size gets larger—no matter what the shape of the population distribution. This allows us to apply normal probability calculations to situations that might not initially seem appropriate for them.
________ is a measure of asymmetry of a probability distribution.
- Mean
- Median
- Mode
- Skewness
Skewness is a measure of the asymmetry of a probability distribution about its mean. It quantifies the direction and extent of skew (departure from horizontal symmetry) in the data.
What is the difference between frequentist and Bayesian statistics?
- Bayesians use Bayes' theorem, frequentists do not
- Frequentists believe in probability and Bayesians do not
- Frequentists interpret probability as a long-run frequency, Bayesians as a degree of belief
- There is no difference
Frequentist statistics interprets probability as the long-run frequency of events, whereas Bayesian statistics interprets probability as a degree of belief or as subjective probability. The Bayesian approach uses Bayes' theorem to update probabilities based on new data.