Can the Mann-Whitney U test be used for paired samples?
- No
- Only if the data is normally distributed
- Only if the variances are equal
- Yes
No, the Mann-Whitney U test is not used for paired samples. It is designed for two independent samples. For paired samples, a different test, such as the Wilcoxon signed-rank test, would be more appropriate.
When is it more appropriate to use the Mann-Whitney U test than a t-test?
- When data is normally distributed
- When data is not normally distributed
- When sample sizes are equal
- When the variances of the two groups are equal
The Mann-Whitney U test is more appropriate to use than a t-test when the data is not normally distributed. This test is a non-parametric alternative to the independent t-test and does not assume normality.
In what type of data distribution is the mean usually greater than the median?
- Negatively skewed distribution
- Normal distribution
- Positively skewed distribution
- Uniform distribution
In a positively skewed distribution, the mean is usually greater than the median. A positive skew means the right tail of the distribution is longer or fatter. The mean, being affected by the values of the data points, gets dragged in the direction of the tail, and hence is typically greater than the median in a positively skewed distribution.
A distribution that is symmetric and bell-shaped is known as a _______ distribution.
- Bimodal
- Normal
- Skewed
- Uniform
A normal distribution, also known as Gaussian distribution, is symmetric and bell-shaped. It is characterized by its mean and standard deviation. The mean, mode and median are all equal and are located at the center of the distribution.
Data that can be divided into categories but has no order or priority is known as ________ data.
- Continuous
- Discrete
- Nominal
- Ordinal
Nominal data is data that can be divided into categories but has no order or priority. It is a type of categorical data that simply allows us to classify or categorize. Examples include types of cuisine (Italian, Chinese, Mexican, etc.), hair color, or city of residence.
When two events are mutually exclusive, what is the probability that both will occur?
- 0
- 0.5
- 1
- The sum of the probabilities of the two events
When two events are mutually exclusive, it means they cannot occur at the same time. Therefore, the probability that both will occur is 0.
The ___________ correlation is a non-parametric measure of correlation based on data rank.
- Kendall's
- Pearson's
- Point-biserial
- Spearman's
Spearman's correlation is a non-parametric measure of rank correlation. It assesses how well the relationship between two variables can be described using a monotonic function. This makes it suitable for both continuous and discrete ordinal variables.
In which situations would you use the Kruskal-Wallis Test instead of ANOVA?
- When data is normally distributed
- When sample sizes are large
- When the assumptions of ANOVA are violated
- When there is only one independent variable
You would use the Kruskal-Wallis Test when the assumptions of ANOVA (like normality or equal variances) are violated.
What is the role of interaction effects in a two-way ANOVA?
- They calculate the variance within each group
- They correct for multiple comparisons
- They show how the levels of one independent variable affect the effect of the other variable on the dependent variable
- They show the distribution of residuals
In a two-way ANOVA, interaction effects show how the levels of one independent variable affect the effect of the other variable on the dependent variable. Essentially, it shows whether the effect of one independent variable depends on the level of the other independent variable.
What are the characteristics of a Poisson distribution?
- All outcomes are equally likely
- It describes the distribution of non-overlapping events in an interval
- It describes the distribution of rare events
- It describes the events that are not independent
The Poisson distribution is used for describing the distribution of rare events in a large population or time/space interval. It also describes events that are independent, meaning the occurrence of one event doesn't affect the occurrence of another.