A) The probability of obtaining results at least as extreme as the observed results, given that the null hypothesis is true B) The significance level for accepting the null hypothesis C) The population parameter being tested D) The measure of confidence in the null hypothesis
A) Kruskal-Wallis test B) Wilcoxon signed-rank test C) t-test D) Mann-Whitney U test
A) To examine the relationship between variables B) To test for differences in means C) To summarize categorical data D) To identify outliers in a dataset
A) The variability within groups B) The spread of the data C) The central tendency of a dataset D) The strength and direction of a linear relationship between two variables
A) To determine the probability of an event occurring B) To compare two independent groups C) To estimate the range within which the population parameter is likely to fall D) To predict future data points
A) Cluster sampling B) Convenience sampling C) Systematic sampling D) Simple random sampling
A) Linear regression. B) Polynomial regression. C) Logistic regression. D) Ridge regression.
A) The probability of rejecting the null hypothesis when it is actually true B) The level of confidence in the alternative hypothesis C) The measure of correlation between two variables D) The margin of error in the sample mean
A) Factor analysis. B) Cluster analysis. C) Regression analysis. D) Time series analysis.
A) Chi-square test. B) Regression analysis. C) T-test. D) ANOVA.
A) Correlation indicates a relationship between variables, while causation implies one variable causes a change in the other B) Correlation refers to linear relationships, while causation refers to non-linear relationships C) Correlation is used for categorical data, while causation is used for continuous data D) Correlation measures the strength of a relationship, while causation measures the direction
A) To state that the sampling distribution of the sample mean approaches a normal distribution as the sample size increases B) To calculate the range of a dataset C) To compare two different samples D) To determine the variability within groups
A) A statement that there is no significant difference between specified populations B) The hypothesis that the researcher believes to be true C) The hypothesis that is tested using a one-tailed test D) A statement that predicts an outcome in an experiment
A) Outlier detection. B) Feature engineering. C) Normalization. D) Imputation.
A) Regression analysis B) T-test C) Chi-square test D) ANOVA |