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