A) The measure of confidence in the null hypothesis B) The population parameter being tested C) The probability of obtaining results at least as extreme as the observed results, given that the null hypothesis is true D) The significance level for accepting the null hypothesis
A) Mann-Whitney U test B) Wilcoxon signed-rank test C) Kruskal-Wallis test D) t-test
A) To test for differences in means B) To summarize categorical data C) To identify outliers in a dataset D) To examine the relationship between variables
A) The central tendency of a dataset B) The variability within groups C) The spread of the data D) The strength and direction of a linear relationship between two variables
A) To compare two independent groups B) To estimate the range within which the population parameter is likely to fall C) To determine the probability of an event occurring D) To predict future data points
A) Systematic sampling B) Convenience sampling C) Simple random sampling D) Cluster sampling
A) Logistic regression. B) Ridge 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 level of confidence in the alternative hypothesis D) The measure of correlation between two variables
A) Time series analysis. B) Factor analysis. C) Cluster analysis. D) Regression analysis.
A) Chi-square test. B) T-test. C) ANOVA. D) Regression analysis.
A) Correlation indicates a relationship between variables, while causation implies one variable causes a change in the other B) Correlation measures the strength of a relationship, while causation measures the direction C) Correlation refers to linear relationships, while causation refers to non-linear relationships D) Correlation is used for categorical data, while causation is used for continuous data
A) To calculate the range of a dataset B) To state that the sampling distribution of the sample mean approaches a normal distribution as the sample size increases 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) A statement that predicts an outcome in an experiment C) The hypothesis that is tested using a one-tailed test D) The hypothesis that the researcher believes to be true
A) Outlier detection. B) Normalization. C) Feature engineering. D) Imputation.
A) T-test B) ANOVA C) Chi-square test D) Regression analysis |