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