The range of values around the point estimate that captures the true population parameter at some predetermined confidence level is called a confidence interval. Confidence intervals are used in statistics to indicate the reliability of an estimate.

To prevent overfitting, we can apply a technique called regularization in polynomial regression. Regularization involves adding a penalty term to the loss function during the process of training a model. This penalty term discourages the coefficients of the model from reaching large values, leading to a simpler model that's less likely to overfit.

The primary purpose of an ANOVA (Analysis of Variance) test is to compare the means of three or more groups to see if they are different. It is a way to find out if survey or experiment results are significant. In other words, they help to figure out if you need to reject the null hypothesis or accept the alternate hypothesis.

The Addition Rule in probability is used to calculate the probability that at least one of two (or more) events will occur. It states that the probability of the occurrence of at least one of two mutually exclusive events is the sum of their individual probabilities.

The Law of Large Numbers states that as a sample size grows, the sample mean will be closer to the population mean. This means that the larger the sample size, the more the sample mean approximates the population mean.

It is more appropriate to use a two-way ANOVA instead of a one-way ANOVA when there are two independent variables. Two-way ANOVA is used to observe the interaction effect between the two independent variables on the dependent variable.

Quantitative data represents quantities and can be measured on a Numerical scale. It includes both discrete data (e.g., the number of students in a class) and continuous data (e.g., the weight of a person).

Pearson's correlation coefficient (denoted as r) is a measure of the strength and direction of association that exists between two continuous variables. It measures the degree to which pairs of data for these two variables lie on a line. The values lie between -1 and 1, where 1 indicates a perfect positive correlation, -1 a perfect negative correlation, and 0 no correlation at all.

If the population standard deviation is unknown, the sample standard deviation is used to estimate the standard error of the mean. The standard error is a measure of how much the sample mean is expected to vary from the true population mean.

If the F statistic in an ANOVA is significantly high, it suggests that the null hypothesis should be rejected. The null hypothesis in ANOVA is typically that all group means are equal.