BUS441 Web Analytics Week 11 Quiz

The probability of observing results as extreme as the ones obtained, assuming the null hypothesis is true. Essentially, it measures the strength of evidence against the null hypothesis.

A range around a measurement that indicates the precision of that measurement. It essentially represents the uncertainty associated with a statistical estimate.

A statistical test where the alternative hypothesis specifies a direction of change, either greater than or less than the null hypothesis.

A statistical test where the alternative hypothesis states that there is a difference, but it doesn't specify a particular direction.

The error of rejecting the null hypothesis when it's actually true. This means wrongly concluding there's a significant effect when there isn't.

The error of failing to reject the null hypothesis when it's actually false. This means missing a significant difference when there actually is one.

Increasing the sample size in an experiment can reduce both types of errors.

It's important to focus on the core concepts of web analytics rather than just the technical details.

The difference in performance between a control group and a variation group. A positive lift indicates improvement, while a negative lift indicates a decline.

An experimental group that doesn't receive the treatment being tested. It's used as a baseline for comparison.

An experimental group that receives the treatment being tested.

The proportion of users who take a desired action, such as making a purchase or signing up for a newsletter.

A group of individuals or data points chosen to represent a larger population.

The entire group of individuals or data points that you are interested in studying.

The process of collecting data over a period of time to observe changes and trends.

A statistical test to compare two versions of a webpage or feature to determine which performs better. It involves randomly assigning users to different versions and measuring their performance.

A measure of how frequently a user interacts with a webpage, often expressed as the average number of pageviews per session.

The period of time a user spends on a website from the moment they enter to the moment they leave, often measured in seconds or minutes.

A period of continuous activity on a website by a single user, typically defined by a set time limit of inactivity or a specific action, like clicking a link or navigating to a new page.

The tendency for estimates of a population mean to become more accurate as the size of the sample data increases.

A statistical technique used to estimate the true average of a population based on sample data. It incorporates prior beliefs about the average into the calculation.

A statistical technique that relies solely on observed data to make inferences about a population. It does not use prior beliefs and is based on probability calculations.

A metric that has only two possible values, typically represented as 1 or 0 (e.g., 'Yes' or 'No', 'Click' or 'No Click').

A metric that can take on any value within a continuous range (e.g., order value, time spent on site).

The process of converting a continuous metric into a discrete metric by defining a threshold and categorizing data points above or below that threshold.

The problem of overestimating the true effect of a change when a small sample size is used.

Increasing the size of the sample data helps reduce the impact of random variability and provides a more accurate estimate of the population mean.