Enhance Your Learning with Probability and Statistics Flash Cards for quick revision
The measure of the likelihood that an event will occur.
The set of all possible outcomes of an experiment.
A variable that can take on different values based on the outcome of a random event.
A function that describes the likelihood of different outcomes in a sample space.
A discrete probability distribution that models the number of successes in a fixed number of independent Bernoulli trials.
A continuous probability distribution that is symmetric and bell-shaped.
A fundamental theorem in probability and statistics that states that the distribution of the sum (or average) of a large number of independent, identically distributed random variables approaches a normal distribution.
The process of selecting a subset of individuals from a larger population in order to gather information about the population as a whole.
The process of using sample data to estimate an unknown population parameter.
A range of values within which the true population parameter is likely to fall with a certain level of confidence.
A statistical method used to make inferences about a population based on sample data.
A statement that assumes there is no significant difference or relationship between variables in a population.
A statement that contradicts or negates the null hypothesis and suggests that there is a significant difference or relationship between variables in a population.
Rejecting the null hypothesis when it is actually true.
Failing to reject the null hypothesis when it is actually false.
A statistical method used to model the relationship between a dependent variable and one or more independent variables.
A measure of the strength and direction of the linear relationship between two variables.
A measure of the proportion of the variance in the dependent variable that can be explained by the independent variables in a regression model.
Data points that are significantly different from other observations in a dataset.
The application of probability and statistics concepts and techniques in various fields such as finance, healthcare, sports, and social sciences.
Computer programs and tools used for data analysis, statistical modeling, and visualization.
Methods and procedures used to analyze and interpret data in order to extract meaningful insights and make informed decisions.
Methods used to summarize and describe the main features of a dataset.
Methods used to make inferences and draw conclusions about a population based on sample data.
Mathematical equations and relationships used to calculate probabilities, perform statistical tests, and estimate parameters.
The average of a set of numbers, calculated by summing all the values and dividing by the total count.
The middle value in a set of numbers when they are arranged in ascending or descending order.
The value(s) that occur most frequently in a set of numbers.
A measure of the dispersion or variability of a set of numbers, calculated as the square root of the variance.
A measure of the average squared deviation from the mean, calculated by summing the squared differences between each value and the mean and dividing by the total count.
A measure of the relationship between two random variables, indicating the extent to which they vary together.
A function that describes the probability distribution of a continuous random variable.
A function that gives the probability that a random variable is less than or equal to a certain value.
The probability that a confidence interval will contain the true population parameter.
A measure of the likelihood that a result or relationship observed in a sample is not due to chance.
The probability of correctly rejecting the null hypothesis when it is false.
A statistical test used to determine if there is a significant association between two categorical variables.
Analysis of Variance, a statistical test used to compare the means of three or more groups.
The coefficients or weights assigned to the independent variables in a regression model, indicating the strength and direction of their relationship with the dependent variable.
The differences between the observed values and the predicted values in a regression model.
An extraneous variable that is related to both the independent and dependent variables, leading to a spurious or misleading relationship.
A statement about the population parameter(s) that is tested using statistical methods.
A procedure used to make a decision about a statistical hypothesis based on sample data.
The probability of obtaining a test statistic as extreme as or more extreme than the observed value, assuming that the null hypothesis is true.
The process of drawing conclusions about a population based on sample data, taking into account the uncertainty associated with sampling variability.
The process of formulating and estimating a statistical model to describe the relationship between variables and make predictions or inferences.
The process of organizing, summarizing, interpreting, and presenting data in order to extract meaningful insights and draw valid conclusions.
Computer programs and tools used for data analysis, statistical modeling, and visualization.
The graphical representation of data to facilitate understanding, exploration, and communication of patterns, trends, and relationships.
The difference between the observed value and the true value of a population parameter, due to sampling variability or other sources of uncertainty.
A systematic deviation of the estimated value from the true value of a population parameter, due to flaws in the study design or data collection process.