Population: A population is a complete set of individuals or objects that share a common characteristic.
Sample: A sample is a subset of a population that is selected for analysis.
Variable: A variable is a characteristic that can be measured or observed and can take different values.
Data: Data are the values of the variables collected from a sample or a population.
Descriptive statistics: Descriptive statistics summarize and describe the main features of the data.
Inferential statistics: Inferential statistics use the data from a sample to make inferences about a population.
Hypothesis testing: Hypothesis testing is a statistical method used to test a hypothesis about a population.
Confidence interval: A confidence interval is a range of values that is likely to contain the true value of a population parameter.
Regression analysis: Regression analysis is a statistical method used to examine the relationship between two or more variables.
Probability: Probability is a measure of the likelihood that an event will occur.
Central tendency: Central tendency is a statistical measure that indicates the typical or central value of a distribution of data.
Standard deviation: Standard deviation is a measure of the spread or variability of a distribution of data.
Correlation: Correlation is a statistical measure that indicates the strength and direction of a relationship between two variables.
Outliers: Outliers are data points that are significantly different from other data points in the sample or population.
Data visualization: Data visualization is the graphical representation of data to help in understanding and analyzing the data.
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