Descriptive Statistics:
Descriptive statistics refers to a branch of statistics that focuses on summarizing and presenting data in a meaningful and informative manner. It involves organizing, analyzing, and interpreting a data set to describe its main characteristics, patterns, and relationships.
Measures of Central Tendency:
Measures of central tendency are statistical measures that aim to describe the central or average value of a data set. Common measures of central tendency include the mean, median, and mode.
Measures of Dispersion:
Measures of dispersion, also known as measures of variability, quantify the spread or scatter of data values around a central point. Examples of measures of dispersion include the range, variance, and standard deviation.
Frequency Distributions:
A frequency distribution is a summary table or graph that displays the number of times each observation or value occurs within a data set. It provides insights into the distribution of data and can help identify patterns and outliers.
Percentiles:
Percentiles are statistical values that indicate the relative position or rank of a specific value within a data set. They divide the data into 100 equal groups, allowing for comparisons and the identification of outliers.
Correlation:
Correlation measures the strength and direction of the relationship between two variables. It helps analyze how changes in one variable are associated with changes in another, providing insights into the dependence or independence of variables.
Regression Analysis:
Regression analysis is a statistical technique that explores the relationship between a dependent variable and one or more independent variables. It allows for the prediction or estimation of future outcomes based on historical data.
Histograms:
Histograms are graphical representations of the distribution of data by displaying it in intervals or bins along the x-axis and the corresponding frequency or count on the y-axis. They provide a visual depiction of data distribution and can reveal patterns, skewness, or outliers.