IndietroIntroductory Statistics: One Variable Data
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Statistics are observations that have been measured, recorded, collected, analyzed, and reported for use. They contain information about a group of individuals, which can be people, animals, or inanimate objects.
Individuals are objects described by a set of data, such as people, animals, or inanimate objects.
Categorical variables place individuals into specific groups or categories, such as gender, colors, size (S, M, L), grades (A, B, C), or political party.
Quantitative variables take numerical values where arithmetic operations make sense. They can be discrete (countable whole numbers) or continuous (measurable with decimals).
A discrete variable is numerical data where whole numbers make sense, like counting number of siblings or pets.
A continuous variable is numerical data where decimals make sense, like height, weight, or time.
Discrete variables are countable whole numbers; continuous variables can take any value within an interval and include decimals.
A frequency table displays how many individuals fall into each category of a categorical variable, showing counts for each category.
Relative frequency is the proportion or percentage of the total count that falls into each category, calculated by dividing the frequency by the total number of observations.
Draw axes with categories on the x-axis and counts or percentages on the y-axis. Draw bars for each category with heights corresponding to their frequency or relative frequency.
A frequency bar graph shows counts on the y-axis; a relative frequency bar graph shows percentages on the y-axis but looks otherwise identical.
A pie graph represents the total quantity (100%) as a circle, with each slice showing a component's proportion of the whole.
Multiply the relative frequency of the category by 360° to find the angle of the slice.
A histogram is a bar graph for quantitative data, showing the distribution of data across intervals or bins.
Divide the data range into intervals (classes), count how many data points fall into each interval, and list these counts in the table.
The lower boundary of each bar is included, but the upper boundary is not included in the interval.
Choose between 5 to 7 bars for clarity, then calculate the class size by dividing the data range by the number of bars.
Discrete data histograms have bars for each whole number value; continuous data histograms group data into intervals.
The range is the difference between the maximum and minimum values in the data set.
Organizing data helps visualize patterns, understand distributions, and answer questions about the data.