The top of each bar, which is blue, represents the number of students who are enrolled at the graduate-level.ДЇrom this bar chart, we can see that overall there are more students who are Pennsylvania residents than non-Pennsylvania residents because the bar on the left is higher than the bar on the right. The bottom of each bar, which is light green, represents the number of students who are enrolled at the undergraduate-level. The bar on theВ right represents the number of students who are not Pennsylvania residents. On this stacked bar chart, the bar on the left represents the number of students who are Pennsylvania residents.

Stacked Bar Chart Penn State En r ollment by Academic Level and P A State Residency 10000 0 30000 50000 70000 P A Resident Non- P A Resident Academic Level Unde r graduate Graduate This should result in the bar chart below: Double click CountВ in the box on the left to insert it into the Y-variableВ box on the right.Under One Column of Values, select Simple.From the tool bar, select GraphВ > Bar Chart > Summarized Data in a Table.To create a bar chart using summarized data: This example uses the following data concerning Penn State undergraduate enrollment: Enrollment by Campus Campus If this is the case, follow the steps below. It is also possible to use Minitab to construct a bar chart with summarized data, for example, if you have your counts in a frequency table. In other words, the data fileВ contained one row for each case. In the exampleВ above, raw data were used.

This should result in the pie chart below: Double click CountВ in the box on the left to insert it into the Summary variablesВ box on the right.Double click CampusВ in the box on the left to insert it into the Categorical variableВ box on the right.From the tool bar, select GraphВ > Pie Chart.Enter the data into a blank Minitab worksheet with one column containing the CampusВ namesВ and a second column containing the CountВ for each campus.To create a pie chart using summarized data: It is also possible to use Minitab to construct a pie chart with summarized data, for example, if you have your counts in a frequency table. Frequencies of Class Standing Class Standing There areВ 27 students who are sophomore or below (i.e., first-year or sophomore).В In terms of percentages, 34.4% of students are sophomores andВ 42.2% of students are sophomores or below. There are 22 sophomore students in this sample. Because ordinal-level variables have a meaningful order, we sometimes want to look at the cumulative counts or cumulative percents, which tell us the number or percent of cases at or below that level.ДЄs an example, let's interpret the values in the 'Sophomore' row. The next example is a frequency table for an ordinal-level variable: class standing. Penn State Fall 2019В Undergraduate Enrollments Because this is a nominal-level variable, cumulative values were not included. The first example isВ a frequency table displaying the counts and percentages for Penn State undergraduate student enrollment by campus. Cumulative counts and cumulative percentages should only be presented when the data are at least ordinal-level. A cumulative percent is the percent in that category and all previous categories. A cumulative count is the number of cases in that category and all previous categories.

In addition to containing counts, some frequency tables may also include the percentВ of the dataset that falls into each category, and some may includeВ cumulative values. Some statistical software, such as Minitab, will use the term tallyВ to describe a frequency table.В Frequency tables are most commonly used with nominal- and ordinal-level variables, though they may also be used with interval- or ratio-level variables if there are a limited number of possible outcomes. A frequency tableВ contains the counts of how often each value occurs in the dataset.

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