displaying in analyzing data unit test part one
Ple
The stem-and-leaf plot below shows the total number of points different gymnasts earned in a gymnastics competition. How many gymnasts scored less than 50 points?
Stem Leaf
6 1 2 2 6
5 1 4 6 8 9
4 1 2 2 7 8 9
3 6 9
A. 4
B. 6
C. 7
D. 8
The answer is C. 7.
To find the number of gymnasts who scored less than 50 points, we need to look at the stem-and-leaf plot and count the number of leaves that are less than 5 (since the stems represent tens).
We see that there are 4 leaves in the 40s, 3 leaves in the 30s, and 0 leaves in the 20s, for a total of 7 gymnasts who scored less than 50 points.
The stem-and-leaf plot shows scores on a recent math quiz for two classes. How many students in each class scored 85?
Quiz Scores
Mrs. James’s Class
Mr. Cleveland’s Class
Leaf
Stem
Leaf
8
6
7
7 6 4 3
7
5 5 7 9
9 7 5 5 3 1
8
2 4 4 5 8
3 1 0
9
2 5
Key: 8|6 means 68%
Key: 6|7 means 67%
A. Mrs. James’s class, two; Mr. Cleveland’s class, one
B. Mrs. James’s class, one; Mr. Cleveland’s class, two
C. Mrs. James’s class, two; Mr. Cleveland’s class, two
D. none of these
The answer is B. Mrs. James’s class, one; Mr. Cleveland’s class, two.
To determine the number of students who scored an 85 in each class, we need to look at the leaf corresponding to the stem of 8.
Mrs. James’s class has one leaf for 85.
Mr. Cleveland’s class has two leaves for 85.
Therefore, the answer is Mrs. James’s class, one; Mr. Cleveland’s class, two.
To display and analyze data in a unit test, you can follow these steps:
1. Set up the unit test: Create a test case or test method in your chosen programming language's testing framework (such as JUnit for Java or pytest for Python).
2. Prepare the test data: Generate or retrieve the data you want to analyze. This could be sample data, mock data, or real data from a source like a database or an API.
3. Perform the necessary calculations or transformations: Depending on the objective of your unit test, you may need to perform calculations or transformations on the data. This could involve filtering, sorting, aggregating, or applying mathematical operations, among other things.
4. Display the data: Use appropriate methods or libraries to visualize or display the data. This could include generating charts, graphs, tables, or any other format suitable for your analysis. You may use popular visualization libraries such as Matplotlib, Plotly, or seaborn in Python or JFreeChart in Java.
5. Assertion or verification: Compare the displayed data with your expected results. You can use assertions or assertions libraries like assertpy in Python or assertEquals in Java to validate if the data is as expected.
6. Run the unit test: Execute the unit test to observe the displayed and analyzed data. The testing framework will indicate whether the test passes or fails based on the assertion results.
By following these steps, you can effectively display and analyze data in a unit test, ensuring that your code operates correctly and produces the expected results.