Histograms example sentences

"Histograms" Example Sentences

1. Histograms can be used to visualize the distribution of data.
2. We plotted histograms of the test scores to see how students performed.
3. Students learn to construct histograms in their introductory statistics course.
4. The data scientist created histograms of the salary data to identify outliers.
5. By examining histograms, we can determine if the data is normally distributed.
6. We created histograms of the lengths, widths, and heights to analyze the shapes.
7. The histograms showed that most of the measurements fell within a narrow range.
8. We compared the histograms of the test scores from the two groups of students.
9. The histograms revealed a positive skew in the distribution of house prices.
10. The histograms helped visualize the spread and central tendency of the data.
11. The bar charts and histograms provided a clear visual representation of the results.
12. The software automatically generated histograms of the numerical data columns.
13. The histograms showed a bimodal distribution instead of the expected normal curve.
14. The histograms revealed that the data contained some extreme outliers.
15. They created overlaid histograms to compare the distributions of multiple data sets.
16. The training module taught the students how to interpret information from histograms.
17. Histograms give a quick visual summary of the key characteristics of numerical data.
18. We analyzed the histograms to determine if the data was suitable for parametric tests.
19. The histograms indicated a right-skewed distribution of the test scores.
20. They adjusted the number of bins in the histograms to get a better visual representation.
21. The histograms displayed the variations and ranges in the measurements.
22. The histograms revealed that most of the values clustered around the mean.
23. We analyzed the histograms to determine the best way to transform the data.
24. Looking at the histograms, we saw that the data did not appear to be normally distributed.
25. Histograms and bar charts were useful for visualizing distributions in the data.
26. Data analysts often plot histograms to get an initial sense of numerical data.
27. Modifying the number of bins affect the appearance and interpretation of histograms.
28. Researchers use histograms to detect patterns and anomalies in large data sets.
29. The histogram showed that half of the measurements fell within a 100 unit range.
30. We tweaked the bin widths of the histograms to better visualize the clusters in the data.
31. Histograms provide visual clues about trends, skewness and outliers in the data.
32. The histograms gave a good indication of the range and variability of the measurements.
33. Combining histograms and descriptive statistics provides a comprehensive summary.
34. The histograms revealed that most scores clustered around the middle values.
35. The histograms helped visualize the spread, lumps and gaps in the distributions.
36. We modified bin sizes in the histograms to better identify subgroups in the data.
37. Polynomial curves were fit to the histograms to analyze the distributions.
38. Histograms allow us to visually compare distributions that have different scales.
39. Probability densities can also be approximated from histograms of sample data.
40. The histograms provided an easy visual reference for discussing the data.
41. Overlaying histograms is a useful technique for comparing distributions.
42. We analyzed the histograms for outliers, clusters and unusual features.
43. Many statistics books begin with foundational concepts about histograms.
44. Histograms assist researchers in spotting data collection and entry errors.
45. The histograms gave a much clearer picture of the data than the raw numbers.
46. The software automatically generated stacked histograms from the data frame.
47. Researchers reviewed the histograms to determine sampling methods for the study.
48. Histograms and box plots complement each other in visualizing data distributions.
49. Areas under the histograms represent probabilities of observations in each bin.
50. Histograms can help identify the statistical distribution that best fits the data.
51. Histograms give a visual profile of how concentrated or spread out the data is.
52. Corresponding histograms can show how distributions change over time or groups.
53. The histograms revealed significant variations in the measurements within each set.
54. Students must be able to construct and interpret histograms for data analysis.
55. The histograms showed that the scores were not normally distributed as expected.
56. The histograms showed that the data were positively skewed and leptokurtic.
57. Probability density functions can be estimated from the shape of histograms.
58. We examined the histograms to determine if data transformations were needed.
59. The histograms provided a quick visual check of the summary statistics.
60. Histograms give researchers an intuitive sense of the shape of a distribution.

Common Phases

1. Construct histograms from data.
2. Interpret histograms of data.
3. Examine histograms to identify patterns and anomalies.
4. Compare histograms of different data sets.
5. Adjust bin sizes in histograms.
6. Overlay histograms to visualize distributions.
7. Analyze histograms for outliers and trends.
8. Describe shapes of histograms.
9. Modify histograms to improve visualization.
10. Fit curves to histograms.