Scatterplotsin example sentences
Related (5): correlation, regression, outliers, trend, trendline
"Scatterplotsin" Example Sentences
Common Phases
1. The scatterplots show a positive correlation between the two variables.
2. She created scatterplots to visualize the relationship between study hours and test scores.
3. By examining the scatterplots, we can determine if a linear or nonlinear relationship exists.
4. The scatterplots indicated that there was no correlation between class size and student achievement.
5. They created separate scatterplots for each gender to determine if the relationships differed.
6. An outlier is evident in this scatterplot of weight versus height data.
7. We added trend lines to the scatterplots to illustrate the general relationships.
8. The data points form an S-shaped curve in the scatterplots, indicating a nonlinear relationship.
9. She overlaid scatterplots of the data for different years to compare trends over time.
10. Scientists create scatterplots to determine if a causal relationship exists between two variables.
11. They added labels, axes, and a title to make their scatterplots professional and informative.
12. By analyzing the scatterplots, they determined that a logarithmic trend line fit the data best.
13. The professor had students create scatterplots as part of an introductory statistics lesson.
14. The positive trend in the scatterplots suggested that the intervention was having an effect.
15. The researcher noticed a curvilinear pattern when examining the scatterplots closely.
16. The data analyst generated a series of color-coded scatterplots to visualize subgroups.
17. Descriptive statistics were calculated for the variables represented in the scatterplots.
18. Participants lined up to view the large scatterplots displayed on the wall during the poster session.
19. The software automatically generated numerous scatterplots from the dataset upon request.
20. The x-axis and y-axis labels were clearly marked on all of the group's scatterplots.
21. They added lines of best fit to their scatterplots to illustrate the strength of the correlations.
22. The scatterplots showed a positive linear correlation between height and weight.
23. Error bars were included in some of the scatterplots to show variation.
24. The most useful scatterplots used consistent axes and scales for comparison.
25. Regression lines were overlaid on the scatterplots to quantify the relationships.
26. The team created three-dimensional scatterplots to visualize trends for the additional variable.
27. They shaded scatterplot points to highlight differences in the independent variable.
28. The employee training included practice reading and interpreting scatterplots.
29. The research assistant printed and organized scatterplots for the investigator to analyze.
30. Expert readers easily spotted misleading scatterplots that exaggerated or minimized correlations.
31. Scatterplots provided quantitative evidence for the expert's hypothesis.
32. The results section of the report included several interpretive scatterplots.
33. Scatterplots can help identify mathematical patterns and relationships.
34. The scatterplots from different sites were compared to determine the generalizability of the findings.
35. Error estimates were calculated for the trend lines on the scatterplots.
36. Scatterplots indicated wide variability in the data.
37. The scatterplots showed a quadratic rather than linear relationship.
38. Scatterplots revealed a potential outlier that required further evaluation.
39. A low correlation coefficient contradicted the strong trend shown in the scatterplot.
40. Data from surveys were plotted on scatterplots to identify clusters.
41. The scatterplots were presented as evidence to support the conclusions of the study.
42. Researchers used scatterplots to explore patterns in their data before formal analysis.
43. The scatterplots suggested a curvilinear rather than linear relationship.
44. Dot plots were compared to scatterplots to highlight distribution features.
45. Numerous scatterplots with different transformations revealed the best fitting model.
46. Smoothed curves were added to reduce variability in the scatterplots.
47. The high school students learned to interpret correlation from looking at scatterplots.
48. Groups took turns generating and explaining scatterplots to their classmates.
49. Scatterplots were saved as images for inclusion in the results section of the report.
50. Annotated scatterplots were included in the final project report.