Tadayoshi Kaya
Biographic Data
| ID | 10711672 |
|---|---|
| NAME | Tadayoshi Kaya |
| GIVEN NAMES | Tadayoshi |
| FAMILY NAME | Kaya |
| SIGNATURE | KAYA T |
| VERIFIED | No |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2006 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Describing Quantitative Data
This entry explores three fundamental aspects of data analysis in applied linguistics: descriptive statistics, data display, and data transformation. First, it delves into descriptive statistics, highlighting its use in the interpretation and summarization of data. Then, it concentrates on measures of central tendency—mean, median, and mode—and their ability to reveal typical data behaviors. It also elaborates on measures of dispersion, such as t…
Describing and Illustrating Quantitative Data
Descriptive statistics, which aim to quantitatively summarize, organize, and visualize data sets, will be explained in detail in this entry. By first dealing with your data descriptively, you will be able to familiarize yourself with them, comprehend them more profoundly, and choose the right statistics to analyze them.
Effects of L2 instruction on interlanguage pragmatic development
No prominent works on this page.
Effects of L2 instruction on interlanguage pragmatic development
Describing and Illustrating Quantitative Data
Descriptive statistics, which aim to quantitatively summarize, organize, and visualize data sets, will be explained in detail in this entry. By first dealing with your data descriptively, you will be able to familiarize yourself with them, comprehend them more profoundly, and choose the right statistics to analyze them.
Describing Quantitative Data
This entry explores three fundamental aspects of data analysis in applied linguistics: descriptive statistics, data display, and data transformation. First, it delves into descriptive statistics, highlighting its use in the interpretation and summarization of data. Then, it concentrates on measures of central tendency—mean, median, and mode—and their ability to reveal typical data behaviors. It also elaborates on measures of dispersion, such as t…
Computer Science (2 works) · Automatic summarization (1 work) · Data Analysis (1 work) · Data Analysis with R (1 work) · Data mining (1 work) · Data science (1 work) · Data transformation (1 work) · Data type (1 work) · Data visualization (1 work) · Data Visualization and Analytics (1 work)