Answer:
To sketch the details of each variable and understand the descriptive characteristics of the variables in his research, Professor Wallaby can utilize various statistical tools and techniques. Some of the commonly used methods include:
1. Descriptive Statistics: Professor Wallaby can calculate measures of central tendency (mean, median, mode) and measures of dispersion (range, variance, standard deviation) to describe the variables' characteristics.
2. Histograms: Creating a histogram will help visualize the distribution of his variables. It provides insights into the shape, spread, and skewness of the data.
3. Box plots: Box plots display the minimum, maximum, median, and quartile values of a variable. They are useful for identifying outliers and understanding the distributional characteristics of the data.
4. Scatter plots: If Professor Wallaby wants to explore relationships between two variables, he can plot them on a scatter plot. It helps visualize patterns, correlations, and possible outliers.
5. Summary Tables: He can create summary tables to present key descriptive statistics of each variable, including counts, percentages, means, and standard deviations.
6. Data Visualization Tools: Utilizing data visualization tools like Excel, Tableau, or Python libraries (such as Matplotlib or Seaborn) can aid in creating informative charts, graphs, or heatmaps to depict various characteristics of the variables.
Step-by-step explanation: