3.4.1 - Scatterplots
3.4.1 - Scatterplots3.4.1.1 - Minitab: Simple Scatterplot
3.4.1.1 - Minitab: Simple Scatterplot3.4.2 - Correlation
3.4.2 - Correlation3.4.2.1 - Formulas for Computing Pearson's r
3.4.2.1 - Formulas
for Computing Pearson's r3.4.2.2 - Example of Computing r by Hand (Optional)
3.4.2.2 - Example of Computing r by Hand (Optional)3.4.2.3 - Minitab: Compute Pearson's r
3.4.2.3 - Minitab: Compute Pearson's r3.4.3 - Simple Linear Regression
3.4.3 - Simple Linear Regression3.4.3.1 -
Minitab: SLR
3.4.3.1 - Minitab: SLR3.4.3.2 - Example: Interpreting Output
3.4.3.2 - Example: Interpreting Output
What type of graph is used for two quantitative data?
A bar graph for any type of quantitative data is called a histogram. The discrete values taken by the data are labeled in ascending order across the horizontal axis, and a rectangle is drawn vertically so that the height of each rectangle corresponds to each discrete variable's frequency or relative frequency.
What graph is best for two quantitative variables?
A scatterplot is the most useful display technique for comparing two quantitative variables. We plot on the y-axis the variable we consider the response variable and on the x-axis we place the explanatory or predictor variable.
How do you determine the relationship between two quantitative variables?
The best way to determine how two variables relate to each other is by plotting the data points on a scatter plot, a graph where each data point is plotted individually. If all the points seem to follow a line of some sort, then we can interpret that relationship.