Scatter Plot Analysis in SPSS

This video tutorial demonstrates how to create a scatter plot in SPSS, including defining variables, interpreting the plot, and adding a regression line. It covers the correlation between socioeconomic status and educational attainment, showing how to customize the scatter plot and regression line for better presentation.

What is the primary purpose of creating a scatter plot in SPSS?

• To calculate the mean of a dataset

• To perform a t-test

• To visualize the relationship between two variables

• To create a pie chart

Which two variables are used in the example scatter plot?

• Temperature and Humidity

• Height and Weight

• Income and Age

• Socioeconomic status and Education

In SPSS, where should the predictor variable be placed when creating a scatter plot?

• On the x-axis

• In the title

• On the y-axis

• In the legend

What does a positive correlation in a scatter plot indicate?

• The variables are unrelated

• As one variable increases, the other also increases

• There is no relationship between the variables

• As one variable increases, the other decreases

What is the default type of regression line added to a scatter plot in SPSS?

• Logarithmic

• Linear

• Exponential

• Quadratic

How can you add a regression line to a scatter plot in SPSS?

• By selecting 'Add Line' from the menu

• By dragging a line from the toolbox

• By double-clicking the chart and selecting 'ADD fit line at total'

• By right-clicking the chart and choosing 'Insert Line'

What does the R-squared value represent in a regression line?

• The percentage of variability explained by the predictor

• The total number of data points

• The correlation coefficient

• The average of the data points

How can you remove the R-squared value from a scatter plot in SPSS?

• By clicking on it and pressing delete

• By adjusting the axis labels

• By selecting 'Hide R-squared' from the menu

• By changing the chart type

What is the significance of the regression line in a scatter plot?

• It shows the average value of the data

• It provides the median of the dataset

• It indicates the trend and relationship between variables

• It highlights the outliers in the data

What should you do if the regression line information is not needed in a report?

• Leave it as it is

• Remove it by clicking and deleting

• Change its color to make it less visible

• Highlight it for emphasis