This will be a brief tutorial, since there is very little
that is required to calculate correlations and linear regressions.
To calculate a simple correlation matrix, one must use
**[Statistics => Correlate => Bivariate...]**, and
**[Statistics => Regression => Linear]** for the calculation
of a linear regression.

For this section, the analyses presented in the computer section of the Correlation and Regression chapter will be replicated. To begin, enter the data as follows,

IQ | GPA |

102 | 2.75 |

108 | 4.00 |

109 | 2.25 |

118 | 3.00 |

79 | 1.67 |

88 | 2.25 |

... | ... |

... | ... |

85 | 2.50 |

- Click on
**[Statistics => Correlate => Bivariate...]**, then select and move "IQ" and "GPA" to the**Variables:**list. [Explore the options presented on this controlling dialog box.] - Click on
**[OK]**to generate the requested statistics.

As you can see, r=0.702, and p=.000. The results suggest that the correlation is significant.

**Note:** In the above example we only
created a correlation matrix based on two variables. The process
of generating a matrix based on more than two variables is
not different. That is, if the dataset consisted of 10 variables,
they could have all been placed in the **Variables:** list.
The resulting matrix would include all the possible pairwise
correlations.

Linear regression....it is possible to output the regression coefficients
necessary to predict one variable from the other - that minimize error.
To do so, one must select the **[Statistics => Regression => Linear...]**
option. Further, there is a need to know which variable will be
used as the dependent variable and which will be used as the
independent variable(s). In our current example, GPA will be
the dependent variable, and IQ will act as the independent
variable. Specifically,

- Initiate the procedure by clicking on
**[Statistics => Regression => Linear...]** - Select and move GPA into the
**Dependent:**variable box - Select andmove IQ into the
**Independent(s):**variable box - Click on the
**[OK]**to generate the statistics.**Note:**A variety of options can be accessed via the buttons on the bottom half of this controlling dialog box (e.g., Statistics, Plots,...). Many more statistics can be generated by explore the additional options via the**Statistics**button.

Some of the results of this analysis are presented below,

The correlation is still 0.702, and the p value is still 0.000.
The additional statistics are "Constant", or *a* from the
text, and "Slope", or *B* from the text. If you recall,
the dependent variable is GPA, in this case. As such, one can predict GPA
with the following,

The next section will discuss the calculation of the ANOVA.