PaceXL Version 2: Summary of options and features

Key features of PaceXL
Charts and Graphs
Ungrouped Data
Tabulations and Histograms
Grouped Data
Probability Distributions
Intervals and Tests
Analysis of Variance
Regression and Correlation
Time Series Analysis
Index Numbers
Quality Control Charts 


PaceXL is a statistics and charts add-in for Microsoft Excel, designed for introductory and intermediate courses.

PaceXL as an Add-in

Menu, toolbar and dialogs

Data Area and data types

Analysing subsets and transformations

Statistics options and results

Charts and graphs

Saving and opening files

Printing and print preview

Help system

Sample data sets


The Charts and Graphs dialog provides the options detailed below, grouped by page tab from the dialog window.

One Variable


For numerical variables:

For categorical variables:

One or More 'Y'


Cross-tab (contingency table) or grouped (frequency distribution) input format recommended:

Numerical variables (raw / ungrouped) required or recommended:

Two or More 'X'


One numerical selected for the Y axis, one numerical variable selected for the X axis, one categorical / coded variable used as a grouping variable. In effect, a different scatter plot is drawn for each category / value in the grouping variable.


Multiple pairs of Y and X variables are selected. Only numerical variables permitted.

Scatter 'Matrix'


Able to draw a scatter plot of each pair of variables included in the selection list.

'Line' of best fit options:


Ungrouped Data - Broad functions

The Ungrouped Data routine is used for analysing 'raw' data, in particular, for calculating summary measures such as the mean and standard deviation, but also for ranking, checking for outliers, etc. for numerical variables, and for frequency counts for categorical variables.

If you wish to group your raw data into frequency distributions or cross-tabs, use Tabulations and Histograms. If your data are already grouped, use Grouped Data.

The Ungrouped Data routine provides the options detailed below, grouped by page tab from the dialog window.

Numerical Data

Choose Measures


Categorical Data


For numerical variables:

For categorical variables:


Tabulations and Histograms - Broad functions

The Tabulations and Histogram routine proceeds from the Ungrouped Data routine. It is used to group raw data into frequency distributions or two-way cross-tabs (or cross-classification tables or contingency tables). It also plots histograms and column graphs of those tables. If the data set is already in grouped form, use the Grouped Data routine.

The Tabulations and Histograms routine provides the options detailed below, grouped by principal options from the dialog window.

Frequency Interval option

This is the default tab of the dialog. It operates on just one variable at a time. Users can specify intervals for grouping values by entering the lower bounds of each class. (Only the first two are required if Equal Classes are selected). The histogram plot includes a wide range of combination plots (such as histogram-dot plot).

Frequency Count option

Operates on one variable at a time. Counts how often each value occurs. This option is suitable for discrete numerical data or categorical data and is equivalent to the Frequency Count and Categorical options in 'Ungrouped Data'.

Multiple Plots option

Useful for comparing two or more distributions. Because histograms plot on top of each other, obscuring underlying plots, the default is the frequency curve. Classes are set in a similar way to Frequency Interval.

Two Variable Cross-Tab option

Operates on two variables at a time and in interval form. Numerical or categorical variables permitted. Either discrete or continuous numerical data can be used. For example, we may want a cross-tabulation of 'Gender' by 'Hours Worked' in 10-hour groups. The lower bounds of each interval for each variable are entered as for Frequency Interval. A 'Chi-Square Test of Independence' is given as an option: note that it uses an alpha level of 5%. The p-value from the test is also shown, which can be used to compare to other alpha levels if required. Cross-tabulations can be graphed. For example, Percent of Row and Percent of Column tables can be plotted as column graphs, thus providing an alternative to the tables for identifying whether relationships exist between two variables. 


Grouped Data - Broad functions

The Grouped Data routine is used when data are already in grouped form, either as a frequency distribution or as a cross-tab. (A cross-tab is also known as either a two-way cross-tabulation or a contingency table).

With Frequency Distributions, the Data Area may include more than one frequency column (for example, frequencies for males and for females and for the two combined).

(Note that the Tabulations and Histograms dialog is used for grouping ungrouped/raw data into frequency distributions and cross-tabs. Once the data are grouped, the output from 'Tabulations and Histograms' is similar to that obtained from 'Grouped Data'.)

The Grouped Data routine provides the options detailed below, grouped by page tab from the dialog window.

Frequency Distribution

With frequency distributions, the Data Area must include two data columns, including one column for the midpoints of the classes for each interval. (The midpoints should not be included as the Row Headers.) Output available includes:

Choose Measures

Two Variable Cross-Tab


Probability Distributions - Broad functions

The two broad functions of the Probability Distributions routine are to:

A Data Area is not required for any calculations.

Probability distributions available

The eight distributions available are:

Uses of this routine

The probability distribution routines can be used in a number of ways but in particular:

Performing calculations

In each case you need to:

Calculations are displayed in the dialog itself. Updating is immediate, once a value of a parameter or input value is updated.

Use the Update button to update values once an input has been altered.

You can repeat calculations for the same distribution or change distributions. However, after changing distributions, defaults are reset.

Saving results

Plots of distributions

Plots are available for each distribution as calculations are performed. Plots can be in:

Plots are updated immediately with any change in input or with the scroll bars. That is, the plots are linked to the dialog window.

The Dialog box can be reduced in size using the 'Less Dialog' button in order to view more of a particular plot.


The scroll-bars can be used to examine incremental values in key parameters and input values. For example, the standard deviation for the normal distribution can be altered gradually by clicking the scroll-bar. If the plot is shown, the height/width of the distribution will gradually alter.

Note that the scroll bars may jump to a default value before returning to your required value. This can apply to calculations and to plots.

Two X values

Two values for X may be entered for the normal, uniform, binomial and Poisson distributions (and two z values for the standard normal distribution). The probability between these two values is calculated and can be shown on a plot.

What-if possibilities

Using the scroll-bars, and other display options, 'what-if' situations can be investigated. For example, gradually changing a parameter and viewing the effects on a result or plot. Or plotting a normal distribution over a t distribution and altering the degrees of freedom, etc. 


Intervals and Tests - Broad functions

The Intervals and Tests routine is used for inferential statistics for one or two sample situations. It is one of the most powerful of the PaceXL statistics options. Input may come from a Data Area or from Summary Measures. Numerical variables and categorical variables are permitted.

The Intervals and Tests option provides the options detailed below. (Functions are grouped by operation, type of calculation, etc.)

Variable type

Calculations may be performed on:

One or two samples

Calculations can involve:

Calculation types

There are three main types of calculations:

Numerical variables

In this tab, calculations are performed for numerical variables with the following options:

Note that PaceXL uses the t distribution as the default distribution, even for large sample sizes (30 or more).

'Categorical' variables

In this tab, calculations are performed for categorical variables (including numerical coded categorical variables) with the following options:

With categorical variables, an attribute value may need to be selected, eg 'Male' or 'Female', or '0' or '1'.

Parametric v nonparametric methods

Statistical inference techniques are sometimes categorized as:

The Intervals and Tests routines includes both categories of techniques.

Finite population correction

If a population is not large:

Data source

The input source for the sample data can be:

Extra input required

Extra input may be required in the form of selecting or entering the:


Calculations are written to the Results Sheet and include:


Note that Unstacking and Selecting from a Data Area are options for this routine. These options provide a powerful means of analysing subsets of your data, for example, testing for any difference between Male and Female respondents

Calculating the sample size

Two choices for calculating the required sample size, n are:


The following plots are available:


Analysis of Variance - Broad functions

The Analysis of Variance routine is used for one factor and two factor analysis of variance.

The options available with the Analysis of Variance routine are given below.

One Factor

Options include:

Two Factor

Data are assumed to be in Stacked format and an Index variable must be included in the Data Area.




Regression and Correlation - Broad functions

The Regression and Correlations routine is used for exploring for relationships between variables using regression modelling, correlation and scatter plots.

Models are generated by simply selecting and deselecting variables as required from the dialog window.

Examples of the types of output include:

The Regression and Correlation routine provides the options detailed below, grouped by page tab from the dialog window.


Produces the following matrices for the pairs of variables chosen:

Matrices can be printed as three (or four) separate tables, or printed as a table with three (four) rows per combination.



This is the default, and principal, tab of the Regression and Correlation dialog. It is used to generate all regression models, including automated methods. Once a mode has been generated, predictions and plots can be made for that model.

Input includes:

Standard Output includes the following:

Optional output including:

Optional table of:

Optional calculation:

Optional input:

confidence interval %


Provides intervals for:

Predictions relate to the latest regression model generated.

Regression Plots

Produces the following plots:

Automated Methods

This tab is used to select, and set up, 'automated' regression methods. The default is multiple regression. Automated options are:

The output level can be set to:

The variables to be included in the model are selected from the Regression tab.

Select and New Variable


Time Series - Broad functions

The Time Series Analysis routine is used for analysing time series data. A range of calculation and plotting methods are available for exploring past behaviour, and for forecasting. Annual and sub-annual (monthly, quarterly, etc) data can be analysed.

Data period:

Number of variables:

Accuracy of fit measures given:

Forecasts available for:

Plots available for all tabs:

The Time Series Analysis routine provides the options detailed below, grouped by page tab on the dialog window.

Set Period

Data period choices:

Data period input:

Plot Series

Options for plotting past data for one or more variables:


Calculation and/or plot options:

Moving Average

Calculation and/or plot options:

Moving averages are centered for an even number of periods per cycle.

Seasonal Analysis

Calculation and/or plot options:

Conditions and notes:

Trend Fitting

Trend types:

Calculation and/or plot options:

Exponential Smoothing

Calculation and/or plot options:

Conditions and notes:


Calculation and/or plot options:


Index Numbers - Broad functions

The Index Numbers routine has two broad functions.

The first is the calculation of index numbers. This option includes calculating unweighted and weighted index numbers (price or quantity) based on inputs of prices and quantities.

The second is the use of price index numbers. This option allows for deflating a value series using a price index series, calculating percentage changes in an index series (for example, calculating the percentage rate of change in the Consumer Price Index to provide an estimate of the period inflation rate), and deriving other index series.

The Index Numbers routine provides the options detailed below, grouped by page tab from the dialog window.

Calculating Indexes

Index types:


Output options:


To calculate price (quantity) indexes, select the column for base period prices and the given (latest) period prices, and the quantities period.

Unweighted indexes

Weighted indexes

PaceXL cannot detect the period to which the weights belong. However, by selecting the appropriate weights in the Data Area, a Laspeyres Index (base year weights) or a Paasche Index (latest year weights) can be calculated.

Using indexes

One value series and one price series:

Two or more value series and one price series:


Quality Control Charts - Broad functions

The Quality Control Charts routine is mainly a plotting routine, but calculations underlying these plots can also be generated. Control charts can be drawn for numerical variables and categorical variables (or attributes).

The Quality Control Charts routine provides the options detailed below, grouped by page tab from the dialog window.

Numerical Variables

Chart types and calculations:

Options with one/some of the above:

Test available for X-Bar chart for non-conformance:

Attributes (categorical variables)

Chart types and calculations:

Options with one/some of the above:

Test available for p chart for non-conformance: