Sigmaplot 12.5 user guide free
SigmaScanPro Worksheets. SigmaScan Image. Mocha Worksheets. Axon Text and Binary formats. For more information, see Importing Axon Files below.
To import data:. Place the cursor to the worksheet cell where you want the imported data to start. From the menus select: File Import. The Import File dialog box appears. Select the type of file you want to import from the Files of Type drop-down list.
Change the drive and directory as desired, select the file you want to read, then click Import, or double-click the file name. Depending on the type of file, the data is either imported immediately, or another dialog box appears. Copying and Pasting Data from Other Applications Perhaps the easiest way to import data from another application is to simply copy and paste it from that applications spreadsheet into SigmaPlot. This is perhaps the simplest method, especially if you cannot directly import the data into SigmaPlot.
Once you have copied and pasted the data, you can promote the top row of data the variable names - to become the column titles. After defining the data source, you can then either import tables or import using SQL structured query language. To define the ODBC data source:. To add a data source that is not on the list, click Add.
Figure Adding a Data Source. Click the User DSN tab. Select a name from the User Data Sources list. Click Add. The Create New Data Source dialog box appears. Select a driver for which you want to set up a data source from the Name list, and click Finish. Enter a name to identify the new data source. Figure Identifying the Data Source. Click Select. The Select Database dialog box appears. Select the database, and click OK. If the data source already appears in the User and System Sources drop down-list, select it.
The Import Table dialog box appears. Figure Importing Fields from a Table. Select fields in the table by moving fields from Unselected fields to Selected fields by double-clicking a selection in the list. Click Import to import the fields into the worksheet. The Field names in the database become column headings in the worksheet. All records in the table are imported. Figure Data that has been Imported into a Worksheet. Click Open to open an. Click Import to run the query and import the data.
Field names in the database become column headings in the worksheet. Only the records defined by the SQL rows are imported. Importing Excel as ODBC When importing Excel spreadsheets using the ODBC Options dialog box, you must first assign a name to each data set or a range of data which is then imported as a table; otherwise, the Excel file will not import.
Select a range of data in the Excel spreadsheet. From the Excel menus select: Insert Name Define. In the Define Name dialog box, enter a name for the range of data in the Names in workbook box. Follow the steps above for as many data sets that you would like to create, and then save the Excel file.
Now you can import this file as a database. Select the range of data by specifying the start and end of the range; the default is the entire range. Click Import to place the data in the worksheet.
From the menus select: File Import File. Select an. The Import Spreadsheet dialog box appears. Figure Import Spreadsheet Dialog Box. Select either the entire spreadsheet or a specified range of cells. Specify cells using the standard Lotus notation for example, A1:C50 for a range from cell a1 to cell c When you have finished specifying the range to import, click Import.
The selected data is imported. Note: The dialog box indicates whether or not the worksheet is in overwrite or insert mode, and where the imported data will begin. To import spreadsheet data from non-compatible programs, save the spreadsheet as either an Excel or text file, then import that file. If you want to use an Excel workbook as an actual Excel workbook within SigmaPlot , you must open the workbook instead of importing it.
Importing places the Excel data into a SigmaPlot worksheet, and does not open the workbook as an actual Excel workbook. Use this dialog box to view the text file and to specify other delimiter types, or to build a model of the data file according to custom column widths.
Figure Import Text Dialog Box. Note: A quicker method of importing text is copying the data in your source application, then opening SigmaPlot and pasting the data. To specify a different column separator, select Delimiter to activate the delimiter options; then select the appropriate type. You can select commas, hyphens, or any other characters. For example, many databases use semicolons ; as delimiters. To specify a model of the data, use dashes - to specify column widths, and bracket characters [ and ] to define the column edges.
Use a vertical bar character to indicate a single-character width column. Click Analyze to re-display the appearance of the file using the new model. To save text import formats, enter a name into the Format scheme box, then click Add. Delete unwanted import formats using the Remove button. To specify a different range, enter the rows and columns to read, then click Analyze. You can use this feature to eliminate file headers and other undesired text. When you are finished specifying the file parameters, click Import.
The specified data from the file is imported. SigmaPlot imports both text and binary data files; if you select one of these options, the Import Axon dialog box appears prompting you to select a range of data to import.
The File selected is indicated in the dialog box title. Select the range of data by specifying the Row and Column ranges; the default is the entire range. Click Import to place the data in the SigmaPlot worksheet. To select variables to import:. In the Unselected Variables list, select a variable you want to import. Note: SPSS data files use category data as the default data format. Exporting Worksheet Data Saving worksheets as non-notebook files is useful if you want edit your data in other spreadsheet applications.
Exporting worksheets does not export associated graphs. You can only export the entire worksheet. If you want to export a portion of the worksheet, delete the portion you do not want to export, then export the remainder of the worksheet.
How to Export a Worksheet 1. Select the worksheet you want to export by opening and viewing it, or selecting it in the notebook window. From the menus select: File Export. The Export File dialog box appears. Select a file format from the Files of type drop-down list, and then enter the file name, directory, and drive for the exported file.
Click Export to create the file. Exporting Worksheets as Text Files When you export a worksheet as a text file, tabs or commas are used to separate data columns and data is saved at full precision.
If you want to save a text file with data as it appears in the worksheet rather than at full precision, copy the selected data to the Clipboard, paste it into a text editor, and save it as a text file. Descriptive Statistics for Worksheets SigmaPlot automatically calculates a number of basic statistical values for all the data in your worksheet columns. For more information, see Printing Column Statistics.
To view the statistics for the currently selected worksheet:. The running calculations performed for each column appear in a Column Statistics window for that worksheet.
Figure Column Statistics Worksheet. Available Statistics To determine the statistics shown in the Statistics windows, use the Statistics Options dialog box. Most calculations ignore empty cells, missing values, and text. The following statistics appear in the Column Statistics window.
The arithmetic mean, or average, of all the cells in the column, excluding the missing values. This is defined by. Std Dev. The sample standard deviation is defined as the square root of the mean of the square of the differences from their mean of the data samples xi in the column. Missing values are ignored. Std Err. The standard error is the standard deviation of the mean. It is the sample standard deviation divided by the square root of the number of samples. For sample standard deviations.
The number of occupied cells in the column, whether they are occupied by data, text, or missing values. The arithmetic sum of the data values in the column. The value of the numerically smallest data value in the column, ignoring missing values. The value of the numerically largest data value in the column. Min Pos. The smallest positive value. The number of cells in the column occupied by missing values, denoted with a double dash symbol Either text or an empty cell.
Statistics Options To display only a portion of the available statistics, use the Worksheet Options dialog box, then select the column statistics to show or hide. To specify which statistics are shown or hidden:. Select the statistic s you want shown or hidden. Select the appropriate options to change the column widths and data display. The E expresses the power of For example, 1. Engineering Notation, which you can select as an option on the Worksheet tab of the Options dialog box, uses integral powers of 3 with 10 as the base.
Figure Figure Numbers are displayed in Column 1, dates are displayed in Column 2, and text is shown in Column 3. You can enter numbers, labels, and dates and times directly into the worksheet. You can also convert numbers to dates and times and vice versa. You can change column widths, number decimal places, or date and time format, and you can also change the color and thickness of the worksheet gridlines, and adjust data feedback colors.
Note: You can format columns to override the defaults set using the Options dialog box. Sizing Columns and Rows If the contents of your column exceed the column width, cell contents display as pound symbols. Label entries are truncated.
To change a column width:. Drag the boundary on the right side of the column heading until the column is the size you want. To change a row height:. In the Settings For list, click Appearance. Set column width and row height in the Column Width and Row Height drop-down lists. Click OK to apply the changes and close the dialog box. SigmaPlot s worksheet can display up to fourteen digits of precision regardless of how many decimal places you specify. Changing the Appearance of the Worksheet Grid You can change the color and thickness of worksheet grid lines.
Still not sure about SigmaPlot? Check out alternatives and read real reviews from real users. Pros: SigmaPlot will automatically test for normality and equal variance with simple statistical tests and let the user know if those assumptions failed and if a new test should be run.
Choose from a wide range of styles, sizes, and colors from any system font. Use in-cell formulas and other Excel data analysis tools on your data. Related documents. Lesson plan. Still not sure about SigmaPlot? Check out alternatives and read real reviews from real users. Pros: SigmaPlot will automatically test for normality and equal variance with simple statistical tests and let the user know if those assumptions failed and if a new test should be run.
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For raw and indexed data, the data is placed in two worksheet columns. Statistical summary data is placed in three worksheet columns. Setting t-Test Options Use the t-test options to: Adjust the parameters of a test to relax or restrict the testing of your data for normality and equal variance.
Display the statistics summary and the confidence interval for the data in the report and save residuals to a worksheet column. Compute the power or sensitivity of the test To set t-test options:. Select t-test from the Standard toolbar. From the menus click: Statistics Current Test Options. Assumption Checking. Adjust the parameters of a test to relax or restrict the testing of your data for normality and equal variance. For more information, see Options for t-Test: Assumption Checking on page For more information, see Options for t-Test: Results on page Post Hoc Tests.
Compute the power or sensitivity of the test. Note: If you are going to run the test after changing test options, and want to select your data before you run the test, drag the pointer over your data. Options settings are saved between SigmaPlot sessions. To continue the test, click Run Test. To accept the current settings and close the options dialog box, click OK. Options for t-Test: Assumption Checking The normality assumption test checks for a normally distributed population.
The equal variance assumption test checks the variability about the group means. Normality Testing. SigmaPlot uses the Kolmogorov-Smirnov test to test for a normally distributed population. Equal Variance Testing. SigmaPlot tests for equal variance by checking the variability about the group means. P Values for Normality and Equal Variance.
The P value determines the probability of being incorrect in concluding that the data is not normally distributed P value is the risk of falsely rejecting the null hypothesis that the data is normally distributed. To require a stricter adherence to normality and equal variance, decrease the P value. To relax the requirement of normality and equal variance, increase P.
Requiring larger values of P to reject the normality assumption means that you are willing to accept greater deviations from the theoretical normal distribution before you flag the data as non-normal. For example, a P value of 0.
Note: There are extreme conditions of data distribution that these tests cannot take into account. For example, the Levene Median test fails to detect differences in variance of several orders of magnitude; however, these conditions should be easily detected by simply examining the data without resorting to the automatic assumption tests.
Options for t-Test: Results Summary Table. Displays the number of observations for a column or group, the number of missing values for a column or group, the average value for the column or group, the standard deviation of the column or group, and the standard error of the mean for the column or group. Confidence Intervals. Displays the confidence interval for the difference of the means.
To change the interval, enter any number from 1 to 99 95 and 99 are the most commonly used intervals. Residuals in Column. Displays residuals in the report and to save the residuals of the test to the specified worksheet column.
Edit the number or select a number from the drop-down list. The power or sensitivity of a test is the probability that the test will detect a difference between the groups if there is really a difference. Use Alpha Value. Alpha is the acceptable probability of incorrectly concluding that there is a difference.
Smaller values of result in stricter requirements before concluding there is a significant difference, but a greater possibility of concluding there is no difference when one exists. Larger values of make it easier to conclude that there is a difference, but also increase the risk of reporting a false positive. Running a t-Test If you want to select your data before you run the test, drag the pointer over your data. The Pick Columns for t-test dialog box appears prompting you to specify a data format.
Select the appropriate data format Raw or Indexed from the Data Format drop-down list. Click Next to pick the data columns for the test. If you selected columns before you chose the test, the selected columns appear in the Selected Columns list.
The title of selected columns appears in each row. For raw and indexed data, you are prompted to select two worksheet columns. For statistical summary data you are prompted to select three columns. Click Finish to run the t-test on the selected columns.
To edit the report, use the Format menu commands; for information on editing reports see. Interpreting t-Test Results The t-test calculates the t statistic, degrees of freedom, and P value of the specified data. These results are displayed in the t-test report which automatically appears after the t-test is performed. The other results displayed in the report are enabled and disabled in the Options for t-test dialog box.
For descriptions of the derivations for t-test results, you can reference any appropriate statistics reference. Note: The report scroll bars only scroll to the top and bottom of the current page. To move to the next or the previous page in the report, use the up and down arrow buttons in the formatting toolbar to move one page up and down in the report. Figure The t-test Report. Result Explanations In addition to the numerical results, expanded explanations of the results may also appear.
You can enable or disable this explanatory text in the Options dialog box. Normality Test. Normality test results show whether the data passed or failed the test of the assumption that the samples were drawn from normal populations and the P value calculated by the test. All parametric tests require normally distributed source populations. This result is set in the Options for t-test dialog box.
Equal Variance Test. Equal Variance test results display whether or not the data passed or failed the test of the assumption that the samples were drawn from populations with the same variance and the P value calculated by the test. Equal variance of the source population is assumed for all parametric tests.
Summary Table. SigmaPlot can generate a summary table listing the sizes N for the two samples, number of missing values, means, standard deviations, and the standard error of the means SEM. This result is displayed unless you disable Summary Table in the Options for t-test dialog box.
N Size. The number of non-missing observations for that column or group. The number of missing values for that column or group. The average value for the column. If the observations are normally distributed the mean is the center of the distribution. A measure of variability. A measure of the approximation with which the mean computed from the sample approximates the true population mean. The t-test statistic is the ratio:. The standard error of the difference is a measure of the precision with which this difference can be estimated.
You can conclude from "large" absolute values of t that the samples were drawn from different populations. A large t indicates that the difference between the treatment group means is larger than what would be expected from sampling variability alone i. A small t near 0 indicates that there is no significant difference between the samples. Degrees of Freedom. Degrees of freedom represents the sample sizes, which affect the ability of the t-test to detect differences in the means.
As degrees of freedom sample sizes increase, the ability to detect a difference with a smaller t increases. P Value. The P value is the probability of being wrong in concluding that there is a true difference in the two groups i.
The smaller the P value, the greater the probability that the samples are drawn from different populations.
Confidence Interval for the Difference of the Means. If the confidence interval does not include zero, you can conclude that there is a significant difference between the proportions with the level of confidence specified. Larger values of confidence result in wider intervals and smaller values in smaller intervals. For a further explanation of , see Power below. This result is set Options for t-test dialog box.
The power, or sensitivity, of a t-test is the probability that the test will detect a difference between the groups if there really is a difference. The closer the power is to 1, the more sensitive the test.
An error is also called a Type I error a Type I error is when you reject the hypothesis of no effect when this hypothesis is true. Smaller values of result in stricter requirements before concluding there is a significant difference, but a greater possibility of concluding there is no difference when one exists a Type II error. Larger values of make it easier to conclude that there is a difference, but also increase the risk of reporting a false positive a Type I error.
The t-test bar chart plots the group means as vertical bars with error bars indicating the standard deviation. The t-test scatter plot graphs the group means as single points with error bars indicating the standard deviation.
Point plot of the column means. The t-test point plot graphs all values in each column as a point on the graph. Histogram of the residuals. The t-test histogram plots the raw residuals in a specified range, using a defined interval set. The t-test probability plot graphs the frequency of the raw residuals. How to Create a Graph of the t-test Data 1. Select the t-test report. On the menus choose: Graph Create Graph. The Create Graph dialog box appears displaying the types of graphs available for the t-test results.
Select the type of graph you want to create from the Graph Type list, then click OK, or double-click the desired graph in the list. The selected graph appears in a graph window. The samples are not drawn from normally distributed populations with the same variances, or you do not want to assume that they were drawn from normal populations. If you know your data was drawn from a normally distributed population, use the Unpaired t-test.
Note: Depending on your Rank Sum Test options settings, if you attempt to perform a rank sum test on normal populations with equal variances, SigmaPlot informs you that the data can be analyzed with the more powerful Unpaired t-test instead.
The null hypothesis is that the two samples were not drawn from populations with different medians. The Rank Sum Test is a nonparametric procedure, which does not require assuming normality or equal variance.
It ranks all the observations from smallest to largest without regard to which group each observation comes from.
The ranks for each group are summed and the rank sums compared. If there is no difference between the two groups, the mean ranks should be approximately the same. If they differ by a large amount, you can assume that the low ranks tend to be in one group and the high ranks are in the other, and conclude that the samples were drawn from different populations i. For more information, see Arranging Rank Sum Data on page If desired, set the Rank Sum options.
For more information, see Running a Rank Sum Test on page View and interpret the Rank Sum report. Arranging Rank Sum Data The format of the data to be tested can be raw data or indexed data; in either case, the data is found in two worksheet columns. Select Rank Sum Test from the toolbar drop-down list. Options for Rank Sum Test: Assumption Checking The normality assumption test checks for a normally distributed population.
Figure Because the parametric statistical methods are relatively robust in terms of detecting. Running a Rank Sum Test If you want to select your data before you run the test, drag the pointer over your data. Select the appropriate data format from the Data Format drop-down list.
The title of selected columns appear in each row. Click Finish to run the Rank Sum Test on the selected columns. If you elected to test for normality and equal variance, SigmaPlot performs the test for normality Kolmogorov-Smirnov and the test for equal variance Levene Median. If your data pass both tests, SigmaPlot informs you and suggests continuing your analysis using a parametric t-test.
These results are displayed in the rank sum report which appears after the rank sum test. The other results displayed in the report are enabled and disabled in the Options for Rank Sum Test dialog box. Normality test results display whether the data passed or failed the test of the assumption that they were drawn from a normal population and the P value calculated by the test.
For nonparametric procedures, this test can have failed, as nonparametric tests do not assume normally distributed source populations. This result is set in the Options for Rank Sum Test dialog box. SigmaPlot Instrumentation Framework. More than 2-D and 3-D technical graph types. Use Global Curve Fitting to simultaneously analyze multiple data.
Obtain Data from Nearly Any Source. SigmaPlot Features. Choose from a wide range of graph types to best present your results. Statistical Analysis is no longer a daunting task. Simply select the Web graph to share its data with colleagues and students Share the data behind your graphs with colleagues and students Enable colleagues to print your full report from your intranet or Web site directly from their browsers — without compromising the quality of the graphs Create an optional password while exporting your graph to limit data access to authorized users Produce Web documents without knowing HTML or embed SigmaPlot Web object graphs within HTML files to create interactive electronic reports Each worksheet can hold a list of user defined transforms that will automatically be re-run whenever the transform input data has changed.
Graphing software that makes data visualization easy. Customize every detail of your charts and graphs. Publish your charts and graphs anywhere.
Share high-quality graphs and data on the Web. Share the data behind your web-based graphs with colleagues and students Enable colleagues to print your full report from your intranetor Web site directly from their browsers — without compromising the quality of the graphs Create an optional password while exporting your graph to limit data access to authorized users Produce Web documents without knowing HTML, or embed SigmaPlot Web object graphs in existing HTML files to create interactive electronic reports.
Use SigmaPlot within Microsoft Excel. Transforms and Quick Transforms. Use the Regression Wizard to fit data easily and accurately. Use the Dynamic Curve Fitter to determine if your fit is valid. Automate Complex Repetitive Tasks. New Worksheet Features Include. Import Excel worksheet data into a SigmaPlot worksheet or Open an Excel worksheet as an Excel worksheet in SigmaPlot Mini toolbar for worksheet cell editing Zoom enabled worksheet Worksheet scrolling with mouse wheel Line widths may be placed in the worksheet for graph customization Formatted text subscript, etc.
Can hold SigmaPlot worksheets, Excel worksheets, reports, documents, regression wizard equations, graph pages, and macros. New dialog-bar-based notebook that has several states: docks, re-sizable, hide-able, summary information mode, etc.
Browser-like notebook functionality that supports drag-n-drop capabilities Direct-editing of notebook summary information. Automate Routine and Complex Tasks.
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