You use the Modify Cell Items dialog to add, remove, and reorder the cell contents. By default, the cell items you define apply to the current table, but you can optionally apply them to all tables or use them as the default for all new tables. You do this using by choosing the Apply to All Tables and Set as Default commands from the Preferences tab menu.

This lists all of the types of cell contents that you can show in your tables. To add an item to the table, select the item, and then click Add.

Lists the selected cell content types in the order in which they will be displayed in the table. To remove an item, select it, and then click Remove. To change the order of items, click Move Up and Move Down.

Show the number of cases that satisfy the row and column conditions for each cell. If the table is weighted, the counts are the weighted counts. For more information, see Counts and unweighted counts.

Express the column percentages as cumulative percentages. For more information, see Percentages.

Express the row percentages as cumulative percentages. For more information, see Percentages.

Show the count or sum of a numeric variable that would be expected in the cell if the row and column variables are statistically independent or unrelated to each other. For more information, see Expected values and residuals.

Calculated for each cell by dividing the row percentage in the cell by the row percentage for the same column in the base row. Indices show how closely row percentages in a row reflect the row percentages in the base row. The nearer a row’s indices are to 100%, the more closely that row mirrors the base row. For more information, see Indices.

This summary statistic of a numeric variable shows the largest value.

This summary statistic of a numeric variable gives a measure of central tendency. It is the arithmetic average – the sum divided by the number of cases who gave a response for the numeric variable. For more information, see Summary statistics of numeric variables.

This summary statistic of a numeric variable shows the value above and below which half of the cases fall (the 50th percentile). If there is an even number of cases, the median is the average of the two middle cases when they are sorted in ascending or descending order. The median is a measure of central tendency not sensitive to outlying values (unlike the mean, which can be affected by one or more extremely high or low values).

This summary statistic of a numeric variable shows the smallest value.

This summary statistic of a numeric variable shows the most frequently occurring value. When several values share the greatest frequency of occurrence, each of them is a mode. UNICOM Intelligence Reporter - Survey Tabulation displays only one mode in each cell – when there is more than one mode, UNICOM Intelligence Reporter - Survey Tabulation displays the first mode that it encounters in the data.

This summary statistic of a numeric variable shows the value that divides cases according to values below which certain percentages fall. For example, the 25th percentile is the value below which 25% of cases fall.

This summary statistic of a numeric variable shows the difference between the largest and smallest values – the maximum minus the minimum.

Show the difference between the count or sum of a numeric variable and the expected values. Large absolute values for the residuals indicate that the observed values are very different from the predicted values. For more information, see Expected values and residuals.

Express the count or sum of a numeric variable as a percentage of the base for the row. For more information, see Percentages.

This summary statistic of a numeric variable shows a measure of dispersion around the mean. In a normal distribution, 68% of cases fall within one standard deviation of the mean and 95% of cases fall within two standard deviations. For example, if the mean age is 45 with a standard deviation of 10, then 95% of the cases would be between 25 and 65 in a normal distribution.

This summary statistic of a numeric variable shows a measure of how much the value of the mean might vary from sample to sample taken from the same distribution. The standard error of the sample mean can be used to estimate a mean value for the population as a whole. In a normal distribution, 95% of the values of the mean should lie in the range of plus or minus two times the standard error from the mean. Additionally, the standard error can be used to roughly compare the observed mean to a hypothesized value of another mean (that is, you can conclude that the two values are different if there is no overlap in the values of the means plus or minus two times the standard error).

This summary statistic of a numeric variable shows the sum or total of the values. For more information, see Summary statistics of numeric variables.

Express the count or sum of a numeric variable as a percentage of the base for the table. For more information, see Percentages.

In a weighted table, these are the unweighted counts. In an unweighted table, the counts and the unweighted counts are identical. For more information, see Counts and unweighted counts.

This summary statistic of a numeric variable shows the sample variance, which is a measure of dispersion around the mean, equal to the sum of squared deviations from the mean divided by one less than the number of cases. The sample variance is measured in units that are the square of those of the variable itself.